Intelligent Agrifood Chains and Networks

Intelligent Agrifood Chains and Networks

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Intelligent Agrifood Chains and Networks Edited by

Michael Bourlakis Kent Business School University of Kent Canterbury Kent UK Ilias Vlachos Department of Agricultural Economics & Rural Development Agricultural University of Athens Athens Greece Vasileios Zeimpekis Department of Financial & Management Engineering University of the Aegean Chios Greece

A John Wiley & Sons, Ltd., Publication

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This edition first published 2011 © 2011 by Blackwell Publishing Ltd. Blackwell Publishing was acquired by John Wiley & Sons in February 2007. Blackwell’s publishing program has been merged with Wiley’s global Scientific, Technical and Medical business to form Wiley-Blackwell. Registered Office John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK Editorial Offices 9600 Garsington Road, Oxford, OX4 2DQ, UK The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK 2121 State Avenue, Ames, Iowa 50014-8300, USA For details of our global editorial offices, for customer services and for information about how to apply for permission to reuse the copyright material in this book please see our website at www.wiley.com/wiley-blackwell. The right of the authors to be identified as the authors of this work has been asserted in accordance with the UK Copyright, Designs and Patents Act 1988. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by the UK Copyright, Designs and Patents Act 1988, without the prior permission of the publisher. Designations used by companies to distinguish their products are often claimed as trademarks. All brand names and product names used in this book are trade names, service marks, trademarks or registered trademarks of their respective owners. The publisher is not associated with any product or vendor mentioned in this book. This publication is designed to provide accurate and authoritative information in regard to the subject matter covered. It is sold on the understanding that the publisher is not engaged in rendering professional services. If professional advice or other expert assistance is required, the services of a competent professional should be sought. Library of Congress Cataloging-in-Publication Data Intelligent agrifood chains and networks / edited by Michael Bourlakis, Ilias P. Vlachos, Vasileios Zeimpekis. p. cm. Includes bibliographical references and index. ISBN 978-1-4051-8299-7 1. Food–Storage. 2. Food–Transportation. 3. Business logistics. 4. Agricultural industries. I. Bourlakis, Michael. II. Vlachos, Ilias P. III. Zeimpekis, Vasileios. TP373.3.I577 2011 664.0068′7–dc22 2010041146 A catalogue record for this book is available from the British Library. This book is published in the following electronic formats: ePDF 9781444339871; Wiley Online Library 9781444339895; ePub 9781444339888 Set in 10/12pt Times by SPi Publisher Services, Pondicherry, India

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Contents

Foreword Contributors 1 Introduction Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis 1.1 Introduction 1.2 Scope and structure of this book 1.3 Conclusions References 2 Food and Drink Manufacturing and the Role of ICT Fintan Clear 2.1 Introduction 2.2 Industry structure 2.3 Food consumer trends and food legislation 2.4 Information systems and food manufacturing 2.5 Food manufacturing and supply chains 2.6 Conclusion References 3 Retail Technologies in the Agrifood Chain Michael Bourlakis 3.1 Introduction 3.2 Food retail logistics 3.3 Information technology in food retail logistics 3.3.1 Bar codes 3.3.2 Electronic data interchange 3.3.3 Data processing and information 3.4 Conclusions References 4 Basic Principles for Effective Warehousing and Distribution of Perishable Goods in the Urban Environment: Current Status, Advanced Technologies and Future Trends Nikolaos Stragas and Vasileios Zeimpekis 4.1 Introduction

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4.2 The nature of perishable foods 4.2.1 Current needs and inefficiencies 4.2.2 Official authorities and legislation for perishable foods 4.3 Warehousing operations 4.3.1 The role of warehousing 4.3.2 Types of warehouse facility 4.3.3 Warehouse operations 4.3.4 Storage of perishable goods 4.3.5 Storage inefficiencies of perishable foods 4.4 Distribution process 4.4.1 Goods distribution in urban environments 4.4.2 Types of urban freight distribution 4.4.3 Routing factors that affect urban freight distributions 4.4.4 Dynamic incidents in urban freight distributions 4.4.5 Current status in urban distribution of perishable goods 4.4.6 Distribution inefficiencies of perishable foods 4.5 New technologies in warehousing and distribution 4.5.1 Technologies for perishable food storage 4.5.2 Technologies for distribution of perishable food 4.6 Conclusions and future trends References 5 Emerging Footprint Technologies in Agriculture, from Field to Farm Gate Spyros Fountas, Thomas Bartzanas and Dionysis Bochtis 5.1 5.2 5.3 5.4

Introduction Precision agriculture Robotics in agriculture Fleet management 5.4.1 Framework 5.4.2 Algorithmic approaches 5.5 ICT technologies in agriculture 5.5.1 ISOBUS system 5.5.2 Traceability systems based on radio-frequency identification technology 5.5.3 Wireless sensor networks References 6 Telematics for Efficient Transportation and Distribution of Agrifood Products Charalambos A. Marentakis 6.1 Introduction 6.2 Technological prerequisites for telematics 6.2.1 Wireless communications 6.2.2 Positioning systems

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6.2.3 Geographical information systems Application of telematics in freight transport and distribution Investing in value of information Distribution of agrifood products: current status and needs The use of telematics in distribution of agrifood products Potential for advanced and value-adding applications 6.7.1 Vehicle routing and monitoring 6.7.2 Safety 6.7.3 Value-added applications References 6.3 6.4 6.5 6.6 6.7

7 RFID: An Emerging Paradigm for the Agrifood Supply Chain Louis A. Lefebvre, Linda Castro and Élisabeth Lefebvre 7.1 Introduction 7.2 RFID technology 7.2.1 Overview of RFID technology 7.2.2 Current drawbacks to RFID adoption 7.3 RFID potential in the agrifood supply chain 7.3.1 RFID drivers in the agrifood industry 7.3.2 RFID opportunities in the agrifood supply chain 7.4 RFID and traceability processes in the agrifood supply chain 7.4.1 Tracking and tracing 7.4.2 Food-source tracking and animal-health monitoring 7.5 RFID and quality control management processes 7.5.1 The cold chain 7.5.2 Product recalls 7.6 RFID and manufacturing processes 7.6.1 Work in progress 7.7 RFID and warehouse and distribution processes 7.7.1 Warehouse processes 7.7.2 Inventory processes 7.8 RFID and asset management processes 7.8.1 Mobile asset management 7.8.2 In-transit visibility 7.9 RFID and point of sales processes 7.9.1 Automated check-out 7.9.2 Smart shelves 7.9.3 Marketing improvement 7.10 Conclusions References 8 Food Quality and Safety Ilias Vlachos 8.1 Introduction 8.2 Food supply-chain management

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8.2.1 Food safety 8.2.2 Quality assurance schemes 8.2.3 Food safety in supply chains 8.3 Information systems 8.3.1 Information systems and foodborne diseases 8.3.2 Forecasting food safety 8.3.3 Decision-support systems for food safety management 8.4 Case studies 8.4.1 Methodology 8.4.2 Food company profiles 8.4.3 Results 8.5 Discussion References

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Traceability in Agrifood Chains Ulla Lehtinen

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9.1 9.2 9.3 9.4

151 153 155 159

Introduction Traceability and food safety legislation Traceability systems Traceability techniques 9.4.1 Global Trade Item Numbering and other barcode systems used in traceability 9.4.2 Radio frequency identification 9.4.3 New technologies References

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E-business Applications in the European Food and Beverages Industry: Evidence from the Wine Sector Michael Bourlakis and Ilias Vlachos 10.1 10.2 10.3 10.4

Introduction E-business applications: a typology E-business applications for agriculture and the food industry The role and use of ICT in the European food and beverages sector 10.4.1 Online selling 10.4.2 Impact of online selling on companies 10.4.3 E-procurement 10.5 Precision vine growing with satellite imagery 10.5.1 World wine production and consumption 10.5.2 World wine marketing and distribution 10.5.3 Use of satellite imagery in winemaking 10.5.4 The application – oenoview 10.5.5 The profile of the companies involved 10.5.6 Operations management 10.6 Conclusions References

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The Impact of Information and Communication Technologies on the Organisational Performance of Microenterprises: Evidence from Greece Ilias Vlachos and Panayiotis Chondros 11.1 Introduction 11.2 Literature 11.2.1 ICT compatibility with human resources practices, management, education, training, trained personnel and skills 11.2.2 The impact of ICT on SME performance 11.2.3 Perceived safety, trust and online transactions 11.3 Methodology 11.3.1 ‘Go-Online’ programme 11.3.2 The sampling procedure and sample 11.4 Results 11.4.1 Demographic variables 11.4.2 ICT influence on business performance variables 11.4.3 The effect of ICT applications on business performance 11.4.4 Barriers to ICT adoption 11.4.5 Factor analysis 11.4.6 Univariate analysis 11.4.7 Hierarchical regression 11.5 Discussion 11.6 Managerial implications 11.7 Limitations/future research 11.8 Conclusion Acknowledgements References

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Warehouse Technologies in Retail Operations: the Case of Voice Picking Aristides Matopoulos

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12.1 Introduction 12.2 Retail warehouse operations 12.2.1 An overview of warehouse operations 12.2.2 Warehouse order picking and the emergence of voice picking 12.3 The AB Vassilopoulos case study 12.3.1 Grocery retailing in Greece 12.3.2 Company background 12.3.3 A view of the company’s warehousing and distribution operations 12.3.4 Analysis of AB’s warehouse operations 12.3.5 Insights from the implementation of RF picking and voice picking 12.4 Conclusions Acknowledgements References

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Leveraging RFID-enabled Traceability for the Food Industry: a Case Study 209 Angeliki Karagiannaki and Katerina Pramatari 13.1 Introduction

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13.2 Background 13.2.1 RFID in supply-chain management 13.2.2 Traceability 13.2.3 RFID-enabled traceability 13.3 The context 13.3.1 The case study: a frozen food company 13.3.2 The warehouse and its operations 13.4 Alternative RFID implementations 13.4.1 RFID decisions 13.4.2 RFID improvement opportunities 13.5 The selected RFID project 13.5.1 Description 13.5.2 The functionality of the proposed traceability system 13.6 The pilot implementation 13.6.1 Evaluating the RFID-enabled traceability system 13.6.2 Results 13.7 Conclusions Acknowledgement References

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Intelligent Agrifood Chains and Networks: Current Status, Future Trends and Real-life Cases from Japan Mihály Vörös and Masahiko Gemma

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14.1 Introduction 14.2 General concepts and roles of the local food systems for improvement of quality of life 14.3 Development of local food systems in Japan 14.4 Examples of local food systems in Japan 14.4.1 ‘Budoubatake’ farmers’ market (privately-owned company) 14.4.2 ‘Rokko Blessing’ farmers’ market (JA-managed company) 14.4.3 ‘Michinoeki’ farmers’ market in Ukiha City (mixed-ownership company) 14.5 Consumer support for local markets 14.6 Conclusions References 15

The Use of Telematics in the Daily Distribution of Perishable Goods: The Case of NIKAS SA Vasileios Zeimpekis 15.1 Introduction 15.2 Background 15.2.1 Real-time fleet-management systems 15.2.2 Travel time prediction for fleet-management systems 15.3 A real-time fleet-management system for dynamic incident handling 15.3.1 Requirements elicitation process 15.3.2 System architecture

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15.4 Simulation testing 15.5 Real-life testing 15.5.1 Profile of the company 15.5.2 System operation and test case scenarios 15.6 Conclusions Acknowledgments References

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RFID-enabled Visibility in a Dairy Distribution Network Daniel Hellström and Henrik Pålsson

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16.1 Introduction 16.1.1 Problems with traditional roll containers 16.1.2 Introduction of the new roll container 16.1.3 The core problem when introducing a new roll container 16.2 Achieving visibility 16.2.1 System setup – useful data to be collected, and control mechanisms 16.2.2 Identification technology solution 16.3 Jönköping dairy implementation 16.3.1 Implementation outcome 16.3.2 Expanding the implementation to include four DCs 16.4 Cost-benefit analysis with ROI calculations and sensitivity analysis 16.5 Lessons learned 16.5.1 Implementation process 16.5.2 Indirect benefits from having visibility 16.5.3 Technology insights 16.6 Concluding discussion References

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Conclusions Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis

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17.1 Evolution of the food chain 17.2 Technologies in the food chain, key benefits and implications 17.2.1 Implications for food managers 17.2.2 Implications for large food companies and SMEs 17.3 Concluding remarks References

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Index

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Foreword

The food sector is the largest economic sector in the European Union. It consists of a complex, global and dynamically changing network of trade streams, food supply network relations and related product flows. Food supply networks are subject to dynamically changing circumstances, including fluctuations at primary production due to changes in weather or climate, which affect supply, demand and prices, and also the quality of raw material, variations in food consumption due to seasonality or the westernization of diets in Asia. Other related issues include the development of alternative uses of raw material such as bio-fuel, and, not least, the changing attitudes of society towards the consequences of the food system’s activities for environmental, social and economic issues, captured in the term ‘sustainability’. To cope with these challenges as an industry and to secure the global availability of food that is affordable, safe and of the quality and variety expected by consumers, agrifood chains and networks need to improve the flexibility and efficiency of coordination activities within the food supply network. Flexibility in the coordination of food supply networks must be robust enough to easily adapt to the wide range of possible future scenarios that food supply networks might have to face. The potential for efficient, flexible and effective coordination of agrifood chains and networks lies in the emergence of internet-based information and communication technologies. Technologies such as RFID, e-commerce and telematics provide proven potential for the improvement of efficiency in coordination and transaction processes. In particular, these technologies provide opportunities for improved flexibility in coordinating supply and demand in dynamic supply network environments. However, in contrast to many other sectors of the economy, the adoption of intelligent technologies to improve efficiency, flexibility and effectiveness is low in the food sector, especially by small and medium-sized enterprises (SMEs). The consequence of this is clear as in Europe 99% of companies in the food and beverage industry are SMEs, creating 49% of the sector’s turnover and employing 61% of the sector’s workforce. This book provides a crucial contribution to the uptake of available and emerging intelligent technologies by businesses in agrifood chains and networks. It is an extremely valuable source of knowledge and practical experience for students, public officials and managers in the food sector that will help them to sustain and strengthen the competitiveness of companies in the food sector. PD Dr Melanie Fritz University of Bonn

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Contributors

Thomas Bartzanas CERETETH Volos, Greece Dionysis Bochtis Aarhus University Tjele, Denmark

Daniel Hellström Packaging Logistics Department of Design Sciences Lund University Lund, Sweden

Michael Bourlakis Kent Business School University of Kent Canterbury, Kent, UK

Angeliki Karagiannaki Department of Management Science & Technology Athens University of Economics & Business Athens, Greece

Linda Castro ePoly Research Center Mathematics and Industrial Engineering Department École Polytechnique de Montréal Montreal, Canada

Élisabeth Lefebvre ePoly Research Center Mathematics and Industrial Engineering Department École Polytechnique de Montréal Montreal, Canada

Panayiotis Chondros Agricultural University of Athens Botanikos, Athens, Greece

Louis A. Lefebvre ePoly Research Center Mathematics and Industrial Engineering Department École Polytechnique de Montréal Montreal, Canada

Fintan Clear Brunel Business School Elliot Jaques Building Uxbridge, Middlesex, UK Spyros Fountas University of Thessaly Volos, Greece Masahiko Gemma Waseda University Tokyo, Japan

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Ulla Lehtinen University of Oulu Oulu, Finland Charalambos A. Marentakis Department of Industrial Management & Technology University of Piraeus Piraeus, Greece

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Aristides Matopoulos Department of Technology Management University of Macedonia Thessaloniki, Greece Henrik Pålsson Packaging Logistics Department of Design Sciences Lund University Lund, Sweden Katerina Pramatari Department of Management Science & Technology Athens University of Economics & Business Athens, Greece

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Nikolaos Stragas SAP Consultant ISW Consulting Ltd Metamorfosi, Athens, Greece Ilias Vlachos Department of Agricultural Economics & Rural Development Agricultural University of Athens Botanikos, Athens, Greece Mihály Vörös College for Modern Business Studies Tatabanya, Budapest, Hungary Vasileios Zeimpekis Department of Financial & Management Engineering University of the Aegean Chios, Greece

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1

Introduction

Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis

1.1

INTRODUCTION

Food has a fundamental position and enjoys a central importance in our society as it ensures health, happiness and political stability. Consequently, the management of food chains and networks is one of the most important aspects of the modern food industry. Typically in a food chain, the raw products are produced in one part of the world, are pre-processed, transported, refined, processed and repacked by a long chain of food and transport companies, and are finally distributed to the end customer in another country or continent. Food is difficult to handle along long supply chains, however, because it represents limited resources of biological raw material, has limited storage and handling time after entering the supply chain, and spoils easily if incorrectly handled or processed. These issues can lead to various logistic problems in modern food supply chains that can severely affect product quality and freshness (Bourlakis and Weightman, 2004). Neverthelesss, the end consumer expects to purchase high-quality food for reasonable prices, and the modern food industry aims to meet these expectations. Consumers are increasingly demanding new information and greater detail regarding the growing and processing of food products. Conventional supply chains are having a difficult time adjusting to these new demands for information. As a result, producers continue to grow those products they are familiar with rather than the products consumers want. In addition, the food industry is generally characterised by a fairly stable demand and is relatively predictable: with the exception of seasonal products, if food demand forecasts are precise enough, the supply chain can be organised to achieve maximum efficiency levels. Moreover, profit margins in this sector are often so low that this kind of optimisation is almost a necessity. Today, most countries have put much emphasis on food safety and other quality attributes. This has resulted from food scares and the inability of some domestic regulatory systems to prevent contaminated products from reaching store shelves. Indeed the modern food industry is quite complex and problems in the logistics management of food, for example in storage and shipping, may result in serious consequences for consumers. In the next few pages the key elements of the theme of this book, i.e. supply chain and intelligent (and information) technologies, will be defined and analysed. Specifically, supply chain management (SCM) can be seen as the management of relations to and from suppliers Intelligent Agrifood Chains and Networks, First Edition. Edited by Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis. © 2011 by Blackwell Publishing Ltd. Published 2011 by Blackwell Publishing Ltd.

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in order to provide better value to the customer at an acceptable cost. Christopher (1999, p. 29) stresses that SCM is ‘based upon the idea of partnership in the marketing channel and a high degree of linkage between entities in that channel’. A significant part of SCM consists of logistics management and a definition of logistics is provided by Christopher (2005) as: The process of strategically managing the procurement, movement and storage of materials, parts and finished inventory (and related information flows) through the organisation and its marketing channels in such a way that current and future profitability are maximised through cost-effective fulfilment of orders.

In the supply chain, products and services flow from suppliers through production, distribution and retail to the end customer. On the other hand, financial information and purchasing data move in the opposite direction (i.e. from consumers). The optimal integration of the product, information and financial flows is the essence of SCM. Furthermore, access to the best supplies, more efficient distribution and higher levels of customer service are sources of differentiation and competitive advantage (see, for example, Bourlakis and Bourlakis, 2005; 2006). Recurring problems in supply chains relate to stock-outs due to longer-than-forecast lead times or to excess stock resulting from over-optimistic forecasts (Zinn and Liu, 2001). The peculiarity of the food industry is the perishable nature of the core product. The latter requires specific handling times and conditions, as well as the need to monitor the origin of the product and the substances that go into it along the supply chain. The positive role that information and communication technology (ICT) can play in effectively tracking the information flows becomes evident in this case. Numerous definitions have been provided for ICT in general, but a definition linking ICT to logistics and supply chain management has been given by Fitzgerald and Willcocks (1994). They note that ICT is the supply of information-based technologies while logistics information systems are organisational applications, more or less information technology based, designed to deliver the logistics and supply chain information needs of an organisation and the defined stakeholders. New and more sophisticated technologies are increasing the capacity to develop and introduce new processes and new products with distinct and differentiable traits. More specifically, emerging technologies, such as telematics and radio frequency identification (RFID), are very promising and can improve the processes of supply chain execution in the food industry by supporting a number of real-time applications such as product monitoring and control as well as support track and trace services (for a generic discussion for these issues, see, for example, Giannopoulos, 1996; Finkenzeller, 2003). RFID comprises a reader/scanner/interrogator and a transponder that can read or write data content using a specified radio frequency (see, for example, Spekman and Sweeney, 2006). At a simple level, RFID involves tags that emit radio signals and devices called readers that pick up the signal. These wireless systems allow for non-contact reading and are effective in manufacturing and other environments. RFID has established itself in a wide range of markets, including livestock identification and automated vehicle identification systems because of its ability to track moving objects. It is a fundamental element of the EPCglobal Network. Telematics is the convergence of computing and communications technologies using telephone or radio to link computers for the exchange of messages. This wireless communications system is designed for the collection and dissemination of information, and particularly

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Introduction

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refers to vehicle-based electronic systems, vehicle tracking and positioning, and online vehicle navigation and information systems. The basic premise of telematics is obvious: by giving access to any form of knowledge anywhere, it speeds up the diffusion of information, saves time, increases collaboration between individuals and groups, and improves the quality of decisions (see, for example, Goel, 2007). By combining RFID technology and telematics, a series of real-time services can be offered, such as traceability and fleet/product management and control. Traceability and control of food items along the food supply chain makes it possible to gather information about the global handling history of items. This knowledge improves stable high-quality supplies and quality management, makes product recall easier, helps in reducing production, transport and storage times, improves delivery-on-demand and adds information value to food products for consumer declarations.

1.2

SCOPE AND STRUCTURE OF THIS BOOK

This edited book aims to investigate the field of emerging technologies in managing agrifood chains and networks from a number of perspectives. The main issues that will be tackled are as follows: ●

●

●

Current status: Chapters 2–4 present the current state in food logistics and indicate the major problems that are faced during production, warehousing, transportation and retailing in connection with ICT. New technologies and future trends: Emphasis is given to new technologies and intelligent systems that are able to process time-dependent information, handle dynamic incidents (e.g. the increase of temperature in a storage area) in real-time and support logistics operations in food logistics management. These technologies include telematics (e.g. real-time fleet and product management) as well as RFID, which can be implemented in the execution part of the supply chain, including warehousing, transportation and retailing. These issues are covered in Chapters 5–9. New technologies in action: The book also presents real-life case studies in Chapters 10–16 that describe the solution to an actual food logistics problem that combines systemic and logistics approaches. These case studies show how RFID technologies and telematics have been implemented in production, warehousing, transportation and retailing in order to address real-life problems.

This approach means that there are a few introductory, and to some extent theoretical, chapters (Chapters 2–4) that will familiarise the reader with the scope of the book. From these chapters academics, researchers, students and other interested readers will gain the necessary background in terms of the interplay and interrelationships between the food supply chain and ICT. Building on that background, the new technologies are emphasised in Chapters 5–9 to increase the reader’s knowledge in that area. Lastly, Chapters 10–16 cover the practical and applied dimensions of the issues examined in the previous chapters, and case studies are illustrated. These case studies involve the use of intelligent information technologies by major food chain members, such as leading national and global food manufacturers and retailers (e.g. Arla, Alpha Beta Vassilopoulos/Delhaize Group, Nikas, etc.). On a chapter by chapter basis the book is organised as follows.

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Chapter 2 is written by Fintan Clear and presents the role of ICT in the food and drink manufacturing sector. It presents the structure of the sector, followed by an overview of food legislation, consumer trends and traceability. The way in which ICT supports manufacturing processes is examined and this is followed by an analysis of how ICT supports supply chain processes from the perspective of food manufacturers. The chapter provides some ICT adoption data and critiques of ICT implementation. In Chapter 3, Michael Bourlakis discusses the issue of retail technologies in the food supply chain. More specifically, this chapter aims to introduce the reader to the food retail logistics function and its evolution over the past few decades, examining its key elements, such as composite distribution, outsourcing and warehousing. The major technologies used in the food retail logistics function are also analysed, including electronic point of sale and electronic data interchange. Chapter 4 is written by Nikolaos Stragas and Vasileios Zeimpekis. It focuses on the analysis of the basic principles for effective warehousing and distribution of perishable goods in urban environments. More specifically, it presents the current status of warehousing and distribution in the cold chain, and describes a series of advanced technologies such as RFID, smart labels, data loggers and fleet management systems. It also proposes some future trends in the area of technology. In Chapter 5 Spyros Fountas, Thomas Bartzanas and Dionysis Bochtis describe the advanced technologies and methods in the production stage in agriculture. They show how these can provide an efficient integrated in-field production system in terms of vital parameters such as product quality, resource usage, economic feasibility and environmental impact. It covers precision agriculture, field robotics, RFID technology, automated data recording and fleet management. Chapter 6 is written by Charalambos Marentakis and it analyses the use of telematics in the efficient transport distribution of agrifood products. It gives a brief overview of the technological prerequisites and components of telematics systems and applications, and deals with the application of telematics in freight business operations. The chapter also describes the benefits that a company may gain by investing in information-gathering systems and shows how telematics can support the distribution of agrifood products. Chapter 7 focuses on RFID technology and is written by Louis A. Lefebvre, Linda Castro and Élisabeth Lefebvre. The chapter starts with a review of RFID technology, including a brief description of RFID system components and a discussion of some barriers to its adoption. It then investigates the potential of RFID at all levels of the food supply chain. The chapter includes an analysis of the potential benefits of this technology for different core business processes in the food supply chain, namely traceability processes, quality control processes, warehouse and distribution processes, asset management processes and point-of-sale management processes. In Chapter 8 Ilias Vlachos presents the results of his research in food quality and safety. The chapter reviews the relevant literature in food supply chain management and its effect on food safety. It then describes the method used to collect empirical evidence from the Greek food sector, presenting the analysis of the data and its interpretation. The chapter concludes with a discussion of the author’s research results and future research directions. In Chapter 9 Ulla Lehtinen discusses the issues of traceability in the agrifood sector. The chapter underlines the importance of food safety and food quality, which has led to the development of traceability systems. The author provides information about the characteristics of traceability in the agrifood sector and describes the traceability standard EN ISO

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Introduction

5

22000:2005. The chapter also describes tracing and tracking technologies such as barcodes, microcircuit cards and voice recognition systems. In Chapter 10 Michael Bourlakis and Ilias Vlachos review the e-business applications in the food sector with an emphasis on the wine sector. Evidence from a large quantitative survey conducted by e-Business Watch is used to develop a taxonomy of e-business applications. Precision vine-growing with satellite imagery is discussed in depth as a exemplary study of the practical achievements of e-business applications. Wine companies can gain great benefits throughout the supply chain from satellite imagery, but there is a matter of excessive costs for small companies. Wine cooperatives can better afford such a cost, as shown in the presented case of ICV. In Chapter 11 Ilias Vlachos and Panayiotis Chondros discuss e-business evaluation and entrepreneurship in the Greek agri-food sector. The authors use a two-step cluster analysis to investigate and identify business groups in Greece with common attitudes towards digital penetration. They highlight the presence of significant groups with common digital attitudes towards e-business adoption. In Chapter 12 Aristides Matopoulos presents the importance of ICTs in retail warehouse operations. The chapter initially overviews the characteristics of warehousing operations and then the order-picking process is analysed along with the most important methods currently employed, with the emphasis on voice-picking. A case study of a major international food retailer (Alpha Beta Vassilopoulos, which is part of the Belgian retail group Delhaize) is provided. The case study emphasises the way the warehouse for fruit and vegetables operates and, drawing from a real company project, presents insights from the implementation of radio-frequency picking and voice-picking technology. In Chapter 13 Angeliki Karagiannaki and Katerina Pramatari describe work (in the form of a case study) undertaken for a company that deals with frozen foods. The work involves the requirement analysis, development and pilot implementation of a RFID-enabled traceability system. Based on the experience gained, several considerations are presented by the authors that could provide valuable feedback to other organisations interested in moving to a RFID-enabled traceability scheme. Intelligent agrifood chains and networks in Japan are examined in Chapter 14 by Mihály Vörös and Masahiko Gemma. The chapter analyses the general concepts and roles of the local food systems towards the improvement of quality of life, and includes a section on the development of local food systems in Japan. Three cases of local food systems in Japan are analysed in connection to ICT: Budoubatake Farmers Market, Rokko Blessing Farmers Market and Michinoeki Farmers Market. Chapter 15 is written by Vasileios Zeimpekis and deals with perishable distribution operations in an urban environment. The chapter describes a real-time fleet management system that continuously monitors the execution of the distribution plan, detects significant deviations that require rerouting, solves the related optimisation routing problem and transmits the revised plan to the vehicle, all in real time. The system has been tested in a leading Greek food manufacturing company (NIKAS), where each vehicle distributes a prespecified set of orders along a preplanned route. In Chapter 16 Daniel Hellström and Henrik Pålsson analyse the value of visibility/ traceability enabled by RFID technology in a diary distribution network. This real-life case study provides an in-depth description of a core problem, the RFID solution to the problem, the implementation process and challenges, a cost and benefit analysis with ROI calculations and a sensitivity analysis. The case study focuses on RFID implementation at Arla Foods Group, which is one of Europe’s largest dairy companies and produces exclusively milk-based products.

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Chapter 17 provides an opportunity for the editors to summarise their thoughts on the theme of the book. They briefly describe the evolution of the food supply chain over the past few decades and the relevant ICTs in the food chain, and analyse the major benefits emanating from the use of ICTs in that chain. They also elaborate on subsequent implications for a range of stakeholders, such as large food companies, small and medium-sized enterprises and food managers.

1.3

CONCLUSIONS

There is a scarcity of books dealing with the critical role of intelligent technologies in the agri-food chain, and the editors believe that this book fills a considerable gap. The book contains chapters that have theoretical and applied aspects, and cover many real-life cases. The editors are confident that this book will become an invaluable source of knowledge for researchers, managers, students, policy makers and any other person having a strong interest in intelligent information technologies and food chains.

REFERENCES Bourlakis, C. and Bourlakis, M. (2005) Information technology safeguards, logistics asset specificity and 4th party logistics network creation in the food retail chain. Journal of Business and Industrial Marketing, 20(2/3), 88–98. Bourlakis, M. and Bourlakis, C. (2006) Integrating logistics and information technology strategies for sustainable competitive advantage. Journal of Enterprise Information Management, 19(2), 389–402. Bourlakis, M. and Weightman, P. (eds) (2004) Food Supply Chain Management. Blackwell Publishing Ltd., Oxford. Christopher, M. (1999) New directions in logistics. In: Walters, D. (ed.) Global Logistics and Distribution Planning. Kogan Page, London. Christopher, M. (2005) Logistics and Supply Chain Management: Creating Value-Adding Networks, 3rd edition. Financial Times Prentice Hall, Harlow. Finkenzeller, K. (2003) RFID Handbook: Fundamentals and Applications in Contactless Smart Cards and Identification. John Wiley & Sons, New Jersey. Fitzgerald, G. and Willcocks, L. (1994) Outsourcing information technology: Contracts and the client/vendor relationship. Research and Discussion Paper 94/10. Oxford Institute of Information Management, Templeton College, University of Oxford, Oxford. Giannopoulos, G.A. (1996) Implications of European transport telematics on advanced logistics and distribution. Transport Logistics, 1(1), 31–49. Goel, A. (2007) Fleet Telematics – Real-time Management and Planning of Commercial Vehicle Operation. Springer, New York. Spekman, R.E. and Sweeney, P.J. (2006) RFID: from concept to implementation. International Journal of Physical Distribution & Logistics Management, 36(10), 736–754. Zinn, W. and Liu, P.C. (2001) Consumer response to retail stockouts. Journal of Business Logistics, 22(1), 49–71.

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Food and Drink Manufacturing and the Role of ICT

Fintan Clear

2.1

INTRODUCTION

According to the UK Food Safety Act (1990), ‘food’ is defined as ‘any substance or product, whether processed, partially processed or unprocessed, intended to be, or reasonably intended to be ingested by humans. It includes drink, chewing gum and any substance, including water, intentionally incorporated into the food during its manufacture, preparation or treatment’ (HMSO, 1990). The effective and careful handling of materials is key to efficient manufacturing processes, whatever the industrial sector, though arguably it is more critical in food manufacturing given both the perishable nature of the product and its ability to cause harm and even death to humans. Food processing began with attempts to preserve foodstuffs (e.g. drying, salting, pickling) and over time such processes have developed to include also, amongst others, bottling, canning, freezing, freeze-drying, chilling and dehydration. More recently Hughes (2004) notes processes such as ‘modified atmosphere packaging’ (related to chill chains) and ‘sous-vide’ (cooking under vacuum). In terms of the level of processing required, Atkins and Bowler (2001) note a range of interventions ranging from ‘natural’ to ‘industrial’. Processed foods such as frozen vegetables, pre-packed beverages such as tea and coffee, and butchered animal meats that may be packed and then frozen represent the natural end of this range. Products such as reformed meats (e.g. chicken nuggets), meat-substitute products based on soya, canned ‘fruit’ drinks, which may contain artificially-introduced chemicals, and soft-form ice-creams represent the industrial end. Between these extremes lie the majority of processed and manufactured foods such as ready-to-eat chilled and frozen foods, milk, egg and potato powders, pastas and pizzas, each of which will have a varying content of natural and artificial additives. To get a sense of the industry’s size, Millstone and Lang (2003) note that, globally, the food industry spent around $20 billion in 2000 alone on additives to improve the colours, flavours, textures and shelf-life of products. However, while statistics and analysis on the food trade and food manufacturing abound – from bodies such as the UN Food and Agriculture Organisation, the European Commission, and UK sources such as the Department for the Environment, Farming and Rural Affairs (DEFRA) – in relative terms the academic literature ignores food manufacturers (Van Donk et al., 2008).

Intelligent Agrifood Chains and Networks, First Edition. Edited by Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis. © 2011 by Blackwell Publishing Ltd. Published 2011 by Blackwell Publishing Ltd.

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Table 2.1

Manufacture of food products and beverages, 2005.

Subsector (code)

Firms

Turnover (£m)

GVA at basic prices (£m)

Employment (000s)

GVA per 1000 employees (£m)

Average firm turnover (£m)

Meat products (15.1) Fish products (15.2) Fruit and vegetables (15.3) Vegetable, animal oils and fats (15.4) Dairy products (15.5) Grain and starch products (15.6) Animal feed (15.7) Other food products (15.8) Beverages (15.9) Total (15)

1 005 386 441

13 751 2 220 5 048

3 395 537 1 753

112 18 40

30.3 29.8 43.8

13.3 5.8 11.4

32

1 218

121

2

60.5

38.1

533

6 767

1 103

29

38.0

12.7

121

3 324

992

14

70.9

27.5

490 3 180

3 692 21 465

692 9 171

13 185

53.2 49.6

7.4 6.8

795 6 983

16 100 72 523

4 000* 21 304

51 464

78.4* 45.9

20.3 10.5

Source: DEFRA (2007). GVA, gross value added; *2004 figures.

The structure of this chapter on food manufacturing begins with an examination of the sector’s structure, followed by an overview of food legislation, consumer trends and traceability. Then an examination is made of how information technology (IT) supports manufacturing processes and this is followed by an analysis of how information and communications technology (ICT) supports supply-chain processes from the perspective of food manufacturers. This will include some ICT adoption data and critiques of some ICT implementations.

2.2

INDUSTRY STRUCTURE

The UK agri-food sector comprises a number of industries described as agriculture, fisheries, food and drink wholesaling, food and drink retailing and food service industries (Curry et al., 2002). In 2006 these industries accounted for a gross value-added sum of £79.4 billion and in the fourth quarter of 2007 they employed 3.7 million people (DEFRA, 2008). Food and drink manufacturing contributed £21.2 billion (DEFRA, 2008). The food supply chain is a series of links and interdependencies that take in primary producers, manufacturers, wholesalers, retailers, agents, logistics providers and shippers, encompassing enterprises running from ‘farm to fork’. Focusing on food and drink manufacturing, Table 2.1 gives a breakdown of industry subsectors as defined by DEFRA (2007). The table shows each of these with its Standard Industry Code (SIC) and by number of firms, turnover, gross value added, employee numbers and related quotients. The largest subsector on a number of counts is ‘other food products’, which includes the manufacture of bread, cakes, biscuits, sugar, confectionary, pasta, sauces, tea and coffee. According to the average firm turnover figures in the final column, the largest firms appear to be in the grain, oils and beverages subsectors, which DEFRA (2007) argues

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Table 2.2 Number of employees in UK agriculture, fishing and food manufacturing sectors, June 2001 to June 2005.

Agriculture and fishing* Manufacture of food, beverages and tobacco Total

2001 (000s)

2002 (000s)

2003 (000s)

2004 (000s)

2005 (000s)

272

251

224

224

239

482

466

458

446

435

754

717

682

670

674

*Seasonally adjusted. Source: Boothby et al. (2007), citing Labour Market Trends, Feb 2006, National Statistics website via Keynote 2006.

tend to be highly capitalised, with relatively low labour requirements and therefore relatively high labour productivity (as shown in the penultimate column). Food and drink manufacturing includes a broad swathe of activities, taking in primary processing activities such as cereal milling, all the way to more complex activities such as the manufacture of ready meals, which may require many stages of production. DEFRA figures show food and drink manufacturing encompassing 6947 enterprises (including 9015 manufacturing sites) and 394 000 employees (DEFRA, 2008). Evidence from Ireland shows that smaller food manufacturers are reducing in number, a result, Cantillon et al. (2006) argue, of manufacturers’ failure to understand the developing market and their under-performance in generating Irish and British retailers’ sales and margins. Table 2.2 includes detail for the years 2001 to 2005 for the manufacture of food, beverages and tobacco, and shows a decline in employment from 482 000 to 435 000 over the period. Nevertheless the food manufacturing (etc.) sector remains the UK’s largest manufacturing sector and additionally is a key customer for UK agriculture, buying 75% of its output (FDF, 2007). This latter sector (described in Table 2.2 as ‘Agriculture and fishing’) shows a decline in employment similar to that in manufacturing over the period. Food and drink manufacturers evince a heterogeneity of size and product scope, ranging from large multi-billion dollar transglobal operations, with a host of production sites and product ranges (e.g. Nestle, Unilever), all the way to small individual cottage industries with perhaps single product offerings. Using 2006 statistics, breakdown by ‘local unit’ and employee size band for the food and drink manufacturing sector (ONS data cited by Boothby et al., 2007) shows 5190 production sites in the UK with between 0 and 9 employees (where zero employees implies a sole trader), 2465 sites with 10 to 49 employees, 1120 with 50 to 249 employees, and 420 with 250 employees and more.1 Structural changes within the food sector have led to high concentration ratios of food manufacturers and processors within the European Union (EU; Atkins and Bowler, 2001), a phenomenon that has been noticeable in the UK agri-food industry. Cox et al. (2003) assert that concentration in most parts of the UK supply chain has been the result of backward vertical integration initiated by the powerful retail buyers. The power imbalances that exist 1

While this ONS data uses employee numbers to classify local units, employee numbers is one aspect by which the European Commission defines whole enterprises. Thus a ‘large’ enterprise has 250 employees and more, ‘mediumsized’ enterprises have between 50 and 249, ‘small’ enterprises have between 10 and 49, and ‘micro’ enterprises between 0 and 9. Taken together, micro, small and medium-sized firms constitute SMEs (small and medium-sized enterprises).

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Intelligent Agrifood Chains and Networks Table 2.3 UK own-label and branded market shares of chilled ready meals. Brand Tesco Marks & Spencer Sainsbury Asda Morrisons Waitrose Other own label Own-label subtotal Branded Total

Turnover (£m) 396 348 286 155 134 80 96 1495 46 1541

Market share (%) 26 23 19 10 9 5 6 97* 3 100

Source: Mintel, 2008. Rounding gives a market share for the own-label subtotal of 98%, but in aggregate terms this figure is actually 97%.

within UK agri-food chains reflect increased buyer concentration (Hingley, 2005) with a downstream shift of power away from producers and towards multiple retailers (Bourlakis, 2001). Given that the top four UK retailers now account for 75.6% of the national grocery market (DEFRA, 2008),2 the multiple retailers are seen as gate-keepers between producers and consumers (Lang, 2003). Thus Senker (1986; 1988) observes how the impetus for innovation in processed food is moving from branded manufacturers to retailers in the UK (cited in Cox et al., 2003). One of the most competitive areas for food chains is the ready-meals market. Such food products reflect the need for firms to meet individual consumer requirements much more closely, resulting in ‘innovative, value-enhanced commodities that sell for premium prices’ (Cox et al., 2002). Mintel (2008) figures in Table 2.3 show sales of chilled ready meals. With 97% market share, this sector is dominated by the multiple retailers and their ownlabel products (known in the USA as ‘private label’). In 1997 two-thirds of all product stocking units in Sainsbury’s stores were own-label, while in the USA fewer than one-fifth were (Cotterill, 1997). Examination of the UK frozen ready-meal market for 2007 shows a similar pattern to the chilled ready-meals field. Although the total market for frozen meals declined by 29% between 2003 and 2007 (from £684 million to £483 million), own-label dominance of this market climbed from 52% in 2003 to 62% in 2007. Birds Eye had 16% of the market in 2007, Heinz/Weight Watchers had 11%, Findus had 4%, with other manufacturers having 7%. Food manufacturers’ share of the UK frozen ready-meal market had therefore declined from 48 to 38% of the whole market sector between 2003 and 2007 (Mintel, 2008). The virtual oligopoly of food retailers has direct implications for the manner in which ICT is used in food and drink manufacture. Apart from financial stability, Fearne and Hughes (2000) note that electronic integration is a pre-requisite for firms trying to supply the large retailers. Desirable aspects in a trading partner, they observe, include an organisational

2

Tesco (31.5%), Asda (17.3%), Sainsbury’s (15.8%) and Morrisons (11.0%) accounted for 75.6% of the UK grocery market in the 12 weeks ending 7 September 2008 (DEFRA, 2008).

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structure and business culture that seeks to meet customer needs at all levels of the business, an ability to exploit and add value to market information, and an ability to measure and control the full costs of servicing customer requirements. All of these put a premium on the capture, storage and exploitation of information in digital form, and its seamless exchange with a trading partner. The large retailers appear to be looking to work with a smaller number of suppliers who have an ability to deliver to scale and with whom they can develop partnerships (Fearne and Hughes, 2000; Hingley, 2001). Thus an inability to offer in-depth informational collaboration using electronic means can bar food manufacturers from supplying the big retailers directly.

2.3

FOOD CONSUMER TRENDS AND FOOD LEGISLATION

In overall terms, the market is becoming ever more consumer-driven (McGuffog, 1999; Van Donk, 2000; Kinsey, 2003), obliging food manufacturers to respond with, for example, increased numbers of pack sizes, new product recipes and new products (Meulenberg and Viaene, 1998, cited in Van Donk et al., 2008). Some general food trends have been evident for a number of years, with Keuning (1990) citing a lowering emphasis on family meals, greater levels of eating out, ‘grazing’ (i.e. snacking), more demand for convenience and microwaveable meals, greater demand for quality and use of natural constituents, and also demands for food to meet special dietary needs. The UK food manufacturing sector has been obliged to respond to demands for fewer calories, less saturated fat and more polyunsaturated and monounsaturated fat, more complex carbohydrates, more fibre and less salt in processed foods, in addition to fewer food additives. Sales trends since 2003–4 show the UK population increasing its purchase of ‘healthy’ foods such as fruit, vegetables, fish and high-fibre breakfast cereals whilst decreasing purchases of ‘unhealthy’ foods such as soft drinks, sweetened breakfast cereals and confectionery (DEFRA/ONS, 2008). While Mintel (2008) note a shift towards home cooking and away from ready-prepared foods, nevertheless four in ten respondents in their survey cite convenience as often playing a role in their food-purchase decisions. Concerns for food quality have stimulated demand for alternative foods, including ‘functional foods’ or ‘neutraceuticals’: foods which have added nutrients such as vitamin C, zinc and Omega 3, for example, or added fibre (Food from Britain, 2006). This market was worth £2.8 billion in Europe in 2004 and was projected to be in excess of £1.7 billion in the UK by 2007 (Food from Britain, 2006). For those seeking to avoid adulterated foods (including genetically modified products), the demand for organic foods has risen during the last 10 years, with total sales in the UK for 2005 of £1.3 billion, or 2% of the total of food and non-alcoholic drink sales (Food from Britain, 2006). In tandem with these worries, concerns have grown about ‘food miles’ (i.e. the distance that foods travel before appearing in shops) and animal welfare. The pressures felt by food and drink manufacturers are added to by concerns about waste in foodsupply chains, both in terms of food product and food packaging. As an example, one body attempting to galvanise efforts by public and private sector alike is WRAP (Waste Resources Action Programme), a UK government-sponsored effort promoting greater carbon neutrality in industrial, commercial and domestic operations (http://www.wrap.org.uk). Shifting consumer trends are also influenced by demands for safer foods, with consumer trust in food producers being shaken in recent years by several food scares. Apart from incidences of salmonella, listeria and E. coli in processed food, BSE (bovine spongiform

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encephalopathy) and foot and mouth disease have had major implications for food chains in general and the red meat food chain in particular. These potent biological threats, allied with contamination (e.g. Sudan Red) and foreign-body scares, have led to more stringent EU legislation on the traceability of products through the different stages of production and distribution in the food chain. Thus EU Regulation 178/2002 (which came into force in 2005) requires that food and feed-business operators be able to identify any person from whom they have been supplied a food, a feed, a food-producing animal or any substance intended to be, or expected to be, incorporated into a food or a feed. In the USA, other imperatives can drive policy, but although the Public Health Security and Bioterrorism Preparedness and Response Act of 2002 may be the product of concerns for national security, the demands for track–and-trace in food-supply chains have the same thrust – one that includes the capture of detailed records on receipt and shipment of goods (Hulme, 2005). Whatever the driver, food businesses need to have systems and procedures in place that allow for food lifecycle information to be captured and made available to the competent authority on demand within a few hours. Naturally the complexity of this task depends on the particular food or drink product under examination – a chilled meal, for example, with a large number of ingredients sourced from around the globe, and which includes meat or fish, naturally presents a more significant informational challenge than some less-complex food product with perhaps no meat or fish, a limited number of ingredients and local sourcing. The heterogeneity of food and drink products is reflected in the legislative framework governing food handling, manufacturing and processing in the UK, which is complex, with every food type having its own regulations and codes of practice. The Food Safety Act 1990 is important legislation in this regard, enabling the 2006 Food Hygiene Regulations and responsible for the establishment of the Food Standards Agency (FSA). The 1990 Act introduced due diligence for food producers, such that responsibility for ensuring the quality of food extends to include their upstream suppliers and is not just an exercise of control of foodstuffs within a producer’s domain (Hobbs et al., 2002). Food buyers are therefore required to take all reasonable steps to ensure that food received from upstream suppliers is safe. Fearne and Hughes (2000) find the use of the word ‘reasonable’ to be critical. The term is sufficiently vague, they argue, that retailers have been encouraged to take extraordinary steps to assure the safety of products from suppliers. Thus a desire to develop own-label products has encouraged the multiple retailers, in effect, to take control of the food chain ‘by instituting stringent quality assurance programmes with their suppliers, with a particular emphasis on traceability’ (ibid). Thus Fearne and Hughes (2000) observe that the 1990 Act has had the effect of driving vertical co-ordination backwards from the retailer rather than forwards from the grower/processor. From an informational perspective, the Food Labelling Regulations 1996 (as amended) requires that foods – with certain exceptions – should carry labels with information including the name of the food, a list of ingredients (in descending order by weight), a best-before or use-by date, storage information, name and address of the manufacturer, and whether the food has been irradiated. Certain foods (such as chocolate, condensed and dried milk, fruit juices, jams and honey) have their own particular regulations. Smith (2006) argues that the quality and safety of food is based on a number of factors, which include the quality of the air surrounding the food, manufacturing procedures, personnel discipline, equipment used, premises, raw materials, packing materials and validated quality-assurance procedures. However, while zero risk for those consuming food and drink is desirable, it is technically impossible to guarantee. In fact, the most frequently occurring

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reasons for food products not meeting consumer expectations are poor-quality raw materials, inadequate process control during production, poorly trained process operators and contamination by spoilage organisms, chemicals or foreign bodies (Efstratiadis et al., 2000). Nevertheless, efforts to minimise risk are fundamental to food safety controls. One internationally recognised approach to risk management in food supply is the hazard analysis and critical control point (HACCP) approach. This approach is viewed as a systematic method through which food safety hazards can be identified, monitored and continuously controlled. It necessarily requires a proactive and hence preventative approach to food safety. EU food-hygiene legislation recommends the use of HACCP. For example, EU Regulation 852/2004 (which applies to all food business operators except farmers and growers) requires food business operators, and especially those handling meat, to implement and maintain hygiene procedures based on the seven HACCP principles, including the establishment of documents and records to demonstrate the effective application of food hygiene methods. Such requirements have implications for food processors and the capabilities of their information systems. Folinas et al. (2006) note that there are two types of traceability information flows: (i) (ii)

The ‘one step up, one step down’ flow model. The aggregated flow model.

Most food businesses use the first flow model, one that is suggested by EU legislation (178/2002). This sees some traceability information filtered and retained at each stage of the supply chain, with other data transferred to the next stage of the food chain to follow the product. Thus the final consumer receives only a subset of the food-chain data, which typically includes basic product features such as origin and quality. Although the consumer will not have access to all the information generated along the food chain, the intention is that such data can be recovered by tracing upstream through the different processors/suppliers/ distributors and their data stores if necessary. Folinas et al. (2006) note that the other flow model aggregates all food-chain data so that it follows the product from ‘farm to fork’. This model is usually undertaken in the case of organic food, fresh fish and meat, for which particular production and treatment methods have been followed, and for products that need to specify that they are free of genetic modification (FSA, 2002). However, as with any insurance system, it is only at a time of crisis that such traceability systems get tested, with product recalls requiring integrated working or joined-up thinking by local government, food manufacturers, retailers and logistics providers. Although the Curry Report (2002) argues that ‘full electronic traceability of livestock should be achieved as soon as possible’ (p. 50), in practice there is a broad range of traceability methods by which data within a food supply chain is captured and stored, ranging from paper-based systems, through hybrid systems that combine paper with machines, and end-to-end or ‘seamless’ electronic systems that exploit high-technology such as radio frequency identification (RFID). In any transformation activity – such as cooking – inputs can differ substantially from outputs. For example, apples, flour, milk, butter, sugar, salt and spices, subject to processes, including preparation, mixing, baking, finishing and packing, can be transformed into apple pies. Full traceability of the constituents would see consignment details for each input captured appropriately and stored in digital form. As transformation activities take place, operational data is collected (e.g. input volumes, chemical constituency, temperatures and process durations, etc.) to supplement consignment details. Finally output

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data (e.g. allocated best-before dates) and logistics data (e.g. dispatch date and time) can be captured and consolidated into an electronic record for the food product’s lifecycle. A subset of data from this record then follows the finished apple pie as it moves downstream from food manufacturer to the consumer, either directly to retailer or indirectly via a wholesaler. Full electronic traceability – for livestock as for any other food source – therefore requires that all actors involved in the supply of foodstuffs (primary producers, manufacturers, retailers, agents, logistics providers, etc.) be in a position to collect data and to transmit it in some precisely defined electronic form to trading partners. Thus when a food scare dictates expeditious data gathering back up the supply chain, the sources and processing undergone by suspect products can be determined in short order. The relative efficiency of such traceability systems is dependent therefore on the manner in which different data capture methods along a food chain can be integrated (Folinas et al., 2003). Such integration begs questions of firms and their business processes in a sector where historically a partnership philosophy has been absent, especially upstream in food supply chains (Hughes, 2004). So even if the technology to support integrated electronic working is relatively cheap, in order to encourage electronic traceability, UK business support agencies (e.g. BusinessLink) and sector trade associations (e.g. the Institute of Grocery Distribution and the Food and Drink Federation) feel the need to offer guidance to food manufacturers and their suppliers on what constitutes good practice. Such advice might cover, for example, technology adoption, skills development, and pointers to case studies highlighting implementation successes. This is in the face of complaints, for example, that so-called experts push ways of working that are not relevant to the food and drink sector (Pendrous, 2006).

2.4

INFORMATION SYSTEMS AND FOOD MANUFACTURING

Information technology and information systems can be used in a number of spheres in food manufacturing (as implied above), such as controlling manufacturing processes, managing material flows, receiving data from suppliers, sending data to customers and maintaining an audit on production activity for process conformance and product traceability. In this section, information systems and their role in serving manufacturing processes is examined first, followed by examination of how such systems support food manufacturers in their supply-chain processes. In simple terms, food processors add value by transforming raw materials into (semi-) finished products. This requires the provision of manufacturing plant, machinery and labour and the deployment of transactional aspects such as the transport of materials into, through and out of the plant, and processes including goods receipt, manufacturing, packaging, storage and dispatch. Traditionally, manufacturers have focused on minimising costs while meeting quality standards (McGuffog, 1999). In this vein the larger manufacturing concerns since the 1970s have exploited IT-supported materials handling systems such as materials requirements planning (MRP) and then manufacturing resource planning (MRP II) to manage materials flows and inventories in line with production schedules. The two meanings for ‘MRP’ display an evolution in informational terms over the scope of control. Nevertheless consumer demand for greater variety, quality and freshness have added to the commercial pressures in food chains for cost reduction and hence the adoption of new ways of working (McGuffog, 1999). Enterprise resource planning (ERP) systems, which seek to

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offer greater enterprise-wide capabilities, have been advanced as key to meeting these needs in tandem with food safety needs. A food manufacturer can avail themselves of a number of different systems to monitor, control and integrate production activities. Van der Vorst et al. (2005) outline the nature of information systems operating in an advanced production facility. On the factory floor will be machinery or robots responsible for food manufacturing processes such as cutting, blending, heating, sorting, etc., and which will rely on embedded information technology including sensors, actuators (that perform some mechanical action such as starting and stopping a machine, making adjustments to settings, etc.) and a programmable logic controller by which the machine is controlled. Such machinery may incorporate a digital control system (DCS), which will allow human operators to manually interact with it and take reports. This DCS can be linked into a supervisory control and data acquisition (SCADA) system, by which a series of different machines (and hence a production line) might be monitored and controlled. In turn the SCADA system may be linked to, and integrated with, an ERP system that will have enterprise-wide oversight over production and allied activities. The ERP system and its functional modules may sit on increasingly powerful desktop computers whose processing power can be deployed in a local setting across local area networks and in nonlocal settings across wide area networks, some of which may be wireless-enabled and global in scope. In terms of the underlying logic, the information systems described here could be applied to almost any manufacturing facility, whatever the industry sector. Key aspects that will differentiate food and drink manufacturing from other industries in broad terms are hygiene and traceability requirements. Taking a food hygiene perspective, an enterprise-wide ERP system can be used – or so ERP providers argue – to monitor and assure quality standards, and to undertake recording of materials traceability and labour use in production. In this way, if necessary, data for product recall based on material inputs, batch and /or production dates can be supplied automatically to a firm’s departments, its trading partners upstream and downstream in the food chain, and food standards authorities. Business performance can be monitored in real time, with a granularity that extends from business departments down to individual product and batch, along with labour usage and consumption of packaging materials, and the integration of financial and payroll packages. Such ERP systems can enable the automation of various functions, including purchase order management and the generation of invoices, dispatch and transport documentation, and facilitate customer portals that provide online access for clients to view invoices, delivery status, production status and traceability information. Relevant data can be delivered to PC desktops, personal digital assistants and mobile/cell phones. This is a brief overview of how ICT can be employed within manufacturing. The question then arises as to the prevalence of such ICT and the adoption levels of, for example, ERP systems within the food and drink manufacturing industry. Definitive academic data on this subject is scarce, although some evidence on ICT usage within the sector is discussed below. Table 2.4 shows ERP usage statistics, findings from an e-Business Watch (2006) survey of the food and drink manufacturing sector across a number of European countries.3 3

In all, the e-Business Watch 2006 survey included 14 081 enterprises from 10 sectors in 29 European countries, including EU member states. Data from this survey has been extracted for 10 countries (Czech Republic, Germany, Spain, France, Italy, Hungary, The Netherlands, Poland, Finland and the UK) to constitute a dataset called the EU-10. The food and drink manufacturing sector has been determined by enterprises classified as having NACE group DA 15 activities.

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Intelligent Agrifood Chains and Networks Table 2.4

ERP system usage.

Survey sample Micro firms Small firms Medium-sized firms Large firms Food and beverage (EU-10) firms All 10 sectors (EU-10) firms

Number having ERP system 4 17 33 66 10 11

Source: e-Business Watch survey of 775 firms using computers, 2006.

The data records ERP occurrence at one level only (i.e. no discrimination is made in terms of the extent to which ERP systems are deployed within enterprises and the function of ERP modules applied). However, an average of 10% of the 775 firms using computers in the sample have an ERP system (against an average for the 10-sector survey of 11%). The influence of size is apparent, with 66% of the large firms in this sample using an ERP system, while the figure for medium-sized firms is 33%, for small firms 17% and for micro firms 4%. In a US study, Ilyukhin et al. (2001) argue that trends in process control and instrumentation show that the food industry has been a laggard in comparison with other sectors in the adoption of new technologies. On the basis of the evidence in Table 2.4, this charge does not appear to have validity as far as ERP systems are concerned, at least from a sector-wide perspective. However, while technology providers such as Oracle and SAP offer case studies on ERP application in food manufacturing, academic research on the subject is limited. Otles and Onal (2004) have made a rare study of the area, and they note that initial ERP implementations amongst food and drink manufacturers are focused on financial and order management processing, and only latterly have such implementations been expanded to allow firms with more complex food manufacturing demands to be accommodated (such as responses to biological emergencies and the need for disassembly). It appears that before 2000, many food firms installed ERP systems purely in order to cope with the millennium bug issue (Otles and Onal, 2004). In any event, Davenport (2000) argues that application of ERP systems is problematic, with only 10 out of the 100 firms examined in a multisector study getting definitive value from their ERP implementation. In another rare academic study on ERP systems in food and drink manufacturing, Tsamantanis and Kogetsidis (2006) echo Davenport’s concerns and note the complexities that ERP implementations can bring and the major difficulties encountered by one firm in the Cypriot brewing industry in doing so. Trade researcher Pendrous (2006) notes distrust of IT vendors by small firms as a result of a failure to get returns on their ERP investments. Even though some small firms in the food sector will be nimble (Hughes, 2004) and more than equal to the challenges raised by the electronic mediation of trade, the mass of small businesses are characterised by a paucity of resources and expertise (Levy and Powell, 2003; Fillis et al., 2004; Quayle, 2004; Simpson and Docherty, 2004). For these businesses, any complications arising through technology adoption and new ways of working can have serious implications for their viability.

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2.5

17

FOOD MANUFACTURING AND SUPPLY CHAINS

Food and drink manufacturers sit in a chain between their raw material suppliers upstream and their finished goods customers downstream. Commercial demands by UK supermarkets for velocity, flexibility, quality, cost and service (Ryder and Fearne, 2003) mean manufacturers need to respond with reduced lead times, smaller batch sizes, postponement of the final form of manufacturing and packaging, and greater variety of handling units throughout the supply chain (McGuffog, 1999). Apart from the need to adjust internal operations, such demands imply close operational working with trading partners, and the use of supply-chain management (SCM) so that flows of materials and information, from raw materials to the end product, are synchronised to customer requirements (Stevens, 1989). SCM blurs boundaries between supply-chain entities through interfirm activities, such as the sharing of research and development, the placing of employees with other firms, the development of cost management systems across firms, collaborative inventory control and inventory placement decisions (Hill and Scudder, 2002). So, by definition, SCM goes well beyond the traditional function of materials management, for example. Information sharing is therefore seen as key to effective SCM, and when information flows seamlessly in both directions, the effect is to create a virtual supply chain (ibid). According to Cox et al. (2003), the competitive dynamics of the UK food manufacturing and retail sector were transformed in the decade leading up to 2003 as the result of the introduction of networked systems and EDI. Food sector firms use electronic data interchange (EDI) and leased telecoms lines to exchange a variety of business documents, including purchase orders, invoices and delivery schedules. With electronic funds transfer interfaces to financial intermediaries, these value-added networks (VANs) can also effect electronic payments. Significant cost savings can be made by use of EDI, with Jessup and Valarich (2003) noting how breakfast cereal manufacturer Nabisco managed to reduce the cost of processing an individual paper-based order from a notional $70 to less than $1. Nevertheless, the costs for use of a VAN and the hardware and software associated with EDI has meant that such electronic mediation has been restricted in the main to the large food manufacturers and their customers (i.e. the large multiple retailers). Definitive data on EDI usage for food manufacturing in academic sources is elusive but Hill and Scudder (2002) note a 72% level of usage by their sample of food-sector firms. In the e-Business Watch (2006) survey, of the 775 firms using computers in the sample of food and drinks manufacturers, only 6% of firms in the sample overall used EDI-based standards (arguably an analogue for EDI use). When broken down by firm size (based on number of employees), however, 67% of the large firms were shown to use EDI-based standards, with figures of 30% for medium-sized firms, 11% for small firms and 5% for micro firms. Where once electronic integration was a challenging task, with EDI applications offering complexity and significant expense (Vlachos, 2004), it is now arguably within the reach of even the smallest food firms to become e-enabled, given the ubiquity of internet access. The emergence of e-commerce and e-business has facilitated vertical electronic mediation through food chains, in addition to horizontal electronic mediation. Fritz et al. (2004) analyse developments in business-to-business (B2B) electronic trading platforms in the agrifood sector in the USA and Europe between 2000 and 2002, and find that, of the 85 platforms in existence in the year 2000, only 25 remained active in the sector in 2002. More research is required to evaluate such platforms’ function and value to the food chain – some of these

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Table 2.5

Electronically generated orders accepted by food and drink manufacturers.

Survey sample

Micro firms Small firms Medium-sized firms Large firms Food and beverage (EU-10) firms All 10 sectors (EU-10) firms Data

Accept orders from customers online

Receive up to 25% of orders online

Receive more than 25% of orders online

Use specific ICT solutions for e-selling

13 26 40

95 89 90

5 11 10

1 9 14

41 19

83 87

17 13

51 4

25

75

25

9

775 firms using computers

212 firms accepting orders online

212 firms accepting orders online

775 firms using computers

Source: e-Business Watch, 2006.

platforms, such as ICS FoodOne and Foods for Trade, appear to be classic trade directories rather than the online trading and negotiation mechanisms much vaunted during the dotcom boom. Fritz et al. (2004) note Tesco using the platforms WWRE and GNX (now since merged) for B2B activity. However, the question remains about how much neutral electronic market platforms such as these may be used by the large multiple retailers in the UK to source food and drink products. The evident power imbalance in the food chain and the relative monopsony the multiple retailers enjoy mean that suppliers and food manufacturers may be obliged to use proprietary platforms such as Tesco’s Information Exchange and Sainsbury’s Information Direct (SID) rather than neutral B2B platforms in order to stay in business. Definitive data for this supposition, however, are lacking. Table 2.5 shows data from the e-Business Watch (2006) survey on electronically generated customer orders accepted by food and drink manufacturers. The picture is somewhat variable in places but it is apparent that the sector average for orders received electronically (19% for the food and beverage category) in the sample of 775 firms is lower than the 10-sector average (25%). When the 212 firms accepting orders online are extracted from the sample, it is clear from the breakdown that for all firm sizes the majority accept only a minority of their orders online (i.e. up to 25%). A rather noticeable and perhaps surprising finding is that the proportion of orders accepted on line by large firms is not markedly different from the equivalent figure for medium-sized ones. Nevertheless, this could highlight the fact that food and drink manufacturers are obliged to use information systems other than their own as a means of collecting customer orders. Given the comments made above and the apparent failure of neutral platforms to gain significant market traction, the figure of 51% for the whole sector sample could imply that large firms use proprietary retailer platforms as a means of gathering electronically generated orders. Table 2.6 shows data for the incidence of online orders or eProcurement in the food and drinks sector, as revealed by the e-Business Watch (2006) survey. An average of 39% of the 775 firms using computers in the food and drinks sector sample placed orders online with suppliers, with the average for the 10-sector survey being somewhat greater at 48%. When the 385 firms placing orders online are extracted for analysis, large firms record a 70% rate,

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Food and Drink Manufacturing and the Role of ICT Table 2.6

19

Orders placed online by food and drink manufacturers.

Survey sample

Micro firms Small firms Medium-sized firms Large firms Food and beverage (EU-10) firms All 10 sectors (EU-10) firms Data

Place orders online

Place up to 25% of orders online

Place more than 25% of orders online

32 54 58 70 39

94 90 77 95 91

6 10 23 5 9

2 7 16 41 5

48

75

25

9

775 firms using computers

385 firms placing orders online

385 firms placing orders online

Use specific ICT solutions for e-sourcing

775 firms using computers

Source: e-Business Watch, 2006.

Table 2.7

Measures of supply-chain collaboration.

Micro firms Small firms Medium-sized firms Large firms Food and beverage (EU-10) firms All 10 sectors (EU-10) firms

Share documents in collaborative work space

Manage capacity/ inventory online

Collaborative design processes

Collaborative forecasting of demand

8 14 26 62 10

11 9 21 61 11

4 7 12 27 6

6 14 22 49 10

14

10

7

11

Source: e-Business Watch (2006). All data refer to 722 firms with internet access.

medium-sized ones 58%, small ones 54% and micro firms 32%. In an echo of the findings for orders accepted online noted above, the majority of firms, whatever their size, place only a minority of their orders online with suppliers (i.e. up to 25%), with large firms being the least interested in placing more than 25% of their orders online. Nevertheless, the survey cites the use of an apparent alternative (‘Use specific ICT solutions for e-sourcing’) for placing orders, and large firms make heaviest use (at 41%) of this avenue, as noted for the original 775-firm sample. Again, however, these data lack equivocation, and must prompt calls for further academic work on the subject. As a measure of supply-chain collaboration by food and drink manufacturers, Table 2.7 shows data from the e-Business Watch (2006) survey as a means of evaluating how embedded electronically mediated business practices are amongst food and drink manufacturers. Figures for the firms that ‘Share documents in collaborative work space’ show an average for the sector of 10% (of the 722 firms with internet access) as against 14% for the 10-sector sample. With a breakdown by firm size, it is noticeable that large firms (62%) are much

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more prepared to work electronically in this manner than smaller firms. Figures for firms that ‘Manage capacity/inventory online’ demonstrate similar findings, and the breakdown shows ‘large’ firms again scoring significantly higher than smaller firms for this aspect. However, one difference between the two sets of figures is that the sector average of 11% is slightly higher than the 10-sector average of 10%. The figures for ‘Collaborative design processes’, however, show a practice that is a lot less prevalent for food and drink manufacturers than the other two aspects discussed here, but not less than the overall figures reveal in comparison to the 10-sector average. Finally, in regard to ‘Collaborative forecasting of demand’, the overall figures shown a similarity with practice in other sectors: firm size breakdown shows almost half of large firms engaging in collaborative forecasting, with only 22% of medium-sized firms doing so. The e-Business Watch (2006) survey finds that the food and drink manufacturing sector overall shows a relatively good level of internal process integration with supply-chain activities, although size seems to be a dominant factor as regards the prevalence of ICT adoption. The interoperability witnessed is driven in part by regulatory constraints (e.g. the need for traceability) in addition to the need to maintain competitive advantage and to meet customer needs. Nevertheless, the authors highlight potential barriers to greater e-adoption because the industry has some unique characteristics, not least of which is the ‘complex value chain and the heterogeneous nature of the different players (e.g. farmers, input suppliers, manufacturers, packagers, transporters, exporters, wholesalers, retailers and final customers)’. Thus any need for coordination and synchronisation of the different entities, and use of ICT to enable such processes, is ‘hindered by their different business interests, cultural attitude and size’, which compounds the level of complexity in the small batch processes that typify the sector. If trust is critical for informational collaboration, then the Curry Commission (2002) makes for sober reading: ‘Relationships [in the farming and food industry) are, in many cases, confrontational and communications poor. The disconnection between supplier, processor and retailer is damaging efficiency’ (Curry, 2002, p. 14). Empirical research conducted by Fearne and Hughes (2000) highlights a lack of trust, for example, in the fresh produce food chain, where suppliers displayed scepticism in regard to the manner in which retailers conducted their commercial partnerships. Pointing to the pivotal role that buyers play in these relationships, the view expressed was that little had changed in retailer attitudes in recent years, with policies, for example, of rotating buyers on a regular basis making it difficult to build long-term relationships. Information sharing appeared to be limited, even with dedicated suppliers, one example being the fact that Tesco continued to charge suppliers for electronic point of sale (EPOS) data. Fearne et al. (2001) find that the food industry has been slow to adopt the partnership philosophy, with progress being particularly slow upstream in the supply chain, where Duffy and Fearne (2004) find a distinct lack of trust and a prevalence of adversarial relationships amongst trading partners. Even where information systems have been implemented in order to enable intra-organisational coordination, Taylor and Fearne (2006) cite problems with the integrity and appropriateness of demand trend data transmitted by the large retailers to suppliers. Data could be difficult to access or were incomplete in terms of longitudinal integrity. In all the food chains they studied there was a problem of data timeliness. For example, purchase orders from retailers to their suppliers would be transmitted around midday, thus giving suppliers only one or two hours to respond, given their vehicle despatch deadlines. Thus suppliers would respond by supplying from stock and would begin their production schedules at the beginning of the day without a clear idea of actual demand. Taylor and Fearne (2006) found,

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however, that the EPOS data from the branch network would be available at the retailer’s headquarters typically some eight hours before. One apparent solution to this issue, which is employed by Sainsbury’s and used by a number of manufacturers and suppliers, including Nestle (the biggest food manufacturer in the world), is a system offered by systems provider EQOS (FCC, 2005). Promotions such as buy-one-get-one-free (BOGOF) can create such high levels of demand that within hours shelves can be emptied of stock. In order to ensure that a manufacturer/processor/supplier is made aware of demand at the branch level, the EQOS web-based system (intended to be low cost and easy to use) can inform suppliers of the level of demand at the branch level so that manufacturers, etc., can spot patterns of consumption behaviour and move product quickly to meet that demand (FCC, 2005). However, as yet such systems appear to be the domain of a small select number of suppliers who have the necessary flexibility to respond in real time to changes in consumption behaviour downstream. According to Welch and Zolkiewski (2004), a collaborative or relational (rather than a commodity and arms-length) approach can have its dark side. Cox (1999), for example, notes that becoming a preferred supplier may offer ‘an operational treadmill to oblivion’ for a food manufacturer, in that the buyer (i.e. a multiple retailer) will demand continuous improvements from that supplier such that they ‘are forever engaged in the vicious circle of efficiency and cost-led competition’ (Hingley, 2005). In the medium-term there are oligopolistic benefits for suppliers that survive the consolidation process, but buying organisations then use their power to aggressively apply leverage to supply survivors to maximise value for themselves (ibid). Cox et al. (2003) draw attention to the trend cited by Nolan (2000) of firms displaying a greater tendency towards networked forms of organisation, and employing new ICT methods by which to do so. Nevertheless, not all of the information is readily available in electronic form. For example, in a study looking at IT in food safety in the dairy sector, Deasy (2002) found that in many processing plants there is no real-time integration of raw materials and quality (or laboratory) data. Additionally, such plants had no electronic links between raw material handling, processing activities and finished goods, making traceability from the customer back to raw material sources difficult. In any event, networked communications bring new operational practices in their train, not least the requirement for firms to take steps to protect digital assets. If data integrity and hence data security are important, therefore, then the fact that half of 100 SME food processors sampled in a regional survey focusing on electronically mediated trade (however manifest) had no apparent security policy (Clear, 2007) may give pause for thought. Certainly a review of the literature by Dixon et al. (2002) looking at e-business adoption by SMEs noted concerns for security and privacy, in addition to a general lack of awareness of the potential of ICT, the lack of an IT skills base, concerns for high initial set-up costs and a lack of staff to implement ICT as common barriers in this regard. If these findings are indicative, then whatever the apparent benefits of greater informational integration argued by Curry (2002), there appears to be some way to go before integrated electronic working might be seen as a safe and comfortable norm for all small food and drink manufacturers.

2.6

CONCLUSION

Food and drink are different from nearly every other product (except pharmaceuticals) that can be manufactured, in that they are designed for human ingestion. Food scares have highlighted the potential that food has to poison humans. Additionally, consumers are now much

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more aware of the quality of food and ingredients (e.g. fat, sugar, salt, etc.) in terms of healthy living and are becoming more demanding in their requirements. In a food supply chain of links and interdependencies that takes in primary producers, manufacturers, wholesalers, retailers, agents, logistics providers and shippers, and which runs from ‘farm to fork’, manufacturers occupy a central role as the processors of raw materials into the finished goods that will ultimately be consumed by the public. So as the multiple retailers react to market trends and consumer demands for the provenance of food and food constituents, food manufacturers are obliged to follow suit. In common with many developed economies, the UK market is one in which a virtual oligopoly of multiple retailers dominate decision-making in food chains, and are able to insist that their suppliers – the food and drink manufacturers – are flexible in terms of product delivered (e.g. new product introductions, recipes and pack sizes), timely in the way they respond to fluctuations in demand, and competitive in terms of price. Additionally, while providing traceability for all food materials, these firms are expected to overperform in terms of adherence to regulations demanding stringent levels of biological control. In this realm, traditional spot purchasing is less common, as retailer monopsonists look for longer-term relationships with fewer suppliers. Key to meeting such demands appears to be the exploitation of integrated intra-organisational and inter-organisational ICT and networked forms of business organisation. Thus, in cases of food contamination, for example, where there is the potential for great damage to be caused to corporate reputations, product recalls that exploit data from integrated supply-chain systems in combination with speedy and effective communications can see such damage minimised for food manaufacturers and their trading partners. Effective traceability therefore requires all in the supply chain to collaborate. However, even though the Curry Report (2002) campaigns for ‘full electronic traceability …’, especially of meat and poultry products, ‘… as soon as possible’ (p. 50), the heterogeneity of actors within the sector, the broad range of traceability methods extant by which data within a food supply chain are captured (i.e. including paper-based systems) and, perhaps most tellingly, the lack of trust felt by some manufacturers in regard to their trading partners, may act to impede universal progress and immediacy of response. The e-Business Watch (2006) survey provides a snapshot of ICT adoption data with regard to a number of technologies, and argues that overall the food and drink manufacturing sector has a relatively good level of internal process integration with supply-chain activities. However, even though there is evidence that ICT is becoming a more pervasive tool within the food supply chain, other researchers note problems with technology implementations that should underline the fact that innovation based on new ICT is not necessarily a straightforward process. Additionally, it is noticeable that there appears to be a divide in adoption behaviour between large firms and their smaller cousins. As a number of researchers have pointed out, large firms have the resources, for example, to bankroll any implementation mistakes they make, and to learn from them; smaller firms do not enjoy such luxury in the main so implementation mistakes can threaten their business viability. The establishment of short-lived institutions such as the Food Chain Centre and their efforts to provide case studies in ICT implementation for food manufacturers and others are to be applauded, as indeed is some of the ongoing work by trade associations and trade journals in their efforts to inform and educate. However, some of the case studies drawn up on occasion look somewhat anodyne and highlight where things went right at the expense of where things went wrong. Apart from cataclysmic events (including food scares), which draw media and then academic attention, there is little case-study material that catalogues the downs as well as the ups of ICT innovation in food manufacturing. If, indeed, there is a will

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to preserve some of the heterogeneity that food manufacturers enjoy as a class, and to provide timely and pertinent advice to preserve this, then arguably there is a case for academic work that extends the few warts-and-all studies in the area, even if it is necessary to anonymise it.

REFERENCES Atkins, P. and Bowler, I. (2001) Food in Society. Arnold, London. Boothby, D., Clark, S., Attwood, S. and Augustin, B. (2007) Research into UK Food & Drink Manufacturing – Final Report, ADAS UK Ltd, Wolverhampton. Available at: http://www.fdf.org.uk/speeches/ ADASreportDeskResearchFinal.pdf (accessed 17 September 2010). Bourlakis, M. (2001) Future issues in supply chain management. In: Eastham J.F., Ball S.D. and Sharples A.E. (eds) Food and Drink Supply Chain Management for the Hospitality and Retail Sectors, pp. 297– 303. Butterworth-Heinemann, Oxford. Cantillon, P., Collins, A. and O’Reilly, P. (2006) The small food manufacturing sector in the Irish grocery market ensuring survival by closing the supplier–customer requirements gap. Journal of Food Products Marketing, 11(4), 91–108. Caswell, J., Bredahl, M. and Hooker, N. (1998) How quality management metasystems are affecting the food industry. Review of Agricultural Economics, 20(2), 547–557. Clear, F. (2007) SMEs, electronically-mediated working and data security: cause for concern? International Journal of Business Science and Applied Management, 2(2), 1–20. Cotterill, R. (1997) The food distribution system of the future: convergence towards the US or UK model? Agribusiness, 13(2), 123–135. Cox, A. (1999) Power, value and supply chain management. Supply Chain Management: An International Journal, 4(4), 167–175. Cox, H., Mowatt, S. and Prevezer, M. (2002) The firm in the information age: organizational responses to technological change in the processed foods sector. Industrial and Corporate Change, 11(1), 135–158. Cox, H., Mowatt, S. and Prevezer, M. (2003) New product development and product supply within a network setting: the case of the chilled ready-meal industry in the UK. Industry and Innovation, 10(2), 197–217. Curry, D. (2002) Farming and Food. A sustainable future. Report of the Policy Commission on the Future of Farming and Food. HMSO, London Davenport, T. (2000) Mission Critical: Realizing the Promise of Enterprise Systems. Harvard Business School Press, Boston. Deasy, D. (2002) Food safety and assurance: the role of information technology. International Journal of Dairy Technology, 55(1), February, 1–4. DEFRA (2007) UK Food and Drink Manufacturing: An Economic Analysis. HMSO, London. Available at: https://statistics.defra.gov.uk/esg/reports/FDM%20paperFINAL%2007.pdf (accessed 3 December 2008). DEFRA (2008) Food Statistics Pocketbook 2008. HMSO, London. Available at: https: //statistics.defra.gov. uk/esg/publications/pocketstats/foodpocketstats/FoodPocketbook2008.pdf (accessed 12 December 2008). DEFRA/ONS (2008) Family Food 2006. HMSO, London. Available at: https: //statistics.defra.gov.uk/esg/ publications/efs/2006cal/complete.pdf (accessed 12 December 2008). Dixon, T., Thompson, B. and McAllister, P. (2002) The Value of ICT for SMEs in the UK: A Critical Review of Literature. Report for the Small Business Service Research Programme, The College of Estate Management, Reading. Duffy, R. and Fearne, A. (2004) Partnerships and alliances in UK supermarket supply networks. In: Bourlakis, M. and Weightman, P. (eds), Food Supply Chain Management. Blackwell Publishing Ltd., Oxford. e-Business Watch (2006) ICT and e-Business in the Food and Beverages Industry. European Commission/ Empirica, Bonn. Efstratiadis, M., Karirti, A. and Arvanitoyannis, I. (2000) Implementation of ISO 9000 to the food industry: an overview. International Journal of Food Sciences and Nutrition, 51(6), 459–473.

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FDF (2007) Working for the UK: our Contribution to the Economy. FDF, London. Available at: https://www. fdf.org.uk/resources/fdf_competitivereport_v32%20amended.pdf (accessed 17 September 2010). Fearne, A. and Hughes, D. (2000) Success factors in the fresh produce supply chain. British Food Journal, 102(10), 760–772. Fearne, A., Hughes, D. and Duffy, R. (2001) Concept of collaboration: supply chain management in a global food chain. In: Eastham, J., Sharples, L. and Ball, S. (eds), Food Supply Chain Management: Issues for the Hospitality and Retail Sector. Reed Educational and Professional, Oxford. Fillis, I., Johansson U. and Wagner, B. (2004) A qualitative investigation of smaller firm e-business development. Journal of Small Business and Enterprise Development, 11(3), 349–361. Folinas, D., Vlachopoulou, M., Manthou, V. and Manos, B. (2003) A web-based integration of data and processes in agribusiness supply chains. Proceedings of EFITA 2003 Conference, Hungary, pp. 143–50. Folinas, D., Manikas, I. and Manos, B. (2006) Traceability data management for food chains. British Food Journal, 108(8), 622. Food Chain Centre (2005) Prosper Through Partnership. Available at: http://www.foodchaincentre.com/ FoodChainFiles/NEW foodchainfiles/Prosper through Partnership/a) Complete Folder – Prosper Through Partnership.pdf (accessed 12 December 2008). Food from Britain (2006) The Healthy Food Market. FFB Research and Consultancy. HMSO, London. Food Standards Agency (2002) Traceability in the Food Chain: a Preliminary Study. Food Chain Strategy Division, Food Standards Agency, London. Fritz, M., Hausen, T. and Schiefer, G. (2004) Developments and development directions of electronic trade platforms in US and European agri-food markets: impact on sector organization. International Food and Agribusiness Management Review, 7(1), 1–20. Hill, C. and Scudder, G. (2002) The use of electronic data interchange for supply chain coordination in the food industry. Journal of Operations Management, 20(4), 375–387. Hingley, M. (2001) Relationship management in the supply chain. International Journal of Logistics Management, 12(2), 57–71. Hingley, M. (2005) Power imbalance in UK agri-food supply channels: learning to live with the supermarkets? Journal of Marketing Management, Special issue: The marketing imperative for the agri-food sector, 21(1/2), 63–68. HMSO (1990) Food Safety Act 1990. Available at: http://www.opsi.gov.uk/acts/acts1990/ukpga_19900016_ en_1.htm (accessed 17 September 2010). Hobbs, J., Fearne, A. and Spriggs, J. (2002) Incentive structures for food safety and quality assurance: an international comparison. Food Control, 13(2), 77–81. Hughes, D. (2004) Food manufacturing. In: Bourlakis, M. and Weightman, P. (eds). Food Supply Chain Management. Blackwell Publishing Ltd., Oxford. Hulme, G. (2005) Food chain’s fear factor. Software tools play a part in protecting the nation’s food supply from accidental or deliberate contamination. InformationWeek, May 23. Available at: http://www.informationweek.com/news/global-cio/showArticle.jhtml?articleID=163106029. Ilyukhin, S., Haley, T. and Singh, R. (2001) A survey of automation practices in the food industry. Food Control, 12(5), 285–296. Jessup, L. and Valarich, J. (2003) Information Systems Today. Prentice Hall, New Jersey. Keuning, R. (1990) Food ingredients for the ‘90s. In: Birch, G., Campbell-Platt, G. and Lindley, M. (eds), Foods for the ‘90s. Elsevier, Barking. Kinsey, J. (2003) Emerging trends in the new food economy: consumers, firms and science. Paper presented at OECD Conference on Changing Dimensions of the Food Economy, The Hague, 6–7 February. Lang, T. (2003) Food industrialisation and food power: implications for food governance. Development Policy Review, 21(5–6), 555–568. Levy, M. and Powell, P. (2003) Exploring SME internet adoption: towards a contingent model. Electronic Markets, 13(2), 173–181. McGuffog, T. (1999) Re-thinking manufacturing by applying value chain management and electronic commerce. In: Rethinking Manufacturing: Winning Strategies for the Next Century (Ref. No. 1999/113), IEE Colloquia, 7/1–7/18. Available at: http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=809406 (accessed 17 September 2010). Meulenberg, M.T.G. and Viaene, J. (1998) Changing food marketing systems in western countries. In: Jongen, W.M.F. and Meulenberg, M.T.G. (eds), Innovation of Food Production Systems: Product Quality and Consumer Acceptance. Wageningen Press, Wageningen.

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Millstone, E. and Lang, T. (2003) The Atlas of Food: Who Eats What, Where and Why. Earthscan Publications, London. Mintel Oxygen (2008) Chilled and Frozen Ready Meals – UK, May. Mintel, London. Nolan, R.L. (2000) Information technology and management since 1960. In: Chandler, A.D. and Cortada, J.W. (eds.), A Nation Transformed by Information: How Information has Shaped the United States from Colonial Times to the Present. Oxford University Press, New York. Otles, S. and Onal, A. (2004) Computer-aided engineering software in the food industry. Journal of Food Engineering, 65, 311–315. Pendrous, R. (2006) Keen to be lean…not a has been. Food Manufacture, October. Quayle, M. (2004) E-commerce the challenge for UK SMEs in the twenty-first century. Journal of Operations and Production Management, 22(10), 1148–1161. Ryder, R. and Fearne, A. (2003) Procurement best practice in the food industry: supplier clustering as a source of strategic competitive advantage. Supply Chain Management, 8(1), 12–16. Senker, J. (1986) Technological co-operation between manufacturers and retailers to meet market demand. Food Marketing 2(3), 88–100. Senker, J (1988) A Taste for Innovation: British Supermarkets’ Influence on Food Manufacturers. Horton Publishing, Bradford. Simpson, M. and Docherty, A. (2004) E-commerce adoption support and advice for UK SMEs. Journal of Small Business and Enterprise Development, 11(3), 315–328. Smith, D. (2006) Design and management concepts for high care food processing, British Food Journal, 108(1), 54–60. Stevens, G. (1989) Integrating the supply chain. International Journal of Physical Distribution & Logistics Management, 19(8), 3–8. Taylor, D. and Fearne, A. (2006) Towards a framework for improvement in the management of demand in agri-food supply chains. Supply Chain Management: An International Journal, 11(5), 379–384. Tsamantanis, V. and Kogetsidis, H. (2006) Implementation of enterprise resource planning systems in the Cypriot brewing industry. British Food Journal, 108(2/3), 118. Van der Vorst, J., Beulens, A. and Van Beek, P. (2005) Innovations in logistics and ICT in food supply chain networks. In: Jongen, W. and Meulenberg, M. (eds), Innovation in Agri-Food Systems. Wageningen Academic Publishers, Wageningen. Van Donk, D., Akkerman, R. and Van der Vaart, T. (2008) Opportunities and realities of supply chain integration: the case of food manufacturers. British Food Journal, 110(2), 218–235. Van Donk, P. (2000) Customer-driven manufacturing in the food processing industry. British Food Journal, 102(10), 739–747. Vlachos, I. (2004) Adoption of electronic data interchange by agribusiness organizations. Journal of International Food & Agribusiness Marketing, 16(1), 19–42. Welch, M. and Zolkiewski, J. (2004) Barriers to virtue: exploring the dark side of dyadic relationships. In: 38th Academy of Marketing Conference Proceedings. University of Gloucestershire, Cheltenham.

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3

Retail Technologies in the Agrifood Chain

Michael Bourlakis

3.1

INTRODUCTION

The rapid speed and wide extent of innovations in computers and information technology (IT) have had profound impact on the way that business is conducted. IT encompasses the gathering, processing, storage, retrieval, display and communication of information or data, normally by means of microprocessor equipment (Willcocks and Fitzgerald, 1993). Lockett and Holland (1991) apply this specifically to retailing. Linking IT to logistics, Fitzgerald and Willcocks (1994) noted that IT is the supply of information-based technologies, while logistics information systems are organisational applications that are more or less IT-based, and are designed to deliver the logistics information needs of an organisation and its stakeholders. This chapter aims to introduce the reader to the food retail logistics function and to discuss the key traditional technologies used in that function. We anticipate that most readers will not necessarily be familiar with both aspects. The analysis will also provide a solid platform for the chapters to follow, where other authors will make reference to the major intelligent technologies and their application and relevance to food retail operations. On that basis, the next section examines the food retail logistics function, after which there is a section on IT applications in that function, while the last section provides some concluding remarks.

3.2

FOOD RETAIL LOGISTICS

Logistics has been a major function for food retail operations (see, for example, Bourlakis and Weightman, 2004; Bourlakis and Bourlakis, 2005, 2006). For example, most British food retail multiples in the early stages of their development in the 1960s and 1970s implemented logistics practices and developed warehouses in order to centralise stockholding (Fernie, 1989). During the 1980s, logistics increased its importance in multiple retailing (both food and non-food) and several trends caused that increase according to McKinnon (1986, pp. 49–50): (i) Development and promotion of a new framework for the integrated management and costing of the main physical distribution functions of transport, storage, stockholding, handling and order processing. Intelligent Agrifood Chains and Networks, First Edition. Edited by Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis. © 2011 by Blackwell Publishing Ltd. Published 2011 by Blackwell Publishing Ltd.

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(ii) Expansion of multiple retailers’ operations in terms of the size and geographical spread of branch stores and the volume and range of goods handled. (iii) Increases in the real cost of physical distribution at a time when intense competition has reduced profit margins. (iv) Downward pressure on stock levels exerted by high interest rates and declining financial liquidity. (v) Deterioration in the trading relationships between manufacturers and multiples. (vi) Growth in the number and size of firms offering specialist distribution services to multiples. (vii) Advent of new materials handling and information processing technology. In a similar vein, Smith and Sparks (1993) noted that during the 1980s and 1990s, various consumer, societal and retail changes had an effect on retail distribution and logistics. Moreover, these authors argue below that retail responses to socio-economic trends require changes to the physical distribution strategy and operations of retailers (see Table 3.1). The same researchers have defined the elements, the management of which comprise the food retail logistics function (Smith and Sparks, 1993): ●

●

●

●

●

the number, type and location of the storage facilities (e.g. issues such as centralised control, specialised depots, composites, in-house or contractor management, site location and scale, picking methods, owned or leased premises); levels of stockholding/inventory management in terms of both quality and quantity (e.g. issues such as product range, bar coding, date coding, investment/promotional buys, quality control, stock turnover days, service levels, fresh foods); transport to be used in moving products (issues such as own fleet, bigger trailers/fewer deliveries, delivery window targets, backhauling, multi-temperature trailers); packaging and unit sizes and how they are handled (e.g. issues such as pallets, roll cages, plastic trays, potato cages, pack sizes for merchandising, pre-packs); communications about the distribution elements of a company (e.g. issues such as computerised systems, electronic mail, electronic data interchange, sales-based order, depot on-line real-time systems, forecasting, checkout plus, hand-held scanners and modems).

A key aspect of the food retail logistics function is warehousing or centralisation. Centralisation implies that the supplier is not delivering directly to the retail premises but to retailercontrolled regional distribution centres (RDC), and therefore the retailer is responsible for the distribution of goods to retail outlets. Centralisation has been developed to a high degree in the Western European retail environment. The introduction of centralisation (and other logistics trends) is depicted in Table 3.2, which describes the British food-multiple retail environment. Although these developments were the result of a 30-year process, until the early 1970s most retail stores received the bulk of their deliveries directly from the suppliers’ factories or warehouses. A similar process has taken place in the rest of Western Europe (Cooper et al., 1991) and is already taking place in other national environments (e.g. in Southern Europe and Asia). In addition, certain factors have encouraged the development of centralised distribution in food multiple retailing in recent decades: ●

The increase in the number, size and quality of contractors providing an integrated distribution service has made it easier for retailers to extend their control over intermediate

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Table 3.1 The distribution/logistics effects of consumer, societal and retail change in UK food retailing. Consumer and societal change

Retail change

Distribution effects

Consumption has increased towards more and better products and patterns have broadened, deepened and become more complex

Increase in average size of stores associated with the growth of the food superstore (hypermarkets and large supermarkets)

The previous increases (consumption, store size) led to increased vehicle requirements (scheduling) and the need to handle larger volumes of a wider range of products

Consumer behaviour has moved from price towards non-price dimensions such as quality or service

A move towards out-of-town locations, linked to the need for large sites

The movement away from high-street locations has improved and eased the distribution position in many cases

Shopping behaviour is influenced by increased consumer mobility and shopping associated with or as a leisure activity has increased

A steady increase in the percentage of own-brand food product consumption

Development of own brands that are in retailers’ control leads to closer control throughout the distribution channel

Individuals or households have seen income levels rising, have more leisure time and increased awareness of health and fitness

A product extension based on new consumer demands such as organic, fresh and non-food products

This product extension has increased the complexity of retail distribution and allowed the use of specialist distribution companies, especially for products that require special temperature environments

Group behavioural changes such as holidays abroad

There has been financial availability to enable food retailer expansion

Finance is a key part of retailing, and attention has turned to costs of distribution

More individualistic society, e.g. take-home alcohol replacing the public house

Food retailers have become increasingly reliant on service and value-added elements rather than pricing elements

The service and value-added elements applied into retail distribution must match the product retail offering and therefore there is a need for high-quality distribution

Food retailers have invested heavily in technology

Technology is applied into all distributional aspects and retailers control distribution by information rather than by doing

Source: Smith and Sparks (1993).

●

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storage and shop delivery without becoming directly involved in the development and/or management of physical distribution systems. Many contractors have acquired the necessary capital resources and managerial skill to handle large-scale distribution operations on the behalf of retailers and have vigorously marketed their services (Fernie, 1989). Major advances in IT have greatly enhanced the relative advantages of centralised distribution. Multiple retailers’ distribution operations generate exceptionally large quantities of information because of their extensive product range, high turnover, broad supply base and numerous outlets. Information handling is further complicated by the need to monitor

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Table 3.2 The introduction of centralisation and other major logistics trends in British food multiple retailing between the 1960s and the mid-1980s. Period

Problem

Innovation

Consequences

1960s and 1970s

Disorderly delivery by suppliers to supermarkets and queues of vehicles led to both inefficiency and disruption

Introduction of RDCs to channel goods from suppliers to supermarkets operated by retailer

(i) Strict timing of supplier deliveries to RDC imposed by retailer (ii) Retailer builds and operates RDC (iii) Retailer operates own delivery fleet between RDC and supermarkets within its catchment area

Early 1980s

Retailers becoming too committed to operating logistics services in support of retail activity

Operation of retailer-owned RDCs and vehicle fleets to specialist freight companies

(i) Retailer can concentrate on core business of retailing (ii) Retailer achieves better financial return from capital invested in supermarkets than in RDCs and vehicles

Mid-1980s

Available floorspace at retail outlets being underused and too much floorspace used for storage

Conversion of storage floorspace at supermarkets to sales floorspace

(i) Better sales revenue potential at retail outlets (ii) RDCs absorb products formerly kept in store at supermarkets (iii) Just-in-time delivery from RDC to replenish supermarket shelves

RDC, regional distribution centre. Source: Cooper et al. (1991).

●

●

and control stock at two levels in the distribution channel (warehouse and store levels) and regulate the flow of supplies between them (Bourlakis and Bourlakis, 2006). Certain improvements in the transport system have proved especially beneficial to the warehousing operations of multiple retailers, such as the construction of the motorway network, increases in the maximum weight and dimensions of lorries and the development of new multi-temperature, compartmentalised vehicles (Quarmby, 1990). Finally, retailers came under increasing pressure to use retail floorspace more intensively, partly as a result of rising site costs, but also to accommodate expanding sales volumes within existing outlets by converting storage space into sales display area (McKinnon, 1988).

Another innovation was the introduction of the concept of composite, multi-temperature storage and distribution centres (Smith and Sparks, 1993). These centres enable ambient, chilled, fresh and frozen products to be distributed through one system of multi-temperature warehouses and vehicles, leading to increased centralisation levels (Table 3.3). Whiteoak (1998) has also stressed the implementation of the ‘just in time’ principle where, at regional distribution centres, stock is reduced to the minimum to support pickby-line cross-docking, and composite networks are supported by accurately timed, daily

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Retail Technologies in the Agrifood Chain Table 3.3

31

The impact of composite distribution.

Distribution trends

Pre-composite distribution

Post-composite distribution

Regional depots Centralisation Stock holding Delivery frequency Identify costs Chill chain control Computerisation

Single and small About 70% High, in store Less than daily Some case rate Single temperature Half telesales

Large and complex Increased to 85% Low, in store and depot Daily All costs known Rigorous control for freshness Total integration

Source: Smith and Sparks (1993).

Table 3.4

The benefits of contract and own account distribution.

Contract distribution

Own-account distribution

Strategic reasons Flexibility Spread risks

Cost Cost-plus argument Monitoring costs

Financial reasons Off-balance sheet financing Opportunity cost of capital investment Better planned budgets

Control Total responsibility though the supply chain Better customer service Loyalty to one, not several companies Security for new-product development

Operational reasons Accommodate seasonal peaks Reduce backdoor congestion at warehouse/store Provision of specialist services Improve service levels Management expertise Minimise industrial relations problems

Economies of scale In-house technological innovation

Source: Fernie (1989).

deliveries on very short lead times. Another key element in food retail logistics is the use of third-party logistics companies/contract distributors. Lieb et al. (1993, p. 37) have given the following definition for contract distribution/third-party logistics: Third party logistics is the use of external companies to perform logistics functions which have traditionally been performed within an organisation. The functions performed by the third party firm can encompass the entire logistics process or selective activities within that process.

Third-party distributors were initially used by food retailers to meet seasonal demand (e.g. Christmas), certain product categories (e.g. frozen) and remote geographical areas (Fernie, 1989). Over the years, these firms were able to offer a range of ‘value-added’ logistics services to their clients, including strategic planning, site acquisition, warehouse design, stock control management and systems development, in addition to transport-related functions (Kearney, 1994). Fernie (1989) provides a complete list of the benefits of the use of contract/ third party distributors, classified into three categories: strategic, financial and operational. Fernie (1989) suggests the categories of cost, control and economies of scale as the benefits arising from own-account distribution (Table 3.4).

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Intelligent Agrifood Chains and Networks Table 3.5

Information technology in retail operations.

Strategy

Offering new products or services (e.g. internet shopping)

Planning

Modelling of store and consumer behaviour Making what-if decisions

Analysis

Processing of market research information forecasting Immediate feedback on sales through bar-coded information Supplier monitoring Direct product profitability

Service

Reducing checkout queues Reducing the incidence of out-of-stock

Operations

Faster checkout throughput Linking of sales, inventory and purchase orders Reduced stockholding

Source: Howe et al. (1992).

Like Fernie (1989), a critical reason cited by the larger retailing chains for contracting out logistical operations is the inherent flexibility that can be achieved through a mix of own-account and contract distribution. With the aid of sophisticated IT, the distribution network can be controlled from the company headquarters. The key factor, however, is the ability of the retailer to control and monitor costs by comparing performance levels between contractors and the own-account operation.

3.3

INFORMATION TECHNOLOGY IN FOOD RETAIL LOGISTICS

Earl (1990) has argued that IT has become central to the delivery of goods and services in the retail sector. IT in a retail (and a food retail) context provides the infrastructure for the management of information. Over the past 20 years, developments in IT have led to a dramatic increase in the availability of information on product movement in the distribution channel. Prior to the introduction of scanner systems, the only sources of information on product movement were manufacturers’ shipment notices or warehouse withdrawals (Clemons and Row, 1993). By the same rationale, Wilson (1998) argues that, without advances in IT, the evolution of modern retailing would have stalled in the 1970s. Running a chain of hundreds of stores, each carrying thousands of products, would be hopelessly inefficient in the absence of IT systems. The above findings were supported by Dolen (1986), who argued that retailers who identified opportunities to exploit IT would have much to gain. To be more specific, the IT function can be a productive factor for retail operations as it contributes to the creation of output (Reardon et al., 1996). IT can contribute to numerous areas of retail operations and some of these are listed in Table 3.5. Dawson (1994) describes two kind of technologies available to retail firms: core technologies and application technologies. Core technologies provide the necessary information infrastructure and result from widely agreed standards. Core technologies, in their own right, do not create added value from information, but they allow for the implementation of

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Benefits of EPoS systems.

Table 3.6

General benefit area

Type of benefit

Stock control

Fewer stock-outs Fewer over-stocks Less stock held in branches

Merchandising

Better range planning and better allocation to branches Better monitoring of sales patterns with suggested re-order requirements Better monitoring on new lines and promotions

Operational

Reduced paperwork as well as better labour scheduling Improved customer services/customer loyalty Accurate pricing and ease of price changes Improved cash management/banking Improved shrinkage control Faster throughput at checkouts Better information An improved bargaining tool with supplier

Credit

Improved authorisation systems reduce fraud Less paperwork Better deal on bank charges with electronic banking systems

Source: Hogarth-Scott and Parkinson (1994) and Ody (1990).

application technologies. There are three core technologies relevant to retailing (Burt and Dawson 1991): bar codes, electronic data interchange and data processing and information.

3.3.1

Bar codes

Items can be identified by bar codes (used on product cases and pallets to identify contents and, in more advanced instances, quantities) by optical-electronic methods. The most common use of this technology is the collection of sales data at the retailer’s point of sale (EPoS), which can be used to improve retail efficiency (Davis, 1995). By collecting information about consumers’ behaviour, retailers can also increase their power in the grocery distribution channel (Ogbonna and Wilkinson, 1996) by developing, for example, own brands that may meet better these customers’ needs. Some other benefits arising from EPoS technology are the better decisions that can be made from a broader informational base. Table 3.6 summarises the most important benefits arising from EPoS technology (Ody, 1990; HogarthScott and Parkinson, 1994). Such major benefits can be conventionally categorised as ‘hard’ (direct) and ‘soft’ (indirect) (Dawson et al., 1987). EPoS technology is used widely: to record product locations in warehouses and to record product movement onto and off vehicles. It has been argued (Lynch, 1990) that in conjunction with electronic data interchange (EDI) EPoS offers the potential for a fully automated sales and stock-handling system.

3.3.2

Electronic data interchange

The second core technology for retailing is the electronic transmission of information using standard protocols. An example of the application technology is the creation of EDI networks based on a specific standard that allows for the co-ordination of various parts of

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Table 3.7

Benefits from the implementation of EDI.

Direct benefits

Benefits from combining EDI with improved management

Reductions in the usage of telephone Less transcribing, data entry, document matching, etc. More efficient paper and paper-handling reduction systems Prompt receipt of trading transactions Reduction in the use of conventional mail

Reduced inventory management Better cash management

Reduction or elimination of data entry Lower postage costs, including stamps, stationery and clerical labour Reduction in administration costs Faster transfer of information Increased record accuracy Reduced clerical errors Reduced number of paper bottlenecks Elimination of manual re-keying of data into the recipient’s computer system Improved information about other members’ operations

Improved inventory management Improved customer service Development of closer relationships between trading partners Increased sale productivity More flexible buying strategies Improved manufacturing process (e.g. just in time) Streamlined operations Reduction in stockholding by all trading partners (supplier, distributor, retailer) Reduction in order-processing time Reduction in the payment cycle, cutting interest on outstanding payments Lower incidence of stock-outs and savings in the costs of correcting errors and reconciling disputed documents Reduced number of sales representatives’ calls

Sources: Benjamin et al. (1990); Takac (1993).

the supply chain (EDIFACT) (Fynes and Ennis, 1994). The Economist Intelligence Unit (1988) grouped the benefits accruing from EDI to business into three categories: strategic, operational and opportunity related. The strategic benefits include some which can be of crucial long-term significance to corporate activity, such as faster trading cycles, improved inventory management and gaining competitive advantage through ‘win–win’ partnerships between the supply chain members. Operational benefits are of major importance to the daily operation of the company but they usually have an impact only on individual departments within the organisation. These may include a reduction in working-capital requirements, improved cash flow, security and error reduction, and acknowledged receipt of order and delivery. EDI also shortens the order lead times between shop and distribution centre and between a retailer’s central buying point and the supplier of the product. For example, some of the large British grocery multiples supply their shops with fast-moving lines from a distribution centre within a few hours of the order being transmitted, allowing shops to cut stocks while maintaining, or even raising, the level of product availability (Patel et al., 2001). A more complete list of the benefits stemming from implementing EDI is given in Table 3.7. Many suppliers in the fast-moving goods sector (manufacturers, logistics firms) have implemented EDI in response to demands made by their customers (retailers). In an attempt to link the use of EDI to retail logistics outsourcing, McKinnon (1990, p. 39) stated that:

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EDI has promoted the use of logistics outsourcing, enabling retailers to exert almost as much control over contract distribution as over in-house operation. It has also created an opportunity for contractors to become much more heavily involved in the collection, transmission and processing of logistical information, thereby adding value to the basic physical functions of transport, storage and handling.

3.3.3

Data processing and information

The last core technology is the processing of data on microprocessors, allowing the reorganisation and representation of data in order to change it into information that is usable by management. In general, retailers adopt application technologies that use the data collected, transmitted and processed by the core technologies to create useful information. These application technologies are addressed through tools such as database-management systems, statistical-modelling systems and decision-support systems. Some applications include (Dawson 1994): ●

●

●

●

●

●

●

●

merchandising applications that are used to optimise the use of sales space, including store layouts and shelf space, such as Apollo, Spaceman, share allocation models and category and range selection tools (Mintel, 1996); stock models that are used to minimise stock holdings and to optimise replenishment processes, such as Safeway’s stock management III system (Davison and ScoulerDavison, 1997); labour scheduling models that are used to optimise job allocations and minimise labour costs, such as Staffplanner II used by Safeway (Mintel, 1996); accounting and control applications that are used not only to make the purchase ledger more accurate and minimise costs, but also to check supplier performance and creditworthiness of customers, such as ERP tools (Richmond et al., 1998); business planning applications, including budgeting and sales forecasting tools, such as the I3 software used by Asda (Fernie and Sparks, 1997); applications for the identification of optimum locations for stores and warehouses, such as the geographical information system, Smallworld, used by Tesco (Mintel, 1996); marketing applications, mainly buying-related, which are used to optimise purchasing conditions and to evaluate product performance, in order to support negotiations with suppliers and to manage customer evaluation through customer loyalty programmes (The Grocer, 1998); applications of network technologies that allow additional facilities to be carried at marginal cost alongside the main facility, such as electronic funds transfer at the point of sale (EFTPoS), which can provide a reduction of around 40% in the cost of processing transactions (Hogarth-Scott, 1989).

Apart from the technologies listed above, recent developments include radio frequency identification, using radio signals to communicate messages, in-cab communications and the satellite tracking of vehicles, which allows vehicles to be constantly monitored (Jones et al., 2004). Another development is warehouse control systems (e.g. Denver, DCAMS, DCOTA), which integrate the reception, storage, picking and shipping of goods into a single process. A further improvement in the performance of warehouse control systems can be secured by full automation (Bell and Davison, 1997). These systems are of rising importance, as the warehouse is becoming central to the logistics

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process for the whole supply chain; it is regarded as the main element in the efficient use of the firm’s stockholding. A more recent issue is the increased use of the internet in the grocery supply chain. The introduction of the internet improved the flow of information between channel members and its use is favoured by a number of food multiple retailers (Quarrie and Hobbs, 1997). For example, Sainsbury’s is already rolling out Xtra Trade, a system that allows suppliers to exchange supply-chain information over the internet, while Tesco is using a similar system called Tesco Information Exchange (Retail Solutions, 1999). The major benefit from the use of the internet is that both retailers and suppliers avoid extensive use of paperwork and moreover each stage of the entire system is far more transparent. All these applications have provided a good platform for the introduction and use of intelligent technologies. These are very popular nowadays (see for example, Prater et al., 2005) and will be discussed in detail later in this book: radio frequency identification in Chapter 7 and retail warehouse technologies, including, inter alia, voice picking and radio frequency picking, in Chapter 12.

3.4

CONCLUSIONS

This chapter discussed in detail the food retail logistics function and its major components. In order for this function to perform efficiently, the use of IT has become an absolute necessity. These technologies were also analysed in this chapter and this analysis has provided a solid grounding for the chapters to follow.

REFERENCES Bell, J. and Davison, J. (1997). Warehouse management systems at Tesco. In: Hart, C.A., Kirkup, M., Preston, D., Rafiq, M. and Walley, P. (eds), Cases in Retailing: Operational Perspectives. Blackwell Publishing Ltd., Oxford. Benjamin, R.I., Long, D.W. and Scott Morton, M.S. (1990) Electronic data interchange: how much competitive advantage? Long Range Planning, 23(1), 29–40. Bourlakis, C. and Bourlakis, M. (2005) Information technology safeguards, logistics asset specificity and 4th party logistics network creation in the food retail chain. Journal of Business and Industrial Marketing, 20(2/3), 88–98. Bourlakis, M. and Bourlakis, C. (2006) Integrating logistics and information technology strategies for sustainable competitive advantage. Journal of Enterprise Information Management, 19(2), 389–402. Bourlakis, M. and Weightman, P. (eds) (2004) Food Supply Chain Management. Blackwell Publishing Ltd., Oxford. Burt, S.L. and Dawson, J.A. (1991) The Impact of New Technology and New Payment Systems on Commercial Distribution in the European Community. Series Studies for Commerce and Distribution, No. 17. Commission of the European Communities, Directorate General, XXIII, Brussels. Clemons, E.K. and Row, M.C. (1993) Limits to interfirm coordination through information technology: results of a field study in consumer packaged goods distribution. Journal of Management Information Systems, 10(1), 86. Cooper, J., Browne, M. and Peters, M. (1991) European Logistics: Markets, Management and Strategy. Blackwell Publishing Ltd., Oxford. Davis, M. (1995) The Future of Distribution: Strategies for Success in a Changing Industry. Financial Times Management Reports. Davison, J. and Scouler-Davison, S. (1997) Managing stock management III in Safeway stores. In: Hart, C.A., Kirkup, M., Preston, D., Rafiq, M. and Walley, P. (eds), Cases in Retailing: Operational Perspectives. Blackwell Publishing Ltd., Oxford.

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Dawson, J.A. (1994) Applications of information management in European retailing. International Review of Retail, Distribution and Consumer Research, 4(2), 219–238. Dawson, J.A., Findlay, A.M. and Sparks, L. (1987) The impact of scanning on employment in UK food stores: a preliminary analysis. Journal of Marketing Management, 2(3), 285–300. Dolen, P.Z. (1986) How retailers can use information for competitive advantage. International Trends in Retailing, 3, 23–28. Earl, M. (1990) IT and strategic advantage: a framework of frameworks. In: Earl, M. (ed.), Information Management: the Strategic Dimension. Clarendon Press, Oxford. Economist Intelligence Unit (1988) EDI for Retailers. EIU Publications, London. Fernie, J. (1989) Contract distribution in multiple retailing. International Journal of Physical Distribution and Materials Management, 19(7), 1–35. Fernie, J. and Sparks, L. (1997) Retail logistics: the case of Tesco stores. In: Hart, C.A., Kirkup, M., Preston, D., Rafiq, M. and Walley, P. (eds), Cases in Retailing: Operational Perspectives. Blackwell Publishing Ltd., Oxford. Fitzgerald, G. and Willcocks, L. (1994) Outsourcing Information Technology: Contracts and the client/ vendor relationship. Research and Discussion Paper 94/10. Oxford Institute of Information Management, Templeton College, Oxford. Fynes, B. and Ennis, S. (1994) EDI in retailing: implementation and prospects in Ireland. International Review of Retail, Distribution and Consumer Research, 4(4), 411–426. Hogarth-Scott, S. (1989) The Strategic Implications of Information Technology for Retailing. Horton Publishing, Bradford. Hogarth-Scott, S. and Parkinson, S. (1994) Barriers and stimuli to the use of information technology in retailing. International Review of Retail, Distribution and Consumer Research, 4(3), 257–275. Jones, P., Clarke-Hill, C., Shears, P., Comfort, D. and Hillier, D. (2004) Radio frequency identification in the UK: opportunities and challenges. International Journal of Retail and Distribution Management, 32, 164–171. Kearney, A.K. (1994) Logistics Services in Europe. European Logistics Association, Brussels. Lieb, R.G., Millen, R.A. and Wasserhove, L.N.V. (1993) Third party logistics services. International Journal of Physical Distribution and Logistics Management, 6(23), 35–44. Lockett, A.G. and Holland, C.P. (1991) Competitive advantage using information technology on retailing: myth or reality? The International Review of Retail, Distribution and Consumer Research, 1(3), 261–283. Lynch, J.E. (1990) The impact of EPOS on marketing strategy and retailer-supplier relationships. Journal of Marketing Management, 6(2), 158–172. McKinnon, A.C. (1986) The physical distribution strategies of multiple retailers. International Journal of Retailing, 1(2), 49–63. McKinnon, A.C. (1988) Physical Distribution Systems. Routledge, London. McKinnon, A.C. (1990) Electronic data interchange in the retail supply chain. International Journal of Retail and Distribution Management, 18(2), 39–42. Mintel (1996) IT in UK Retailing. Mintel Intelligence, London. Ody, P. (1990) Information Technology for Retailers: A Review of Applications and Developments. Longman, Harlow. Ogbonna, E. and Wilkinson, B. (1996) Information technology and power in the UK grocery distribution chain. Journal of General Management, 22(2), 87–103. Patel, T., Sheldon, D., Woolven, J. and Davey, P. (2001) Supply Chain Management. Institute of Grocery Distribution, Watford. Prater, E., Frazier, G.V. and Reyes, P.M. (2005) Future impacts of RFID on e-supply chains in grocery retailing. Supply Chain Management: An International Journal, 10(2), 134–142. Quarmby, D. (1990) Changes in the physical distribution of food to retail outlets. In: Fernie, J. (ed.), Retail Distribution Management. Kogan Page, London. Quarrie, J. and Hobbs, S. (1997) Supply Chain Technology: Improving Retail Efficiency and Effectiveness. Financial Times Retail and Consumer Publishing, London. Reardon, J., Hasty, R. and Coe, B. (1996) The effect of information technology on productivity in retailing. Journal of Retailing, 72(4), 445–461. Retail Solutions (1999) Collaborating with Electronic Business. November, 20–21. Richmond, B., Burns, A., Mabe, J., Nuthall, L. and Toole, R. (1998) Supply chain management tools, minimising the risks: maximising the benefits. In: Gattorna J. (ed.), Strategic Supply Chain Alignment: Best Practice in Supply Chain Management. Gower, Aldershot.

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Smith, D.L.G. and Sparks, L. (1993) The transformation of physical distribution in retailing: the example of Tesco plc. The International Review of Retail, Distribution and Consumer Research, 3(1), 35–64. Takac, P.F. (1993) Electronic data interchange: an avenue to better performance and the improvement of trading relationships? International Journal of Computer Applications in Technology, 5(1), 22–36. The Grocer (1998) Invasion of the Cyberbrands. 29 August 1998. Whiteoak, P. (1998) Rethinking efficient replenishment in the grocery sector. In: Fernie, J. and Sparks, L. (eds), Logistics and Retail Management. Kogan Page, London. Willcocks, L and Fitzgerald, G. (1993) Market as opportunity? Case studies in outsourcing information technology and services. Journal of Strategic Information Systems, 2(3), 134–156. Wilson, N. (1998) Growing competition. Logistics Europe, April 1998.

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4

Basic Principles for Effective Warehousing and Distribution of Perishable Goods in the Urban Environment: Current Status, Advanced Technologies and Future Trends

Nikolaos Stragas and Vasileios Zeimpekis

4.1

INTRODUCTION

As the market for perishable foods is increasing (e.g. refrigerated products), regulation of the supply chain must be prescribed by public authorities to protect final customers from health hazards. The maintenance of temperature and other types of preservation control at each stage of the supply chain is essential to maintain the prescribed quality of the product until it reaches the final consumer. This quality is influenced by the time delays in actions and by temperature disturbances. The European Union (EU), along with other developed countries, has established a set of regulations for temperature control and equipment performance at different steps of the cold chain (Bogataj et al., 2005). These regulations include: ● ●

●

product temperature regulation along the supply chain; obligatory recording of air and product temperature in refrigerated vehicles and loadingreloading places; standardised equipment.

Much of food safety is about keeping food at the right temperature. When chilled meat, seafood or salad is stored above 5°C, the environment becomes suitable for bacteria to multiply. Depending on the degree of temperature variation, the food’s shelf life is shortened, food is spoilt or, in a worst-case scenario, food-borne illness occurs. Currently, operators that store and/or deliver perishable foods face various problems. Once goods are stored in remote warehouses operators have little control over the conditions affecting their quality. Problems that may arise include equipment failure, temperature variations within refrigerated trailers and mistakes during delivery. On top of that, logistics companies are faced with the added burdens of low margins, high capital costs, aging assets, shortage of good drivers and high fuel costs. In addition, they are under pressure to meet retailer and consumer demands for quality. Intelligent Agrifood Chains and Networks, First Edition. Edited by Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis. © 2011 by Blackwell Publishing Ltd. Published 2011 by Blackwell Publishing Ltd.

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New technologies and information systems allow for innovative approaches to realtime monitoring of important field data (such as temperature, track-and-trace services, proof-of-delivery, etc.) during the storage and delivery process. Indeed, technologies such as radio-frequency identification (RFID) tags, smart labels, electronic temperature loggers, fleet management systems and so on can be used effectively in order to minimise operational costs and quality and safety issues as well as to increase customer service. The main purpose of this chapter is to provide readers with some basic principles for the effective warehousing and distribution of perishable goods in urban environments. More specifically, it aims to describe the cold chain as it is now, a series of advanced technologies used in its operation, and to discuss some trends that will affect it in future. The structure of the chapter is as follows. Section 4.2 describes the nature of perishable foods and gives details about current legislation concerning cold-chain storage and delivery operations. Section 4.3 describes the main warehousing processes, the current situation in perishable food storage, and the quality and safety certifications that a warehouse must obtain. In Section 4.4 we describe the transportation process in urban environments and the dynamic events (such as adverse weather conditions, traffic congestion, vehicle breakdowns, etc.) that may affect the delivery schedule and accordingly the quality of products. Then, in Section 4.5 we look at a list of new technologies that can be used in order to deal with the current difficulties in warehousing and delivery operations. These technologies include RFID tags, temperature sensors, fleet management systems, smart trace labels and so on. The chapter concludes with a summary of the main issues discussed together with the outline of a future research agenda.

4.2 4.2.1

THE NATURE OF PERISHABLE FOODS Current needs and inefficiencies

One of the most critical factors affecting the quality of perishable foods is temperature. From the time of production until the moment the product reaches the end customer, the preservation of a precise temperature will impact on the freshness, desirability and marketability of perishable foods (Jedermann et al., 2009). Temperature is a factor that must be under control throughout the entire product lifecycle. Because of this, information systems have been developed and temperature control applications have been established by the firms that produce, transport or store perishable foods. Because of the nature of perishable food, temperature records must be available to all the involved parts of the perishable foods operation at any time, to decide whether products may be forwarded or discarded before reaching the end customer. The dispatching and transportation of perishable food also requires investment in specific infrastructure. Special vehicles with the necessary equipment on board, such as refrigerators, sensors or wireless networks for real-time data transfer, must be available for the carriage of perishable foods (Pannozzo and Cortella, 2008). Additionally, the workforce has to be qualified to use this equipment, to interpret the sensors’ measurements and to take further steps in order to deliver the products at the required quality. Perishable food must be loaded, shipped and unloaded while avoiding temperature variations and exposure to adverse conditions. Products should be transferred quickly and safely, following specific regulations that prevent perishable food being put at risk.

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4.2.2

Official authorities and legislation for perishable foods

4.2.2.1

Authorities

41

The principal food safety authorities describe themselves as follows: The European Food Safety Authority (EFSA) is the keystone of the EU’s risk assessment process regarding food and feed safety. In close collaboration with national authorities and in open consultation with its stakeholders, EFSA provides independent scientific advice and clear communication on existing and emerging risks. Since EFSA’s advice serves to inform the policies and decisions of risk managers, a large part of EFSA’s work is undertaken in response to specific requests for scientific advice. EFSA also undertakes scientific work on its own initiative, so-called self-tasking. Accordingly, EFSA’s advice frequently supports the risk-management and policy-making processes. These may involve the process of adopting or revising European legislation on food or feed safety, deciding whether to approve regulated substances, such as pesticides and food additives, or developing new regulatory frameworks and policies, for instance in the field of nutrition (see the EFSA website at http: //www.efsa.europa.eu). The US Food and Drug Administration (FDA) is responsible for protecting the public health by assuring the safety, efficacy, and security of human and veterinary drugs, biological products, medical devices, USA food supply, cosmetics, and products that emit radiation. The FDA is also responsible for advancing the public health by helping to speed innovations that make medicines and foods more effective, safer, and more affordable; and helping the public get the accurate, science-based information they need to use medicines and foods to improve their health (see the FDA website at http: //www.fda.gov).

4.2.2.2

Regulations

Regulation (EC) No 178/2002 formulates the principles that ensure the protection of human health and maintain consumers’ interests in relation to food, considering the diversity in the supply of food, including traditional products. Through the framework that is established, the regulation provides organisational arrangements, processes and a scientific basis to support effective decision-making concerning food and feed safety. Defining the principles that characterise food safety at both a general and an individual level, this regulation establishes the EFSA and is applied to all stages of the food lifecycle (production, processing and distribution). Regulation (EC) No 178/2002 of the European Parliament and of the Council of 28 January 2002 laying down the general principles and requirements of food law, establishing the European Food Safety Authority and laying down procedures in matters of food safety. (Source: Official Journal L 031, 01/02/2002 P. 0001–0024)

Regulation (EC) No 1642/20031 amends Regulation (EC) No 178/2002, laying down procedures in matters of food safety. Additionally, it determines the principles and prerequisites that characterise food law. Regulation (EC) No 852/20042 takes particular account of principles such as the responsibility for food safety that rests with the food business operator. The regulation also emphasises the fact that food safety should be ensured right back to production. Additionally, the 1 2

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regulation describes the importance of maintaining the cold chain for perishable food that cannot be stored safely at ambient temperatures. According to this regulation, the food business operator’s responsibility is reinforced by the implementation of procedures based on the hazard analysis critical control point (HACCP) principles and good hygiene practices. Finally, the regulation underlines the importance of microbiological criteria and temperature control requirements based on a scientific risk assessment, along with the necessity to ensure that imported foods are of a high hygiene standard.

4.3 4.3.1

WAREHOUSING OPERATIONS The role of warehousing

Traditionally, a warehouse represents the physical place where raw materials, final products or goods are stored, either in batches or in a stockpile, depending on the type of product. The role of warehousing inside the supply-chain framework is to accelerate and simplify the distribution of particular products between the producers and end customers. In the case of perishable foods, warehousing operations are crucial because of the nature of the products that are stored: there is a need to preserve the quality of the goods by continuously monitoring their storage conditions. In the last decade warehouse operations have been tackled with a more sophisticated approach than in previous years. It has been proved that factors such as the selection of the location, the type of warehouse, the operating procedures, as well as the warehouse space setup, play a pivotal role in efficient warehousing. In addition, the implementation of innovative warehouse management models (e.g. picking systems) coupled with procurement strategies like just-in-time require the development of advanced warehouse management systems that will also fulfill current needs, such as the reduction of operational costs and improvement in customer services. Particularly in the case of perishable foods, warehouse operations should aim to achieve the following: ● ● ● ● ● ● ● ●

preservation of high-quality standards; continuous storage conditions monitoring; reduction of response time between demand and delivery; seasonal demand coverage; storage of a variety of products instead of limited types; mixture of product for orders formation; reduction in operational costs; increase in customer service.

These factors play a pivotal role for companies in the food sector, as nowadays many buyers of perishable food demand availability in the right quantity and quality, and at the correct price (Bogataj et al., 2005). If these requirements cannot be met, customers will seek alternative suppliers. In order to fulfill these needs, several companies in the perishable food sector are orientated towards intelligent methods for storage, introducing advanced technologies and processes. Lately, special attention has also been given to quality monitoring and preservation. McMeekin et al. (2006) underlined the significance of information systems that are capable of the capture, storage, analysis and retrieval of data, and can therefore provide the opportunity

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Basic Principles for Effective Warehousing and Distribution of Perishable Goods Table 4.1

43

Warehouse types.

Cross-docking

3PL

Private or leased warehouses

No intermediate storage

Most commonly used warehouse type

Batches broken

Provision of warehouse services for a third party Low investment costs

Goods are mixed Order completion Goods loaded and shipped

Saving human resources Saving financial resources Includes indoor procedures

Usually established near the company’s property Serves specific needs Management conducted by the company Management know-how required

for the cumulative gathering of knowledge, leading to preservation of quality. In addition, food warehouses have moved one step further by requiring the adoption of certification, such as the HACCP, ISO 14001 or EMAS standards, in order to preserve the high standards of perishable stock.

4.3.2

Types of warehouse facility

There are several ways of classifying warehouses depending on the nature of the product, the level of safety stock or even the warehouse layout. The most commonly accepted classification of warehousing in terms of logistics is that of cross-docking, 3PL centres and private or leased warehouses. Table 4.1 presents the basic characteristics for each type of warehouse. 4.3.2.1

Cross-docking

The collection and distribution of goods usually takes place with a time-lag inside the warehouse. In some cases, however, these procedures occur at the same time and in these are referred to as ‘cross-docking’ warehouses. The goods are transferred from the receipt point to the delivery point without any intermediate storage, as the warehouse operates more like a distribution centre than a storage location. The orders are placed in quantities adequate to cover the next-day’s demand. Batches are broken into smaller ones and the goods are mixed in order to create the requested order. Afterwards, the orders are loaded into trucks and shipped to the customers. The shorter lead times, the less time-consuming goods management and the lower storage cost result in faster goods movement. In terms of perishable food, faster goods movement is considered to be a major factor in better freshness and reduced spoilage. 4.3.2.2

Third-party logistics

It is common for a company to decide not to focus on developing a system for storage and distribution of goods, either because the investment cost is very high, or because they do not have the necessary knowledge. Third-party logistics (3PL) companies are one of the most widely used storage options, as they allow firms to focus on other major lines of business, enabling savings in resources (human and financial). They also offer companies better product management due to the expertise they possess. 3PL warehouses are the link between the sender and the receiver, and include all indoor procedures, such as the transportation from the sender to warehouse, storage, order completion, distribution management and shipment.

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Warehouse operations Storage

Picking

Shipping

Analysis

Receiving/ Returns

- Physical receipt - Unloading - Verification of quantity - Quality check - System update

- Storage location selection - Physical goods movement - Mixing - Goods consolidation - Sorting - Cross-docking - WMS update - Quality control

- Picking organisation - Product location - Product collection - Order formation - Packaging - Palette formation

- Packing list - Quality control - Invoice and order control - WMS update - Loading

Figure 4.1 Warehouse operations.

4.3.2.3

Private or leased warehouses

Private or leased warehouses are probably the most common type of warehouse in the supply chain. Companies construct or lease storage locations according to their needs, their budgets and the know-how they have. Warehouse equipment is obtained either from the company or from a warehouse specialist firm, whereas the warehouse management, which includes the warehouse information system, the manpower and the central organisation, is usually provided by the company itself. Private or leased warehouses are generally established inside or nearby the company’s property, which is usually at the production location. Products are stored directly after production and this is the basic need that a private or leased warehouse serves. Private warehouses are owned and operated by the company itself, in order to serve their own business activities (e.g. food distribution, food production). On the other hand, leased warehouses may serve more than one company or only be in use for a specific time period.

4.3.3

Warehouse operations

To assess the functionality of a warehouse, it is a matter of describing the flow of goods from the moment they are received until the time that they are sent to the customer (Figure 4.1). Goods are initially unloaded on the receiving bay of the company before the receiving procedures take place. This includes verifying the proper quantity has been received per the invoice and a quality check of a sample of the goods. Afterwards, the goods will receive a code (usually a barcode label is attached to them) in accordance with the relevant system of identification used by the company. They are then moved into the storage space (storage procedures). When an order is placed, goods are recalled from storage (picking procedures) and prepared for dispatch. Goods are either packaged or mixed with other products or sent directly to the dispatch bay, from where they are delivered to the customer (shipping procedures).

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4.3.3.1

45

Receiving and returns

Receiving includes procedures such as the physical receipt of goods, unloading, quantity checks and so forth. It is followed by quality control, along with the update of the warehouse information management system (e.g. barcode readers), recording the receipt and storage of goods within the warehouse. This function may include unpacking or batch formation, but also the temporary storage of goods while quality inspection takes place. Additionally, there is the returns procedure, including steps such as the return of damaged and/or defective goods for replacement, return of packaging for recycling, disposal or reuse (e.g. pallets), and finally recall of products due to safety defects (Emmett, 2005). 4.3.3.2

Storage

Storage includes the predetermined movement of goods from the receiving point to the final point of storage, while the choice of the specific location inside the warehouse is performed using warehouse management systems (WMS) and can be long- or short-term. In long-term storage there is full coverage of demand because of the high stock kept, whereas in shortterm storage, goods are temporarily stored while further procedures, such as mixing, goods consolidation, shorting or cross-docking, take place. Short-term storage is used for perishable goods that will be directly dispatched to the customer. 4.3.3.3

Picking

In picking, goods are recalled from storage, in appropriate quantities and at a scheduled time, according to an order placed, so as to be transferred to the shipping bays and sent to the customer. Picking usually involves pallet fragmentation into smaller lots, packaging, final pallet formation and labelling of goods with details such as the sender, the recipient, the transport company, etc. Recalling goods from storage involves considerations such as warehouse optimal withdrawal routing, goods location, lead times reduction and minimisation of faulty orders. 4.3.3.4

Shipping

Shipping of goods is the last operation that takes place inside the warehouse and involves dispatching of products from the warehouse to the customers. The first step is the formation of the packing list. Then, the packed products are transported in containers or pallets in order to be loaded onto whatever transport is to be used. At the same time, invoices are checked and verified against the orders, while the whole process is accompanied by quality control of the cargo so as to minimise the possibility of damage during transfer.

4.3.4

Storage of perishable goods

4.3.4.1

Basic principles

Storage of perishable food is considered to be a function of vital importance in the cold chain. Products are usually stored more than once in their lifecycle, often by different intermediaries (producers, retailers etc.), until they finally reach the end customer. This is why special attention is required. As a result, in order to preserve quality and safety, the storage procedure is a first priority and a great challenge for the cold chain, which adopts certain

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characteristics such as visibility, maturation, durability, labelling and regulations. The characteristics of the storage procedure are analysed in the following sections. According to Arbib et al. (1999), visibility is crucial in a cold chain, where control of the temperature in storage by adding preservatives is needed to maintain the quality and quantity of product through to the end of the supply chain. Maturation is also considered to be an essential characteristic, as perishable food can be stored up to precise time limits, after which the maturation process must necessarily begin. By the time the maturation period ends, the product is packed and expiry dates are printed onto the package. Perishable food is also described using the characteristic of product durability. Perishable foods, and especially those with short durability, should always be labelled with the relevant piece of information that will tell the seller to replace the product at the appropriate time and protect the customer from expired products. Along with the date of durability comes the need for labelling. According to Likar and Jevsnik (2006), labelling should include all special storage conditions of the goods and additionally the instructions for use, where appropriate. As the market for refrigerated products and prepared meals is increasing, regulation of the supply chain must be prescribed by public authorities to protect final customers from health hazards. The temperature and other types of preservation control at each stage of the supply chain are essential to maintain the prescribed quality of the product until it reaches final consumer. This quality is influenced by time delays in actions and by temperature disturbances. Europe and other developed countries have established a set of regulations for temperature control and equipment performance at different stages (especially at the storage stage) of the cold chain. Risk assessment is necessary and requires permanent control of the products in the cold chain. Temperature variations may result in the growth of pathogens, such as microbacteria, or other deteriorations in quality. Temperature control is therefore essential to keep the final consumer safe. Many countries have established food safety regulations such as: ● ●

●

product temperature regulation along the supply chain; obligatory recording of air and product temperatures in refrigerated vehicles, production cells and loading–reloading places; standardised equipment.

Recently, the concept of ‘cold traceability’ was introduced, which requires the use of tools and equipment such as thermometers, temperature recorders, temperature indicators and time–temperature integrators, for quality control of perishable goods. This approach helps in tracing perishable goods, such as poultry and other meat, fish, fruit and vegetables, confectionery, ice cream and other dairy products, which are stored under different refrigeration conditions. 4.3.4.2

Warehouse certification

Qualitative features of goods storage that can determine the life cycle of the product, such as temperature, humidity or other preservation control characteristics, are specified in specific certification that a warehouse must obtain. This certification is critical for storage operations, in order to maintain the prescribed quality of the product until it reaches the final consumer (Bogataj et al., 2005). Among the certification legislated to assure the quality of goods during warehouse operations are:

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●

●

●

47

ISO 9001: 2000. ISO 9001: 2000 defines traceability as the ability to track history and place all the relevant information for the traced product through recorded data (Zeimpekis et al., 2007). This can be achieved with advanced traceability systems such as EAN 128 and EAN.UCC. The former is a barcode system that carries information regarding dates and lot numbers of the product and the latter provides information related to shipment movements. ISO 22000. ISO 22000 is about food management systems and is implemented by all participants of the food supply chain, from primary production to supermarket shelves. ISO 22000 sets requirements about hazard identification and acceptable levels of hazards, traceability systems, handling of low-quality products, and continuous improvement of food quality, records maintenance and evaluation. The system can be applied to businesses of all sizes and types of food. Hazard analysis and critical control point (HACCP) certification is a preventative approach to controlling food safety, as it focuses more on preventing potential hazards regarding food safety than providing the appropriate tools to test the condition of final products. The HACCP system provides the company with a specific hazard analysis on food safety and determines the critical control points and critical limits for particular quantitative aspects (e.g. temperature). Additionally, HACCP establishes corrective actions to be taken in order after extreme variation at control points or violation of limits. ISO 14001/EMAS. The ISO 14001 standard provides a series of requirements for top management, which companies should adopt in their environmental management systems (EMS), in order to establish a system that is focused on controlling and improving a company’s impacts on the environment. As guidance for the development of best practices of environmentally conscious policies and practices (Gavronski et al., 2008), ISO 14001 promises cost savings, reduced waste generation and disposal costs, reduced energy consumption, resource productivity, and improvements in public relations and liability.

4.3.5

Storage inefficiencies of perishable foods

Storage operations are confronted by several types of problem when handling with goods of high risk. Perishable food cannot therefore be handled like other materials. The information that accompanies the products cannot any longer be only the delivery and the dispatch date. Additional information such as expiry dates, temperature, incoming quantities, storage location and product tracking are all critical in order for the products to reach the end customer on time and with high quality (Figure 4.2). All this information, which is demanded by legislation and which is consolidated through warehouse certification (e.g. ISO 9001, HACCP), can have a positive impact on products only if it is centrally organised by an advanced information system. 4.3.5.1

Expiry date control

One of the most critical tasks that warehousing has to face is the expiry-date control of perishable foods. The first aspect of this issue concerns the tracking of the expiry dates of perishable foods at the time that they reach the warehouse. At that point, perishable food with a short expiry date should be handled with a higher priority than those products with longer expiry dates. The second aspect is related to the storage operation itself. Perishable food should be stored in a way that serves the acceleration of picking and dispatching operations. Warehousing operations should follow a specific inventory method (i.e. Last in, first

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Product tracking - Product labelling - Real-time verification

Temperature monitoring

Product’s storage location

- Temperature preservation inside ranges - Real-time monitoring - Product labelling

- Product labelling - Real-time verification Storage operations present status and needs

Expiry dates control - Real-time monitoring - Inventory strategies application - Product labelling

Incoming quantities forecasting - Product quantities received - Quantity verification

Figure 4.2 Warehouse inefficiencies.

out (LIFO), First in first out (FIFO) ) that will ensure that products reach the final customer sufficiently in advance of the expiry date. These kinds of inventory strategy can be more efficient when they are supported by advanced information systems that provide real-time monitoring and uninterrupted access to expiry-date master data. 4.3.5.2

Temperature monitoring

The food preservation temperature is another vital aspect of perishable food management that must be taken into account. There are certain temperature ranges that have been specified for particular types of foods, in order to avoid food contamination or quality deterioration. According to European regulations, the legal range for food preservation – below 5°C for the cold chain and over 63°C for the hot chain – should not be applied only in storage operations. The preservation of the right temperature during storage is one issue, but the monitoring of this temperature is another and perhaps more important one. Real-time temperature monitoring is required from the receiving point until the time that food is

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dispatched. Along with ensuring temperature monitoring, warehousing processes should also ensure that products are labelled with information about how goods should be stored. 4.3.5.3

Product’s storage location

The allocation of products to locations inside the warehouse is considered to be another aspect of warehousing. Products are labelled with their storage location when received, and afterwards are moved to this specific location. The exact location is selected based on factors such as expiry date, dispatch date, type of product (returns) or batch formation. There are still cases where products may not be allocated directly to their position or may be stored in an inappropriate location, and these may be caused by the lack of an information system that can provide real-time verification of the correct storage location. 4.3.5.4

Product tracking

Product movement inside the warehouse is a daily routine that makes it difficult to monitoring the product’s location. Real-time information is required at this point, in order for warehouse management to be aware of the product’s location and the available free space. Efficient product tracking is also important for the faster execution of picking operation and for reduction of the working hours required for order formation.

4.4 4.4.1

DISTRIBUTION PROCESS Goods distribution in urban environments

Distribution is a key logistics activity and contributes, on average, the highest proportion of the total logistics-related costs (Ballou, 1999). Distributors face various problems, such as determining the optimal number, capacity and location of facilities serving more than one customer, and finding the optimal set of vehicle schedules and routes (Min et al., 1998). These problems become more complex in urban areas due to the traffic issues that occur mainly in city centres. Urban freight transport and logistics operations are concerned with the activities of delivering and collecting goods in town and city centres. These activities are often referred to as ‘city logistics’, as they entail the processes of transportation, handling and storage of goods, the management of inventory, waste and returns as well as homedelivery services. City logistics is a relatively new field of research, brought about by the challenge of moving growing quantities of freight within metropolitan areas. While cities, particularly since the industrial revolution, have always been important producers and consumers of freight, many of these activities were taking place in proximity to major transport terminals, such as ports and rail yards, with limited quantities of freight entering the city itself (Figure 4.3). The functional specialisation of cities, the global division of production, as well as increasing standards of living, are all correlated with larger quantities of freight coming from, bound to or transiting through urban areas. According to the Institute of City Logistics, city logistics is ‘the process for totally optimising the logistics and transport activities by private companies in urban areas while considering the traffic environment, the traffic congestion and energy consumption within the framework of a market economy’. Simplistically, city logistics concerns improving the efficiency of urban freight transportation, reducing traffic congestion and mitigating environmental impacts.

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DC

Central city

n

a rb

te

al

in

rm

U

Figure 4.3 City logistics environment (Rodrigue et al., 2006).

The urban environment is characterised by high settlement and population densities and high consumption of goods and services. In such environments traffic infrastructure and the possibilities for its extension are both limited and unsustainable. This dichotomy between the demand and limitations of the urban environment has resulted in the significant problems that are associated with urban freight transport. The most commonly mentioned ones are congestion, pollution, safety risks, noise and carbon creation.

4.4.2

Types of urban freight distribution

One may distinguish at least two ways of distributing goods in an urban environment: standard deliveries and ex-van sales. While both cases use a typical delivery network with N warehouses that deliver to M customers through a fleet of K vehicles, they differ in the way they handle demand. Standard deliveries are based on a known demand (usually driven by pre-placed customer orders), while ex-van sales operate in an unknown demand environment, where orders are placed during the truck’s visit to the customer site. Table 4.2 summarises the main attributes of the two modes of urban delivery. The performance of either urban distribution model may deteriorate significantly due to a number of factors (Min et al., 1998). No matter how well the initial delivery plan has been designed, unforeseen events inevitably occur during the distribution execution stage, thereby resulting in a need to make real-time adjustments, such as truck re-routing and delivery rescheduling (Brown et al., 1987; Rego and Roucairol, 1995; Savelsbergh and Sol, 1998), in order to adapt to the new conditions and achieve the objectives of the initial plan as closely as possible. In the case of standard deliveries, such events may include traffic congestion, ramp overload at points of delivery, truck breakdowns, unforeseen reverse logistics requests (for example, goods returns) and others (Ghiani et al., 2003). This situation may become even more complex in the case of ex-van sales, where inefficiencies usually stem from the inherent demand/route uncertainty of the model, raising complex requirements for real-time

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Characteristics of standard delivery and ex-van sales in urban distribution.

Standard deliveries

Ex-van sales Fixed geographical layout Fixed distribution centre capacity Fixed truck capacity and fleet

Known demand per sales point Fleet delivers based on orders Fixed schedules and delivery time windows Truck routes determined a priori based on demand, network traffic and other parameters in a near-optimal way

Unknown demand per sales point Orders are not known in advance (only sales area is) More relaxed schedules and delivery time windows Distribution of work per truck is based on past area sales and business agreements with the drivers

Customers

Depot

Vehicle route

Figure 4.4 Schematic representation of the typical vehicle-routing problem.

decision-making. For instance, if a vehicle has disposed of its entire inventory in the first few points of sales due to unexpectedly high demand, it may be beneficial for another vehicle (carrying excess inventory) to be re-routed in order to accommodate the increased sales needs in the first vehicle’s area. Other issues in ex-van sales involve requirements that arise for real-time connectivity with back-end company systems, in order to support processes such customer credit control, invoicing and so on.

4.4.3

Routing factors that affect urban freight distributions

Many problems in the area of urban goods transportation by vehicle fleets can be modelled, to a certain extent, within the vehicle-routing problem (VRP) framework (Figure 4.4). The focus of the typical VRP is the design of routes for delivery vehicles that operate from a single depot, and which supply a set of customers at known locations, with known demand. Routes for the vehicles are usually designed to minimise the total distance travelled (or a related cost function). Bowers et al. (1996) present the formulation of the typical VRP.

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In an effort to model and address important practical issues, the fundamental VRP has been extended in a number of aspects. Indeed, one can distinguish no less than nine topics of critical practical importance that raise considerable challenges in VRP-related research and are all closely related to the real-time vehicle management problem. 4.4.3.1

Number of stages

While the single-stage VRP (delivery only) is primarily concerned with the establishment of outbound delivery routes, the double-stage VRP considers both delivery and pickup, i.e. outbound and inbound distribution. The latter is a salient feature of real-time distribution, since reverse logistics may necessitate adjustments to the original schedule depending on the truck load and its capacity. For a treatment of the two-stage VRP see Savelsbergh (1995) and Yang et al. (2000). 4.4.3.2

Deterministic versus stochastic supply/demand

The deterministic VRP assumes that demand and supply are known a priori, while the stochastic VRP encompasses uncertainty in demand and/or supply levels (Min et al., 1998). As discussed above, demand uncertainty is a key characteristic of ex-van sales. 4.4.3.3

Fleet size

We can differentiate between the cases of single vehicle and multiple vehicles. As the number of vehicles in the delivery fleet is increased, the problem size, as well as the computational complexity, increases accordingly. It is clear that the multiple vehicle case is appropriate in the real-time vehicle management problem, since many contingency measures involve the cooperation between vehicles through appropriate inter-vehicle communication infrastructure. 4.4.3.4

Vehicle capacity

There exist formulations for both the capacitated VRP and the uncapacitated VRP, depending on whether vehicle capacities are considered. The capacitated VRP (CVRP), as presented for example in Toth and Vigo (2002), is perhaps among the most widely researched variations of the problem. Capacity considerations are important in the case examined here, especially in view of reverse logistics, in which the capability of the vehicle to respond to the customer need depends on its available capacity. 4.4.3.5

Planning horizon

The static VRP takes into consideration a single planning period (for example, solving the distribution problem for next day’s deliveries), while the dynamic VRP considers optimal solutions in multiple periods. In this case the initial schedule can be adjusted according to the current needs for distribution (Laporte, 1988). 4.4.3.6

Time windows

A classical variation of the VRP refers to the consideration of time windows, outside which deliveries cannot be accepted. Time windows can either be ‘hard’, in which case they cannot be violated, or ‘soft’, in which case violations are accepted but penalised. A recent analysis of

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Dynamic incidents in urban freight distributions.

Cause of incidents

Incident

Effect on delivery

Road infrastructure and environment

Traffic congestion, adverse weather conditions, road constructions, flea markets, protests

Increased vehicle travel time

Clients

No available unloading area, problems with the delivered products (e.g. wrong order) New customer request (delivery or pickup), amount of request

Increased customer service time Vehicle re-routing/no service

Delivery vehicle

Car accident, mechanical failure

No service/delayed service

the VRP with soft time windows has been provided by Ioannou et al. (2003). Time windows present one of the most common causes for the need for real-time incident management. Further to the factors just listed, there are a series of dynamic incidents that may influence urban distribution, which are analysed in the following section.

4.4.4

Dynamic incidents in urban freight distributions

In general, an incident is any event that occurs during delivery execution and cannot be anticipated with certainty (Aronson and Van der Krogt, 2002). In case of urban freight deliveries, one can distinguish three sources of incidents: (i) Incidents originating from the clients served, for example cancellation, time window changes, new customer request, amount of request, no available unloading area and changes of source and/or destination. (ii) Incidents from the road infrastructure and environment, for example road blocks, traffic congestion, road constructions, flea markets, protests, rain. (iii) Incidents that arise from delivery vehicles, for example car accidents and/or mechanical failure. Table 4.3 shows the classification of dynamic incidents in urban freight distribution. Each category of dynamic incident has a direct effect on delivery execution. Incidents that arise from road infrastructure and environmental sources usually result in increased vehicle travel times, whereas client incidents result in increased service times, vehicle re-routing or no service at all. Finally, for the case where the source of the incident arises from the vehicle itself, the effect is usually felt in delayed service or in no service at all. The current methods used by freight carriers to tackle these incidents are presented in the following section.

4.4.5

Current status in urban distribution of perishable goods

By definition, perishable goods deteriorate over time or if exposed to extreme temperatures (heat or cold), humidity or other environmental conditions. Therefore, it is of great importance to handle, store and cool them properly along their entire journey through the logistics and value chain, from harvesting to the retailer’s shelf.

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Wholesaler

Transporter/Distributor

Receival point

- Unloading/Loading*

- Vehicle maintenance

- Unloading*

- Repackaging of products

- Unloading/Loading*

- Temporary storage

- Consolidating/Palletising

- Temporary storage

- Presented for sale

- Temporary storage

- Consolidating/Palletising#

- Consumers

Key Products transported to next point in the cold chain, susceptible to breaks in the cold chain

Text * #

Areas in the cold chain that are susceptible to breaks Minimise the time perishable products spend in this area May not be required

Figure 4.5 The cold chain for perishable foods (GSA, 2003).

To minimise spoilage and cost, perishable foods need to reach the consumer as quickly as possible and in the best possible condition. Today, up to 40% of perishable products are wasted or spoiled during their distribution from the wholesaler to the receiving point (Bogataj et al., 2005). As shown in Figure 4.5, there are various operations that must take place before the products arrive with consumers, such as unloading/loading of goods, in-vehicle temporary storage and so forth, which may affect their quality and freshness. Because of this, urban freight distribution of perishable goods is considerably more complex than typical freight movement in the city environment. Fruit and vegetables, in particular, are foodstuffs with a high value added, which are sensitive to a great extent to storage conditions, and for which the impact of poor transport conditions in terms of cost is not negligible. Furthermore, this kind of perishable foodstuff can suffer as much from low temperature (below its minimum recommended storage temperature) as from high temperature. A typical list of the maximum temperature that certain foodstuffs can reach during transport is shown in Table 4.4. The maintenance of temperature is a common practical problem for the transport of temperature-sensitive goods, especially in cases where mixed deliveries occur (Radulescu et al., 2005). Indeed, on nearly all occasions, mixed deliveries are required for each retail store and decisions must be usually made on how products will be separated into a single load or across multiple loads. Firstly, separation choices are made on the temperature requirement of the product, i.e. frozen, chilled, chilling sensitive, and secondly decisions are made on sensitivity to odour contamination and ethylene production. Table 4.5 provides recommendations on how products should be separated in relation to the volume of product to be moved in different load options. Finally, packaging of perishable goods during distribution is also an important issue. Packaging is used to protect products and allow them to be received by end users in good condition. For most operations involved in the supply of products to remote communities, packaging will not be an issue and packaging provided by packers and manufacturers will be accepted as adequate. However, because transport conditions are often harsh and because of the need to consolidate small quantities of a wide range of products (especially when local deliveries occur), some additional packaging is usually required to prevent damage and losses. Care needs to be exercised in any repackaging to ensure that product conditions are

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Basic Principles for Effective Warehousing and Distribution of Perishable Goods Table 4.4

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Maximum temperature during transport based on ATP agreement.

Foodstuff

Maximum temperature °C

Ice cream Frozen or quick (deep)-frozen fish, fish products, molluscs and crustaceans and all other quick (deep)-frozen foodstuffs All frozen foodstuffs (except butter) Butter Red offal Butter Game Milk (raw or pasteurised) in tanks, for immediate consumption Industrial milk Dairy products (yoghurt, kefir, cream, and fresh cheese) Fish, molluscs and crustaceans Meat products Meat (other than red offal) Poultry and rabbits

−20* −18*

−12* −10* +3 +6 +4 +4 +6 +4 Melting ice +6 +7 +4

(*) During certain operations, a brief rise of the temperature of the surface of the foodstuffs of not more than 3°C in a part of the load above the appropriate temperature may be permitted. Source: ATP, 1970.

Table 4.5

Truck selection based on required transport temperature of products and journey time.

Truck type

Maximum travel time for product at +10 to +12°C

0 to +2°C

<−18°C

Open tray top Double tarped load

1h

Not recommended

Not recommended

Curtainsider Unrefrigerated Refrigerated

3h 6h

Not recommended 3h

Not recommended Not recommended

Insulated van Unrefrigerated Refrigerated

3h Unlimited

1h Unlimited

Not recommended Unlimited

Reefer No power With generator

3h Unlimited

1h Unlimited

Not recommended Unlimited

Source: GSA, 2003.

maintained, e.g. ventilation is not restricted and sealed plastic bags or boxes are not used for respiring products. Packaging factors that are usually considered when transporting products include: ● ● ● ● ●

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ventilation; product protection (protection against contamination and physical damage); strength; insulation; labelling.

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4.4.6

Distribution inefficiencies of perishable foods

The main factors influencing quality behaviour during post-harvest transport are generally temperature and time. In general, a low temperature and a shorter transport time are generally advantageous in terms of maintaining quality. However, some products are very sensitive to low-temperature decay (also called chilling injury), which typically occurs in products that originate from the sub-tropics. Also, unripe products will not ripen when stored at low temperatures, but may ripen when stored at a reduced temperature due to the production of ethylene (Jedermann et al., 2006). The main inefficiencies during transport of perishable foods are analysed below. 4.4.6.1

Product temperature

Perishable food products are at risk of suffering damage along the cold chain. The parties involved should control and monitor the conditions of goods in order to ensure their quality for consumers and to comply with all legal requirements (Tanner and Amos, 2003). Among the environmental parameters during transport, temperature has the most significant influence on the quality of food products. Strong coordination and cooperation of all parties involved are necessary. It is fundamental to minimise cold-chain delays during transportation. In addition, it is essential to ensure that temperatures inside the transport units are correct; local temperature deviations can occur in almost any transport situation. Reports from the literature indicate that deviations of 5°C or more can occur. There is a variance in the degree of temperature changes, depending on the transport conditions (Moureh and Flick, 2004; Punt and Huysamer, 2005; Wild et al., 2005; Rodriguez-Bermejo et al., 2007). Nowadays, most companies perform only a minimum level of temperature control in order to comply with food regulations. These regulations mainly concern fixed temperature maxima and minima but do not give any information about the effects of temperature deviations that are below the threshold (Jedermann et al., 2009). Real-time monitoring of product temperature, especially during transportation, is crucial for achieving product safety and quality. Modern technology (e.g. sensors) can be used to collect and transmit data concerning truckload temperature in real time. In this way, freight operators can monitor the temperature of the goods and automatic alerts can be sent to them in the event that the temperature falls under or exceeds a predefined threshold. 4.4.6.2

Transportation time

Time is also an important factor when perishable goods are delivered. Especially in cases where freight movement is made in urban environments, there are a number of unforeseen events (e.g. traffic delays, road works, vehicle breakdown, weather conditions) that are likely to occur and may have a negative impact on delivery execution of perishable foods. The use of an initial distribution plan, although necessary, is by no means sufficient to address these events, which may have adverse effects on system performance. It is thus very important for the dispatcher to monitor the delivery process and intervene in cases where the execution deviates from the plan. Nowadays, most companies are unable to monitor the execution of the delivery plan. Indeed, the driver is the only one that knows exactly the way products will be delivered and

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is the one that will decide what to do if any unexpected event occurs. Even in cases where voice communication between the drivers and the dispatcher occurs, the resulting decisions usually have limited effectiveness. Real-time monitoring of delivery fleets through fleet management systems is a technology that can be used for efficient surveillance of the distribution process. Fleet management systems enable the real-time monitoring of various parameters such as vehicle location and speed, field data (e.g. load temperature) and so on in order to detect bottlenecks in delivery execution and minimise operational costs. These systems are specialised software packages that are aimed specifically at fleet operations (Laporte and Crainic, 2000; Larsen, 2001).

4.5

NEW TECHNOLOGIES IN WAREHOUSING AND DISTRIBUTION

New developments in logistics use two major technologies to improve the supervision of the cold chain: ● ●

mobile and satellite networks for real-time monitoring of the delivery process; sensor technology and information systems to monitor temperature levels and the location of moving products. The following sections provide details concerning the use of these technologies.

4.5.1

Technologies for perishable food storage

4.5.1.1

Warehouse management systems

The need for expiry-date monitoring inside the warehouse is efficiently covered by advanced information systems such as WMS. Such a system records the date of arrival of all perishable products, along with their expiry date. These recordings allow the WMS to supply the warehouse administration with the appropriate information (Figure 4.6) for the picking of the products in advance of the expiry date, using available system applications such as alerts or business reports. Providing real-time information regarding received and expiry dates, a WMS can contribute to the implementation of a more efficient FIFO or LIFO inventory method, reducing the waste of expired products. 4.5.1.2

Temperature monitoring – temperature sensors

Temperature sensors are widely used in warehouses storing perishable food, in order to ensure that goods are preserved in the appropriate storage conditions. They provide a remote, real-time and reliable system to monitor and alert for temperature changes at the time they take place and in advance of product deterioration. Sensors are placed where temperature should be monitored inside the warehouse and data are collected by the monitor. Data are finally transferred back to the terminals through a network (Figure 4.7). Specific software is available to set temperature parameters and ensure that the users are informed via email or SMS when these parameters are violated.

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Figure 4.6 Warehouse management system.

SNMP SNMP Client Probe SNMP

Network

SNMP Client HTTP / HTML

Monitor

Heavy duty probe

Web browser Figure 4.7 Temperature sensors network.

4.5.1.3

Product storage location – RFID tags

RFID systems are used to identify products. They exchange data between interrogators (readers) and tags through a wireless radio link. The signal broadcast from the tag is processed by the interrogator, which then decodes the transmission and transfers the data to a

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Figure 4.8 Barcode labels system.

computer. At this stage, the computer either records the reading or requires further action according to the data transmitted. In the warehouse, perishable food pallets or batches are read by a portal reading unit placed at the docking bay door as they are unloaded from the truck. The WMS receives the information and provides the users with instructions for the exact storage location. When products are stored on shelves, the readers automatically record the exact location of the items. 4.5.1.4

Product tracking – barcode labels

Barcode labelling is a reliable system that is widely used in warehouses to track the exact location of a batch or pallet of perishable food inside the warehouse. Barcodes are usually printed using thermal transfer printers, using an alphanumeric code in a certain order (Figure 4.8). The barcode reading and decoding process starts when the barcode label is scanned with a bright light. The reflection is transferred into the scanner and is converted to an electrical high/low signal. The signal is then sent to a decoder for conversion to the appropriate letters and numbers. Finally, a computer application receives the decoded data, usually wirelessly, and reports it to the user.

4.5.2

Technologies for distribution of perishable food

4.5.2.1

Temperature monitoring

There are three types of technology that can be used for real-time temperature monitoring: (i) smart labels; (ii) semi-passive RFID tags; (iii) temperature sensors. Smart labels Smart labels can be used as a real-time cold-chain monitoring and traceability tool, and can help suppliers, logistics companies and retailers to deliver fresher, safer food with less waste. This type of label monitors perishable food using a tag (Figure 4.9), which is easily attached to pallet loads as they are loaded into refrigerated trailers, rail cars or sea containers. The tag wirelessly transmits temperature readings back to the headquarters of a company for monitoring. More specifically, each tag repeatedly transmits temperature readings to a telematic unit installed on the refrigerated trailer, railcar or container. The telematic unit then forwards the data to the control centre of the company, along with GPS location data.

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Figure 4.9 Smart label.

Figure 4.10 Semi-passive RFID tag.

The end result is a near-real-time stream of data about the condition of goods during delivery (i.e. temperature, location, identity, etc.). These tags come with easy-to-use web applications, which provide users with configurable alerts and accurate time/temperature/location charts. To minimise information overload, data is distilled down to simple, meaningful graphics and metrics. This technology offers numerous benefits to suppliers, logistics providers and retailers. These include: ● ● ● ● ● ●

guaranteed quality of deliveries right up to the retailer’s premises; proactive management of temperature abuse situations; automation of quality assurance (HACCP) requirements and records; minimisation of costly product recalls and insurance premiums; continuous improvement of supply-chain efficiency; brand/reputation protection with retailers and consumers.

Semi-passive RFID tags RFID is an emergent technology that is being used increasingly in many applications. RFID has been successfully applied to logistics and supply-chain management processes because of its ability to identify, categorise and manage the flow of goods and information throughout the supply chain. RFID tags can be active, passive or semi-passive. Passive and semipassive RFID (Figure 4.10) send their data by reflection or modulation of the electromagnetic field that was emitted by the reader. The typical reading range is between 10 cm and 3 m.The battery of a semi-passive RFID is only used to power the sensor and recording logic.

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Figure 4.11 Temperature sensor/logger.

RFID semi-passive hardware outfitted with sensors can extend the range of logistics applications because such hardware provides new features such as temperature and shock measurement. This hardware represents a new type of wireless sensor that can be very useful for cold-chain monitoring. Indeed, RFID temperature loggers can be adapted to analyse local deviations, detect temperature gradients and estimate the minimum number of sensors that are necessary for reliable monitoring inside a truck or container. These devices are useful tools for improving control during the transport chain and detecting weaknesses by identifying specific problem areas (Jedermann et al., 2009). Temperature sensors/loggers This type of sensor has been designed to meet the growing demand for cost-effective electronic temperature and humidity recording solutions (Figure 4.11). As in smart labels, these sensors repeatedly transmit temperature readings to a telematic unit installed on the refrigerated trailer, railcar or container. The telematic unit then forwards the data to the control centre of the company, along with GPS location data. To minimise information overload, data are distilled down to simple, meaningful graphics and metrics. 4.5.2.2

Fleet management systems

A fleet management system allows a logistics manager to monitor the daily distribution process of goods to customers (e.g. retail outlets) and at the same time monitor important parameters (such as load temperature). More specifically, such a system records the position of the delivery fleet and the product temperature in real time (via temperature loggers), using a telematic unit that is fitted in each vehicle. The position (coordinates) of the vehicle is then relayed back to a central monitoring centre using GPRS technology. The data received are stored in a database and displayed on a digital (vector) map. The GPS/GPRS hardware is integrated with the refrigerated containers. These containers are monitored constantly for any changes, such as refrigeration status and human or system errors. Retail distribution vehicles are usually provided with predefined routes for delivery

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Figure 4.12 Proof of delivery application.

and any violation of these routes would generate an alert at the control centre. This would then prompt the dispatcher to take necessary action so as to avoid longer transportation times, which might affect the quality of the products. Retail outlet locations are mapped on the digital map of the city and stop periods at these locations are also predefined. Should a vehicle stop at locations other than those defined by the system, an alert would be generated to highlight the unauthorised stop. 4.5.2.3

Vehicle-routing systems

The main aim of a vehicle-routing software is to optimise vehicle usage (e.g. minimise transportation time, distance travelled, etc), whilst providing a given service level for a given level of work. This may be achieved in a variety of ways, such as maximising vehicle usage and capacity usage, etc. It is usually constrained by factors such as delivery-time windows, vehicle capacity and so forth. The principal advantage of using automated vehicle-routing systems is that they can take into consideration a larger number of constraints and calculate more alternative solutions than can ever be done manually. Vehicle-routing software incorporates advanced scheduling methods (routing algorithms) that can generally be relied upon to provide very efficient solutions. Indeed, a vehicle-routing system can enable the scheduler to make fundamental changes to existing routes to allow late or urgent orders to be planned into the schedule while the system checks for any implications (missed delivery windows, legal infringements, etc.) (Rushton et al., 2000). Typical vehicle-routing output includes extremely detailed vehicle routes, which indicate the precise order of delivery drops, the locations, the drop sizes, summary results, visual maps of the trips, bar charts to show route summaries, etc. The visual output makes it much easier to interpret and understand the results, and the detailed delivery schedules can be used by the drivers (Rushton et al., 2000). 4.5.2.4

Proof of delivery application

Proof of delivery (POD) is a method used to establish the fact that the recipient received the contents sent by the sender. Although these applications has been used extensively by courier operators (especially when a track-and-trace service is required by the customer), over the last decade logistics companies have also adopted the same method during product delivery. By using a ruggedised portable terminal (Figure 4.12) that runs a proof-of-delivery application, drivers are able to prove the day and time that they delivered the products to the end

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customer and in some cases record details concerning product state (e.g. the temperature of a perishable product at the delivery time). When GPRS technology is used, POD data are transmitted in real time to the company’s dispatcher. POD data coupled with information from a fleet-management system can provide full control of the delivery fleet and of the state of loaded products to the user. In this way, quality and safety of perishable products is guaranteed.

4.6

CONCLUSIONS AND FUTURE TRENDS

Perishable food products are at risk of suffering damage along the cold chain. The parties involved should control and monitor the conditions of goods in order to ensure their quality for consumers and to comply with all legal requirements. Among environmental parameters during storage and delivery, temperature and transportation time are the most important in prolonging the shelf life of the products. Currently, companies that store and/or deliver perishable foods face various problems concerning quality and safety. Once goods are stored in remote warehouses or leave the dock, carriers have little control over conditions affecting their product’s quality. Problems that may arise include equipment failures, temperature variations within refrigerated trailers and mistakes during delivery. On top of that, logistics companies also face the added burdens of low margins, high capital costs, aging assets, shortage of good drivers and high fuel costs. To ensure high-quality and safe products in every step of the chain a controlled coldchain management system is required. Food producers and retailers have therefore become more and more interested in innovative systems to control food safety and quality over the whole chain. There are several systems available to support cold-chain management (Kreyenschmidt, 2008): ● ● ● ●

temperature monitoring systems, e.g. time-temperature indicators; predictive models for shelf life and food safety, e.g. shelf-life models for meat; rapid methods for food freshness and safety analysis, e.g. biosensors; packaging and storage systems to prolong shelf life and increase food safety, e.g. oxygen scavengers and indicators.

The integration of innovative solutions in different supply chains is a challenge and several factors have to be considered. An important prerequisite for successful integration is an easy adaptability to the heterogeneous structures of international food chains. Cost-effective and user-friendly implementations as well as integration with pre-existing or new technologies, software and inspection schemes are also important prerequisites for successful market launches (Kreyenschmidt, 2008). Further value can be added to the production of high-quality and safe products by introducing innovative solutions to support cold-chain management, like chipless technology (e.g. chipless tags) and microbiological growth models. Usually, there are no guidelines available that explain how to integrate complex solutions in different supply chains and which specific parameters have to be considered. Instructions on the best solutions for specific supply chains are also missing. This leads to long implementations and the results are often not what was expected. Compared to a single solution, a practical implementation of combined innovative solutions should be even more flexible according to the structure of international food chains.

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REFERENCES Arbib, C., Pacciarelli, D. and Smriglio, S. (1999) A three-dimensional matching model for perishable production scheduling, Discrete Applied Mathematics, 92(1), 1–15. Aronson L.D. and Van der Krogt, R.P.J. (2002) Incident Management in Transport Planning, White paper, TRAIL Research School, Delft. ATP (1970) Agreement on the International Carriage of Perishable Foodstuffs and on the Special Equipment to be used for such Carriage. United Nations Economic Commission for Europe – Agreement Transport Perishables, Geneva. Available at: http: //www.unece.org/trans/main/wp11/atp.html. Ballou R.H. (1999) Business Logistics Management. 4th Int edn. Prentice-Hall, Upper Saddle River. Bogataj, M., Bogataj, L. and Vodopivec, R. (2005) Stability of perishable goods in cold logistic chains, International Journal of Production Economics, 93, 345–356. Bowers, M., Noon, C.E. and Thomas, B. (1996) A parallel implementation of the TSSP +1 decomposition for the capacity-constrained vehicle routing problem. Computers Operations Research, 23(7), 723–732. Brown, G.G., Ellis, C., Graves, G.W. and Ronen, D. (1987) Real-time wide area dispatching of Mobil tank trucks. Interfaces, 17(1), 107–120. Emmett S. (2005) Excellence in Warehouse Management: How to Minimise Costs and Maximise Value. John Wiley & Sons, New Jersey. Gavronski, I., Ferrer, G., Laureano Paiva, E. (2008) ISO 14001 certification in Brazil: motivations and benefits. Journal of Cleaner Production, 16, 87–94. Ghiani G., Guerriero, F., Laporte, G. and Musmanno, R. (2003) Real-time vehicle routing: solution concepts, algorithms and parallel computing strategies. European Journal of Operational Research, 151(1), 1–11. GSA (2003) Transport and Handling of Perishable Products in Remote Areas of South Australia. Government of South Australia. Melbourne. Ioannou, G., Kritikos, M. and Prastacos, G. (2003), A problem generator-solver heuristic for vehicle routing with soft time windows. Omega, 31, 41–53. Jedermann, R., Schouten, R., Sklorz, A., Lang, W. and Kooten, O. (2006) Linking keeping quality models and sensor systems to an autonomous transport supervision system. Proceedings of the 2nd Workshop of Cold-Chain Management, 8–9 May, Bonn, Germany. Jedermann, R., Garcia, L.R. and Lang, W. (2009) Spatial temperature profiling by semi-passive RFID loggers for perishable food transportation. Computer Electronics in Agriculture, 65(2), 145–154. Kreyenschmidt, J. (2008) Innovative tools for supporting cold chain management. In: the Proceedings of 3rd International Workshop on Cold-Chain Management, 2–3 June, Bonn, Germany. Laporte, G. (1988) Location-routing problems. In: Golden, B.L. and Assad A.A. (eds), Vehicle Routing: Methods & Studies. North-Holland Publishing, Amsterdam. Laporte, G. and Crainic, T.G. (eds) (2000) Fleet Management & Logistics. Kluwer, Boston. Larsen, J. (2001) The Dynamic Vehicle Routing Problem. PhD Thesis, Department of Mathematical Modelling, Technical University of Denmark, IMM-PHD-2000–73, ISSN 0909–3192, Lyngby, Denmark. Likar, K. and Jevsnik, M. (2006) Cold chain maintaining in food trade. Food Control, 17, 108–113. McMeekin, T.A., Baranyi, J., Bowman, J., et al. (2006). Information systems in food safety management. International Journal of Food Microbiology, 112(3), 181–194. Min, H., Jayaraman, V. and Srivastava, R. (1998) Combined location-routing problems: A synthesis and future research directions. European Journal of Operational Research, 108, 1–15. Moureh, J. and Flick, D. (2004) Airflow pattern and temperature distribution in a typical refrigerated truck configuration loaded with pallets. International Journal of Refrigeration, 27(5), 464–474. Panozzoa, G. and Cortella, G. (2008) Standards for transport of perishable goods are still adequate? Connections between standards and technologies in perishable foodstuffs transport. Trends in Food Science & Technology, 19, 432–440. Punt, H. and Huysamer, M. (2005) Supply chain technology and assessment–temperature variances in a 12 m integral reefer container carrying plums under a dual temperature shipping regime. Acta Horticulturae, 687, 289–296. Radulescu, C., Lohan, J. and Higgins, H. (2005) Impact of hot-gas injection on the heating capacity of a transport temperature control unit operating in low ambient temperatures. Proceedings of International Conference on Latest Developments in Refrigerated Storage, Transportation and Display of Food Product, Amman, Jordan, 28–30 March.

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Rego, C. and Roucairol, C. (1995) Using tabu search for solving a dynamic multi-terminal truck dispatching problem. European Journal of Operational Research, 83, 411–429. Rodrigue, J.P., Comtois, C. and Slack, B. (2006) The Geography of Transport Systems. Routledge, New York. Rodriguez-Bermejo, J., Barreiro, P., Robla, J.I., Ruiz-Garcia, L. and May, I. (2007) Thermal study of a transport container. Journal of Food Engineering, 80(2), 517–527. Rushton, A., Oxley, J. and Croucher, P. (2000) The Handbook of Logistics and Distribution Management. Kogan Page, London. Savelsbergh, M.W.P. (1995) The general pickup and delivery problem. Transportation Science, 29, 17–29. Savelsbergh, M.W.P. and Sol, M. (1998) Drive: dynamic routing of independent vehicles. Operations Research, 46, 474–490. Toth, P. and Vigo, D. (2002) Models, relaxations and exact approaches for the capacitated vehicle routing problem. Discrete Applied Mathematics, 123, 487–512. Wild, Y., Scharnow, R. and Róhmann, M. (2005) Container Handbook 3. Gesamtverband der Deutschen Versicherungswirtschaft e.V. (GDV), Berlin. Yang, J., Jaillet, P., Mahmassani, H.S. (2000) Real-time Multi-Vehicle Truckload Pick-up and Delivery Problems. Working paper, Department of Industrial and Manufacturing Engineering, New Jersey Institute of Technology, Newark, NJ. Zeimpekis, V., Psarrou, M. Vlachos, I. and Minis I. (2007) Towards an RFID based system for real-time fruit management. In: Blecker, T. and Huang, G. (eds). RFID in Operations and Supply Chain Management: Research and Application. Erich Schmidt, Berlin.

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Emerging Footprint Technologies in Agriculture, from Field to Farm Gate

Spyros Fountas, Thomas Bartzanas and Dionysis Bochtis

5.1

INTRODUCTION

During the last few years, the agricultural sector has been through a critical phase, having been seriously affected by several factors. At an international level the agreements of the International Trade Organization and at a European level the new Common Agricultural Policy have resulted in problems with the competitiveness of agricultural products and the necessity for improvements in production methods of safe, healthy, high-quality products that are also in accordance with the objective of environmental protection. The agricultural sector is currently benefiting from a wide range of new information and communication technology (ICT) tools that are helping improve the flow of information in the real-time management of agricultural crops. New technologies to enhance the precision and automation of crop management are continuously being developed, tested and evaluated. The tools of precision agriculture and other information technologies should move into mainstream agricultural management when they are sufficiently developed and incorporated into the production chain. These technologies are paving the way for the reversal of the current trend towards heavy-machinery systems, replacing them with teams of smaller field robots. In this view of the future, fleet management will maintain its key role in maximizing overall efficiency, which it will achieve by optimizing the selection, dispatching and in-field coordination of these teams. This chapter describes advanced technologies and methods that can provide an efficient integrated in-field production system that will meet the objectives of product quality, resource usage, economic feasibility and environmental impact. Chapter sections include precision agriculture, field robotics, radio frequency identification (RFID) technology, automated data recording and fleet management.

5.2

PRECISION AGRICULTURE

Precision agriculture (PA) can be defined as the management of spatial and temporal variability to improve economic returns and reduce environmental impact. This can be achieved through using appropriate technologies within a coherent management structure. The technology provides the tools and management decides how the tools should be used. PA uses these new technologies to reduce the unit area of treatment from, in some cases, the farm down to field or even sub-field level. Intelligent Agrifood Chains and Networks, First Edition. Edited by Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis. © 2011 by Blackwell Publishing Ltd. Published 2011 by Blackwell Publishing Ltd.

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Yield layer

Drainage tile layer 6.0

5.8

7.2

Soil pH layer

7.0

Boundary layer FIELD 2.0

Figure 5.1 A GIS system that can combine different levels of sub-field data to generate management zones within the field (Morgan and Ess, 1997).

At the farm level, management is relatively easy, as it is a process of managing by averages. Inputs are calculated at a level that can be applied across the whole farm. At the field level, local conditions can be taken into account, for example soil type and the previous crop. These added data sources increase decision-making complexity but when used correctly they also improve the efficiency. At the sub-field level the level of complexity rises further, since changes in soil type, shading from trees, areas of compaction and so on must also be taken into account. At this level, the complexity can become so great that there is data overload and the manager cannot use all of the available data. PA technology now has the ability to produce data about soils and crops at sub-meter level, across a whole field, but the possibility of using this data is very limited until suitable information systems have been developed. The first applications of PA around the world became available in the early 1990s but the first major adoptions only took place at the end of that decade. Yield monitors connected to a GPS receiver represented farmers’ first real attempts to conduct site-specific management of their fields. The next attempts involved variable-rate application of lime, fertilizer and, more recently, chemicals. Soil sampling has also been a very important PA application, but the sample sizes vary between farmers, depending mainly on the soil-analysis cost. On-the-go sensing devices, such as electromagnetic induction equipment for the measurement of soil structure and water content and the hydro-nitrogen sensor, which tests chlorophyll content and automatically adjusts fertilizer doses, have been very promising, but farmers are still skeptical of their reliability and effectiveness. Finally, remote sensing has recently been the focus of many research projects, with commercial companies and their advisors using aerial photographs or satellite pictures to estimate yield potential, nutrient deficiencies and stresses. All these data can be combined and, with the use of geostatistics and fuzzy clustering algorithms, could delineate management zones within the field (Figure 5.1).

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PA can play a significant role in producing application maps for farm inputs, such as chemicals, fertilizers, seeds and water. These application maps can help farmers to apply the right amount of input at the right place at the right time. Therefore, they should prove to be part of an environmentally friendly management system.

5.3

ROBOTICS IN AGRICULTURE

Automation and ICT have developed to the point where autonomous vehicles that can intelligently nurture growing plants throughout the cropping cycle are being demonstrated. These vehicles are currently being developed around the world, which indicates that commercial robotic crop-production machines are now likely to be a reality within the foreseeable future. Robotics in agriculture could play an essential role, as this kind of technology could automate routine agricultural operations, utilizing the technologies and methods that have already been applied in PA in a holistic system. Robotic systems may have a significant role to play, particularly in organic agriculture, which is very labor-intensive, and where the prices of the end products are also high. Robotic concepts have been developed in a number of field operations, such as crop care, crop establishment and robotic harvesting (Blackmore et al., 2006). In agriculture and, more specifically, in crop production and harvesting, research and development of mobile robots was initiated in the early 1960s. The first developments in mobile vehicles mainly dealt with automatic steering for tractors (Wilson, 2000). Moreover, Hollingum (1999) has reviewed developments in agricultural robotics around the world, while Kondo and Ting (1998) have elaborated on robotics in bioproduction systems, including open fields. Fully mobile robots first appeared at the beginning of the 2000s, for example the Demeter system for automated harvesting, which is equipped with a video camera and GPS for navigation (Pilarski et al., 2002), and also semiautonomous agricultural vehicles (Billingsley, 2000; Freyberger and Jahns, 2000). Nevertheless, in recent years the development of a number of mobile robotic platforms has taken place around the world, led mainly by research institutes and tractor manufacturers. One of the most important aspects of good management is the ability to collect timely and accurate information about the growing crop. Quantified data has tended to be expensive and sampling costs can quickly outweigh the benefits of spatially variable management (Godwin et al., 2001). Data collection would be less expensive and timelier if an automated system could remain in the crop for continual monitoring, assessing crop health and status. This could be achieved by either embedding cheap wireless sensors at strategic positions within the crop or placing more expensive sensors onto a roving platform. Crop characteristics would include leaf area index, crop height (giving growth rates), growth stage, biomass, senescence, etc. For crop establishment a seed map is available, which uses RTK GPS and infrared sensor technology. As the seed drops, it cuts the infrared beam and triggers a data logger that records the indicated position and orientation of the seeder. A simple kinematic model can then calculate the actual seed position (Griepentrog et al., 2005). Another interesting application is microspraying, in which a spray boom is applied at the centimeter level. The system is used for the highly targeted application of chemicals and can treat very small areas by selectively switching the jets on and off. It is part of a larger system that can recognize the position of individual weed plants, locate their leaves and apply herbicides via a

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Figure 5.2 The small plant-nursing robot, Hortibot, with two different weeding tools: a herbicide cell sprayer and a tine weeder (Sorensen et al., 2008).

micro-sprayer according to a spray map, all coordinated by an RTK-GPS guided vehicle (Søgaard and Lund, 2005). A prototype of a plant-nursing robot, Hortibot (Figure 5.2) has been developed to carry light weeding tools for parcels of five to six rows of a crop (Sorensen et al., 2008). For harvesting, many robotic pickers have been developed for high-value row crops, notably in Japan (Kondo et al., 2006). These usually use machine vision to sense the color, shape and location of the product before directing a robotic arm with a specialized endeffector to pick the product. Some examples of robotic harvesters are those for cucumbers (Van Henten et al., 2003), cherries (Tanigaki et al., 2008) and orange citrus (Hannan and Burks, 2004). These robotic harvesters have not been commercially viable due to their low operation speeds and high cost. An example of one machine that is close to commercial viability is a strawberry-harvesting robot that harvests fruit hung from the sides of a tabletop culture in approximately 20 s, yielding a harvest capacity of 0.3 ha greenhouse per night (Kondo et al., 2005).

5.4

FLEET MANAGEMENT

A number of agricultural field operations involve multi-machine systems that might include one or more self-propelled or tractor-implement units and one or more transport units. The biomass supply chain, for example, typically involves a number of highly interconnected operations, e.g. harvesting, material handling, out-of-field removal of biomass, rural road transportation and public road transportation. Between successive stages there are a number of homogenous and heterogeneous machines, e.g. harvesters, transport units, medium- and high-capacity transport trucks, and unloading and pre-processing equipment (Figure 5.3). Large-scale operations of similar planning complexity to harvesting – “material output operations” – are the “material input operations” such as spraying and fertilizing.

5.4.1

Framework

A hierarchical modeling framework for multiple-machine field operations was outlined by Bochtis (2007a,b). According to this framework the overall planning problem of field operations is decomposed into a hierarchy of simpler problems that can be solved independently and efficiently. Each lower-level problem is modeled in a way that enables optimization algorithms from robotics and operations research to be adopted for their solution.

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Figure 5.3 Large-scale harvesting system.

The highest-level problem is the computation of an optimal machine assignment. This can be solved using factory scheduling algorithms, such as the solutions to the job-shop scheduling problem (JSSP), or the open-shop scheduling problem (OSSP) (Sadeh and Fox, 1996). The second problem that must be solved is area coverage path planning. This plan determines a path that will ensure that a machine will pass over every point in a given field and includes the following three procedures: (i) decomposition of the coverage region into sub-regions; (ii) selection of a sequence of those sub-regions; (iii) generation of a path that covers each sub-region (Huang, 2001). The third sub-problem is the generation of a path that covers each sub-region, given the type of fieldwork pattern that will be followed and its main direction. The last problem consists of the secondary-work-vehicle routing and can be addressed by the implementation of algorithms for the solution of the vehicle routing with time windows problem (Solomon and Desrosiers, 1986) or of dynamic routing strategies (Bertsimas and Van Ryzin, 1993).

5.4.2

Algorithmic approaches

In multiple-machine systems, two different management types should be considered: offline management and online fleet management. 5.4.2.1

Offline management

Offline management determines the appropriate fleet size and composition, and machine allocation and scheduling for a given operation. It has to determine the field (or field part) allocation to the available machines of the fleet, the assignment of the machines to the

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available supporting vehicles, the number of deposit or refilling units (facility units) that will be used and their type (e.g. mobile, non-mobile), location, capacity, cycle time, etc. Although this is an offline planning system, it is a very complex process and involves interactions between the farm machinery system and biological and meteorological subsystems, such as crop, soil and weather conditions. A traditional method of evaluating systems with interacting machines or components is cycle analysis (Buckmaster, 2006). This method accounts for all time spent by each machine in the system and, in field operations, can be useful for identifying suitable transport systems. The cycle diagram is a static instrument that does not take into account variability in speed, yield, transport distance and time evolution. Recently, however, powerful optimization methods have also been adopted in order to deal with the inherently large number of decision and state variables involved. Søgaard and Sørensen (2004) have presented an approach involving the development of a nonlinear-programming optimization model, which uses a level of aggregation consistent with accessible, existing data on machinery sets, crops, weather and timeliness of operations. Busato et al. (2007), meanwhile, developed a dynamic discrete event simulation model in order to optimize wheat harvesting and transport operations while accounting for field size and shape, field distance to silo, yield and resources available. A further approach using this system was presented in Busato and Berruto (2008), where an event-oriented simulation was combined with linear programming for the evaluation of the biomass supply chain. The model developed considers the interaction between resources and the effect of a number of limiting factors on the performance of the whole chain. The tool is suitable for detailed evaluation of system efficiency under changes in many variables (field yield, shape, size, transport distance and working chain composition). 5.4.2.2

Online fleet management

Online fleet management, on the other hand, has to determine, in (almost) real time, the updated sequence of tasks that each participant mobile unit has to execute in order to achieve an optimal (in some terms) performance of the whole system. This dynamic planning should give answers to questions such as: ● ● ●

Which facility or machine does each support vehicle have to travel to from its current position? What is the best route to reach this next destination? Where and when will the service take place?

There are two general approaches to dealing with stochastic optimization problems such as the one in question; a priori optimization-based methods (Bertsimas et al., 1990) and realtime optimization methods (Papastavrou, 1996). In the first type, the solution is based on a priori probabilistic information on future events. For harvesting, this translates into knowledge of the statistics of the spatial distribution of yield in the field. Such statistics are almost impossible to obtain. Furthermore, the uncertainty related to the time and location of a “full-grain-tank” event increases the uncertainty of the next similar event, and so on. Because of this dependence between events, an a priori scheduling method is of limited use. Bochtis et al. (2007a,b) presented an algorithmic procedure based on dynamic programming for planning harvesting operations, for a fleet of harvesters supported by a fleet of transport carts. The optimization criterion for planning is minimization of the total distance traveled by the carts. The optimization also includes penalty factors for those cases where a harvester

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stops operation while waiting for the transport cart. Another implementation of a wellknown method from other scientific areas is Petri nets. Guana et al. (2008) introduced hybrid Petri nets into their modeling of farm workflow. This was because agricultural operations involve both continuous and discrete events, and hybrid Petri nets conventionally comprise a continuous part and a discrete part. In Guan’s method, the continuous part mainly models the practical work in the field, and the discrete part represents status changes in resources such as machinery and labor, as well as handling machine status or undesirable breaks during the farming process. The simulation suggests that the hybrid Petri net model is promising for exactly describing the farming process and reallocating resources in the presence of uncertainties. 5.4.2.3

Geographic information systems

Recently, technologies based on the geographic information system (GIS) have been developed in order to support agricultural fleet-management decisions, with the main applications being in harvesting operations. In these systems, data are collected in real time and transferred via telematic technologies (Figure 5.4) to a central server (farm manager or contractor), which provides a data base to the decision maker (human or automatic systems). The whole system follows a closed-loop control architecture, which results in a sequence of planning, execution and re-planning. In current GIS-based fleet-management systems the following information is monitored and transferred to the decision maker: ●

●

●

●

information regarding specific on-board mechanisms – reel speed, chaff speed, threshing drum speed, concave position, cutting height, etc. – which is used for the detection of blockages and the evaluation of the performance and healthiness of the mechanisms; yield-specific information, such as grain moisture and yield measurements for the documentation and traceability of the product uses; geo-referenced information, which makes available the performance of each individual unit – area coverage/time unit, harvested biomass/time unit, idle times, travel times between fields etc. – and consequently of the whole system; unit remote diagnostic check, which makes available information regarding engine hours, engine load, diesel tank level, engine speed, hydraulic oil temperature, engine coolant temperature etc.

5.4.2.4

The multiple-robots perspective

Besides the fact that optimal fleet management is expected to solve current problems in conventional agricultural multi-machine systems, it also has to deal with the prospect of autonomous agricultural machines. According to the current take on this technology, large teams of smaller and simpler autonomous machines are to replace smaller groups of heavier and complex machines in the future, in order to build collective behavioral systems. (Blackmore et al., 2002). These systems are expected to have a number of advantages: ●

● ●

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The design, production and use of many simple units can be more economic than a larger and complex robot. A team of simple units is more scalable than a complex unit. Many problems, by their nature, are better suited to team-execution.

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On-board computer

On-board computer Digital maps

Digital maps

Area coverage algorithms

Routing algorithms

Operator interface

Operator interface Decision making GIS

Planning algorithms Farm manager interface Figure 5.4 GIS-based decision-making system.

●

●

●

●

●

A task that consists of sequential subtasks can be accomplished more quickly with team execution that by a single unit. The orientation to team-executed tasks provides means that specialized robots can be designed for specific subtasks rather than having to design a single robot capable of performing a number of heterogeneous tasks. More efficient positioning is possible because of the information exchanged about the relative position of each unit in the team. A team of units is less susceptible to overall failure as long as there is overlap between the units’ capabilities. A team can respond more efficiently to dynamic environments due to there being statistically more potential solutions to planning problems.

In multiple agricultural robot systems, online planning is necessary so that the robots can react to obstacles or unsafe conditions and handle unexpected situations, which are caused mainly by the presence of other robots, humans or animals. Real-time generation of paths requires the implementation of fast algorithms. An existing heuristic algorithm with low

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computational requirements (of the order of a few seconds) was used by Bochtis et al. (2007a,b) for the generation of optimal paths for multiple-harvesting operations. In this method, the problem of motion sequence generation for a fleet of m harvesters is formulated as a discrete optimization, multi-traveling salesman problem (m-TSP). Given a weighted graph with vertices and edges, the m-TSP searches for m optimal paths (sequences of edges), which – combined – contain all graph vertices. In Bochtis’s model, the vertices of the m-TSP correspond to the operating rows of the field. The cost is the nonproductive time, which is spent during the turning of the harvester at the ends of the rows. This cost is computed from the kinematic constraints of the vehicles and the geometrical space constraints of the field. The existing heuristic algorithm that was adopted for the solution of the m-TSP has the advantage of low computational time, making it feasible to re-plan an optimal pattern for the remaining nonharvested field, while the harvesting procedure is being executed. Ryerson and Zhang (2007) used genetic algorithms for the dynamic path planning of complete area coverage. Although this research did not create completely optimized paths, it has uncovered issues worthy of further investigation. For example, by making the genetic algorithm more intelligent and/or by adding constraints specific to agricultural problems, genetic algorithm-based planning could become capable of determining optimum paths even on uneven field terrains, for example by representing the field in a threedimensional format. Recently, algorithms that search for the optimal decomposition of a complicated field into subfields and for the optimal driving direction have been developed. Sörensen et al. (2004) presented a planning method for finding the optimal coverage path for a designated field operation, applying a range of solution methods developed for the Chinese postman problem (Greistorfer, 1995). Oksanen and Visala (2007), meanwhile, presented two different algorithms to solve the coverage path planning problem for agricultural machines. The first merge-and-search algorithm, based on a trapezoidal split, was used to split a complex-shaped field, including obstacles, into smaller parts. The second algorithm utilizes a bottom-to-top approach and solves the problem recursively for realtime usage. As a complement to previous research, Bochtis (2008) presented an algorithmic procedure for the optimal execution of field operations into each subfield. The procedure computes traversal sequences for parallel field tracks, and so improves the field efficiency of a fleet of agricultural machines operating in a field or in a number of geographically dispersed fields. It does this by minimizing the total nonworking distance traveled. Field coverage is expressed as the traversal of a weighted graph and the problem of finding optimal traversal sequences is shown to be equivalent to finding the shortest tours in the graph. The optimization problem was also formulated and solved as a binary integer programming problem. Experimental results showed that by using the specific algorithmically computed optimal sequences; the total nonworking distance can be reduced by up to 50%. An implementation of this procedure for conventional agricultural machines supported by auto-steering systems is presented in Bochtis and Vougioukas (2008). The majority of previous research has been designed to explore new applications for existing algorithms from mature research areas, rather building new specialized algorithms. It seems clear that utilization of advanced techniques from operation research will offer totally new dimensions for the optimal planning of multiple-machine operations.

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5.5

ICT TECHNOLOGIES IN AGRICULTURE

The agricultural sector is currently benefiting from a wide range of new ICT tools that are helping improve the flow of information for the real-time management of agricultural crops and the transfer of data throughout the supply chain. Three emerging technologies are described here: the ISOBUS system in farm machinery, RFID technology and wireless sensor networks.

5.5.1

ISOBUS system

To enable automated data recording on the go, over the last decade the main farm machinery manufacturers have been working on the standardization of information flow between the tractor, the tools and the farm office. Machine data are based on a number of sensor parameters, such as speed, fuel consumption, draft force and chemical usage rate. With the help of a GPS system for positioning and devices for application control and data collection, these data can be used for monitoring actual field operations. However, due to the different data formats used in the sensors and the machinery, a standardized system has been developed by the major machinery manufacturers, the ISOBUS system (ISO, 2007a,b). ISOBUS specifies a serial data network for control of and communication with forestry or agricultural tractors and mounted, semi-mounted, towed or self-propelled tools. Its purpose is to standardize the method and format of transfer of data between sensors, actuators, control elements, and information storage and display units, whether mounted on, or part of, the tractor or implement (Figure 5.5). The information from the tractor and the tools can be linked to a farm management information system, which is on the farm PC, so that the farmer can see and document all parameters on real time (ISO, 2007b).

Implement ECU and implement bridge

Implement subnetwork bus

VT

Task controller mgt. computer gateway

GPS

Implement bus Hitch Implement ECU

Transmission

Tractor ECU

Engine

Tractor bus

Implement ECU

Figure 5.5 IOSBUS system on a tractor and implement. ECU, electronic control unit; VT, virtual terminal (Stone et al., 1999).

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Traceability systems based on radio-frequency identification technology

Quality is today the most important factor in improving the competitiveness of horticultural produce as, for most products we have local overproduction or large volumes of imports into the EU. In addition, over recent years, sorting and packaging of all horticultural produce are required for retailing within the EU. Integrated production of horticultural crops offers safe, high-quality food for producers and consumers, as well as protection of the environment. A basic part of integrated production, sorting and packaging (which is necessary for food safety) is product traceability and the reduction of quality losses throughout the postharvest chain. Development and application of certification systems will complete the farmer’s technical and economic organization and will help in building cooperation between growers and all the other parties involved, particularly the scientists who support innovation. With an increasing demand for security and safety, documentation for food products, from field to customer, has become increasingly demanding (Thysen, 2000). RFID has been accepted as a new technology for a well-structured traceability system (Sahin et al., 2002). It has been projected that the applications of RFID will grow rapidly in the next 10 years (Sangani, 2004). Much research has been conducted to support this potential. Nowadays, the international business community acknowledges the advantages of RFID technology over barcodes (WinterGreen Research, 2005) in the areas of marking and traceability of goods. Substantial efforts have been made to incorporate RFID into the processes of packaging, transporting and supplying consumer goods. In addition, the need for integration of RFID sensor network systems has been acknowledged by significant hardware and software manufacturers worldwide (IBM, INTEL, Oracle, Microsoft). During 2006, the completion of some important pilot projects in the field was expected (Collins, 2005). An RFID system consists of a device capable of transmitting and receiving a radio signal (interrogator, reader), which communicates through a standard protocol with a tag that includes an integrated circuit for the implementation of the communication protocol, a memory and an antenna. This tag is of the dimensions of a credit card (Finkenzeller, 2003). By use of this – half duplex – communication link, the RFID reader writes and reads information to and from the memory of the RFID tag. The power for the signal is supplied to the tag through a radio signal of a different frequency, which is also transmitted by the reader. As a result, the tag does not need an external power source (battery) for communicating. Like barcode technology, the reader can be fixed or portable. In a sense, the tags represent a technological extension of the concept of barcode labels, but offer the advantage of storing a greater quantity of information. In addition, when compared to traditional barcode readers, RFID readers can simultaneously exchange information with more than one tag (point-to-multipoint) and without optical contact (line-of-sight) or the need for a specific orientation. RFID readers can also transfer the information they have collected through to other cable or wireless communication networks. In summary, we can conclude that an RFID system consists of (Figure 5.6): ● ● ●

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a fixed or portable reader; RFID tags; application edgeware.

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Antenna

Reader

Tag

Computer

Figure 5.6 An RFID system.

The main features of the system are: ●

●

● ● ●

The reader sends RF data to and receives data from the tag via antennas and can have multiple antennas. The tag consists of a microchip that stores the data, an antenna and a carrier to which the chip and antenna are mounted. A clear line of sight is not required for the reader to detect the tag. RFID tags are dynamic in that the information they contain can be changed or updated. RFID tags can also carry information that allows for the unique identification of each instance of a product passing the reader, as well as the product type.

The most innovative applications of RFIDs today are those which incorporate integrated sensor microsystems within the tags, and which can therefore measure physical quantities such as temperature, humidity, acceleration, pressure and force. These microsystems record the physical quantity of interest with a specific sampling frequency, process the signal, compress the information collected and store it in the tag’s memory. From here it becomes available to the whole network. The operation of these microsystems is based on the use of extremely low-power integrated circuits, the power to which is supplied by internal recyclable batteries in paper form (power-paper). The RFID tag and sensor system has extremely low costs, the dimensions of a credit card and a lifetime of more than a year. It allows companies to manage the chain of processes from production, packaging, transport, storing and supply of their products (supply-chain management), helping them to improve the quality and competitiveness of their products and services. Management efficiency and product visibility are the two main reasons for using RFID in agriculture. Processors, manufacturers and retailers are all finding RFID to be a useful tool, and one that can be used in agriculture industry for the decidedly important goal of traceability. So far, RFID technology has been used for animal identification, for food packaging and inspection, and of course in the transportation chain from farm to fork. A virtual moving fence for controlling the movement and behavior of cows was developed by Butler et al. (2004). The virtual fence is created by applying an aversive stimulus to an animal when it approaches a predefined boundary. It is implemented by a small animal-borne

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Figure 5.7 A fully assembled smart collar, with PDA case open and a cow with a collar (Butler et al., 2004). © 2004 IEEE.

computer system with a GPS receiver. This approach allows the implementation of virtual paddocks inside a normal physically fenced field. Since the fence lines are virtual they can be moved by reprogramming as required by the needs of animal or land management. Each animal in the herd is given a smart collar consisting of a GPS, a personal digital assistant (PDA), a radio unit and a sound amplifier (Figure 5.7). Location is determined using the GPS and is verified through measurement of the proximity of the cow to the boundary fence. When approaching the perimeter, the animal receives a sound stimulus, which drives it away from the fence. In livestock, body temperature is an important parameter for assessing stress. A new telemetric body-temperature measurement system was evaluated by three independent laboratories for its research application in poultry, swine, beef and dairy cattle (Brown-Brandl et al., 2001). In the case of poultry and swine, the system employs surgery and freetemperature sensors that are orally administered to allow short-term monitoring. Although the system has been successfully tested and evaluated it should be noted that due to the cost of the system, the surgery involved (in some applications), and the need for filtering of data, careful consideration needs to be given to ensure that telemetry is the best method for the experimental protocol. Haapala (2003) tested the performance of electronic identification tags and various readers on cattle at extremely cold temperatures. His work was performed in Finland, in winter, where temperatures can fall to –50°C with rapid and frequent fluctuations from +5 to –25°C). In the area of food packaging, Wentworth (2003) developed sensors for the rapid detection of microbes. His intention was to try to produce cheap, disposable RFID sensor tags that could be placed on food products, such as packets of chicken, and then be scanned for history, contamination and inventory control. Information that could be stored on the RFID sensor tag includes location, date and time of events such as the farm, processing plant, distributor, supermarket, and problems with contamination or temperature. The biosensor was based on acoustic wave platforms incorporated into circuits such that a change in loading on the selective film caused a measurable frequency shift in the circuit. In order to improve animal welfare and meat quality, and reduce environmental impacts comprehensive and detailed research is required to develop new knowledge and methods, particularly in respect to logistics. A transport surveillance system has been developed which integrates the following information: individual identification of animals, unloading place and time, temperature and movement (Geers et al., 1997; Gebresenbet et al., 2003). These data are collected by telemetry and GPS, and are transmitted to a dispatch center by

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Production traceability system Management resume

RFID

Environmental resume

Environmental factors measurement system

RFID

Crops remote sensing system

Remote control

Internet

AP (Control room)

Precisions agriculture management systems

Variable spraying control systems

Environmental control system

Figure 5.8 An RFID-integrated multi-functional remote sensing system (modified from Chang Yang et al., 2008).

the global system for mobile communication (GSM). It was reported that the system greatly improved animal welfare during handling and transportation. However, the whole logistics chain needs to be considered if comprehensive solutions are to be reached. The use of RFID in temperature monitoring during fruit transportation was studied by Amador et al. (2008). This was done by comparing the performance of RFID temperature tags against conventional temperature tracking methods, and RFID temperature tags with probe versus standard RFID. The study dealt with the temperature mapping of a trial shipment comprising pallets of crownless pineapples instrumented using various RFID and traditional temperature data loggers. The results showed the many advantages of RFID temperature tracking, such as quick instrumentation and data recovery, and the possibility of accessing the sensor program and data at any point of the supply chain without requiring a line of sight. The feasibility of RFID technology in wireless and real-time monitoring of soil properties was studied by Hamrita and Hoffacker (2005). They developed a laboratory prototype system for wireless measurement of temperature using a commercially available 13.56-MHz RFID passive tag. Although limitations in transmission range (less than 1 m) would normally necessitate proximity when reading the sensor, use of existing equipment that regularly passes over the field as a mount for the interrogator, for example center pivot booms or sprayers, would increase the feasibility of this telemetry strategy. In greenhouses, environmental control of temperature, relative humidity and lighting are vital to the cultivation of crops. For these purposes, RFID technology is ideal. A multifunctional remote-sensing system integrating RFID technology alongside remote spectral imaging and environmental sensing was developed by Chang Yang et al. (2008) to enhance seedling production and management in greenhouses. The system’s measurements of temperature, relative humidity and lighting conditions were able to provide the spatial distribution profiles of these environmental parameters in the greenhouse. The RFID-integrated multi-functional remote-sensing system is shown in Figure 5.8. RFID plays an important role in this system, which included seedling spectral image acquisition, spatial variation analysis of environmental factors, and wireless information transmission (Figure 5.9). The RFID information was recorded with the boom location, enable analysis of images and

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Seedlings in greenhouses

81

Tag

RFID Production traceability system

Production database

Multi-functional remote sensing systems

Remote sensing & monitoring

Figure 5.9 The role of RFID between the tags, production database and remote sensing system (modified from Chang Yang et al., 2008).

environmental factors of the seedlings. The relational database fed by the RFID system could also track additional information such as greenhouse operators, seedling species and cultivation management factors. As consumer demand for better food quality and safety increases, the demand for traceability systems incorporating rigorous inspection and systematic detection, labeling and recording of quality and safety parameters will steadily grow. RFID is the most important identification tool to establish an effective traceabilty system. When combined with wireless sensors, RFID can also record important parameters (environment, climate) along the chain, increasing its usefulness and efficiency.

5.5.3

Wireless sensor networks

One of the biggest impacts of ICT in agriculture is the ability to transfer data wirelessly. Combining this with the advent of small cheap motes (low powered, cheap computer applications connected to several sensors), the acquisition of real-time data will have a profound impact on how we manage crops in the future. These technological opportunities will be integrated into commercially viable solutions for the mainstream farmer to improve competitiveness and reduce environmental impact. Wireless informatics and smart motes have been investigated by, for example Pierce and Elliott (2008) have shown that there is significant potential. Low-power electronics and improved batteries combine to give systems that can be supplied by renewable energy sources such as biological fuel cells, wind power and solar cells. Low capital costs and almost zero running costs allow multiple units to be purchased, giving high spatial resolution and consequently more detailed management information. Wireless motes combined

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Figure 5.10 Field server – the Japanese soil scouting system.

with novel sensors provide a level of information about the growing crop that has not been available before. There are many sensing techniques that can ascertain crop and soil conditions. A number of them could be used commercially in existing production systems, but for the fact that they take a long time to process the data and require logistical support. Examples are weed recognition using machine vision, multi-spectral response from the plant canopy that can indicate stress (whatever the cause) and chlorophyll content that is associated with crop vigour. Biosensors are being developed that can recognize a range of specific crop pathogens. Carbon dioxide has been associated with soil health and can give an indication of compaction or anaerobic subsoil processes. Ethylene can be associated with pest attack, and soil conductivity has been correlated with soil moisture. Soil nitrates, organic matter, chargedion exchange capacity, pH and soil moisture have all been measured at different depths using near infrared reflectance with a soil photospectrometer in real time (Shibusawa et al., 2000). Ion selective field effect transistors can be modified to be sensitive to nitrates, pH and other factors from soil solution (Birrell and Hummel, 2001). Some of these sensing systems are still in the research phase but they hold great promise for the improvement of our understanding and management of the growing crop and its environment. The reason some of these systems are not used now is that the associated cost of an operator’s time does not justify the information benefit. If these systems were automated then the cost of accessing the data would be dramatically reduced. After 15 years of practising precision agriculture in Australia, McBratney et al. (2005) proposed that the future of precision agriculture is the understanding of temporal variation. The management of temporal variation within the field can be addressed by the use of sensing elements during the growing season. Wireless sensor networks in agriculture and parks management is one of the most promising areas for research. A wireless sensor network should collect data about the local environment (solar radiation, temperature, relative humidity and soil moisture) and crop growth (leaf and branch shapes, blooming, fruiting and size). These data can be automatically collected and transferred to a personal computer inside the farm office through a wireless connection. In this area, there are a number of systems that are either at the prototype stage or are entering commercial use, such as the Field Server system in Japan (Figure 5.10) (Hashimoto et al., 2007), the a-Lab weather station in Finland (http://www.a-lab.com) and the field scout wireless system from Helsinki University (Tiusanen, 2007).

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REFERENCES Amador, C., Emond, J.P. and Nunes, M.C. (2008) Application of RFID technologies in the temperature mapping of the pineapple supply chain. In: Proceedings of the Food Processing Automation Conference, 28–29 June 2008, Providence, Rhode Island. ASABE, St. Joseph, MI. Bertsimas, D. and Van Ryzin, G. (1993) Stochastic and dynamic vehicle routing problem in the euclidian plane with multiple capacitated vehicles. Operation Research, 41(1), 60–76. Bertsimas, D., Jaillet, P. and Odoni, A.R. (1990) A priori optimization. Operations Research, 38(6), 1019– 1033. Billingsley, J. (2000) Automatic guidance of agricultural mobiles at the NCEA. Industrial Robot, 27(6), 449–457. Birrell, S.J. and Hummel, J.W. (2001) Real-time multi ISFET/FIA soil analysis system with automatic sample extraction. Computers and Electronics in Agriculture, 32(1), 45–67. Blackmore, B.S., Griepentrog, H.W., Fountas, S. and Gemtos, T.A. (2006) A specification for an autonomous crop production mechanization system. Agricultural Engineering International: the CIGR Ejournal, Manuscript PM 06 032. Available at: http: www.cigrjournal.org/index.php/Ejounral/article/view/900/894 (accessed October 2010). Blackmore, S., Have, H. and Fountas, S. (2002) Specification of behavioural requirements for an autonomous tractor. In: Qin Zhang (ed.), Automation Technology for Off-Road Equipment, Proceedings of the 26–27 July 2002 ASAE Conference, Chicago, Illinois. ASAE, St Joseph, MI, pp. 33–42. Bochtis, D.D. (2008) Planning and control of a fleet of agricultural machines for optimal management of field operations. PhD thesis, Agricultural University of Thessaly, School of Agriculture, Agriculture Engineering Laboratory. Bochtis, D. and Vougioukas, S. (2008) Minimising the non-working distance travelled by machines operating in a headland field pattern. Biosystems Engineering, 101(1), 1–12. Bochtis, D., Vougioukas, S., Ampatzidis, Y. and Tsatsarelis, C. (2007a) Online coordination of combines and transport carts during harvesting operations. In: J.V. Stafford (ed.), Proceedings of the 6th European Conference on Precision Agriculture, 3–6 June 2007, Skiathos, Greece. Wageningen Academic Publishers, Wageningen, The Netherlands. Bochtis, D., Vougioukas, S., Tsatsarelis, C. and Ampatzidis, Y. (2007b) Optimal dynamic motion sequence generation for multiple harvesters. Agricultural Engineering International: the CIGR Ejournal. Manuscript ATOE 07 001. Vol. IX. Available at: www.cigrjournal.org/index.php/Ejounral/article/ view/900/894 (accessed October 2010) Brown-Brandl, T.M., Yanagi, T., Jr., Xin, H., Gates, R.S., Bucklin, R.A. and Ross, G.S. (2001) A new telemetry system for measuring core body temperature in livestock and poultry. Applied Engineering in Agriculture, 19(5), 583–589. Buckmaster, D.R. (2006) Systems approach to forage harvest operations. 2006 ASAE Annual Meeting. Paper number 061087. Michigan. Busato, P. and Berruto, R. (2008) System approach to biomass harvest operations: simulation modeling and linear programming for logistic design. ASABE Annual International Meeting, June 29–July 2, 2008. Paper Number 084565. Providence, Rhode Island. ASABE, St Joseph, MI. Busato, P., Berruto, R. and Saunders, C. (2007) Modeling of grain harvesting: interaction between working pattern and field bin locations. Agricultural Engineering International: the CIGR Ejournal. Manuscript CIOSTA 07 001. Vol. IX. Available at: www.cigrjournal.org/index.php/Ejounral/article/view/900/894 (accessed October 2010). Butler, Z., Corke, P., Peterson, R. and Rus, D. (2004) Virtual fences for controlling cows. In: Proceedings of the 2004 IEEE International Conference on Robotics and Automation, New Orleans, April 26–May 1. Collins, J. (2005) Dutch supermarket plans RFID trial. The RFID Journal, February. Finkenzeller, K. (2003) The RFID Handbook, 2nd edn. John Wiley & Sons, Chichester. Freyberger, F. and Jahns, G. (2000) Symbolic course description for semiautonomous agricultural vehicles. Computers and Electronics in Agriculture, 25, 121–132. Gebresenbet, G., Ljungberg, D., Van de Water, G. and Geers, R. (2003) Information monitoring system for surveillance of animal welfare during transport. In: Proceedings of the 4th European Conference in Precision Agriculture, Berlin, Germany, June 14–19 2003. Wageningen Academic Publishers, Wageningen, The Netherlands. Geers, R., Puers, B., Goedseels, V. and Wouters, P. (1997) Electronic Identification, Monitoring and Tracking of Animals. CAB International, Wallingford.

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Godwin, R.J., Earl, R., Taylor, J.C. et al. (2001) Precision farming of cereal crops: A five-year experiment to develop management guidelines, Project report 264e. Home Grown Cereals Authority, London. Greistorfer, P. (1995) Solving mixed and capacitated problems of the Chinese postman. Central European Journal for Operations Research and Economics, 3(4), 285–309. Griepentrog, H.W., Nørremark, M., Nielsen, H. and Blackmore, B.S. (2005) Seed mapping of sugar beet. Precision Agriculture Journal, 6, 2157–2165. Guana, S., Nakamuraa, M., Shikanaib, T. and Okazakia, T. (2008) Hybrid Petri nets modeling for farm work flow. Computers and Electronics in Agriculture, 62, 149–158. Haapala, H.E.S. (2003) Operation of electronic identification of cattle in Finland. In: The Proceedings of the 4th European Conference in Precision Agriculture, Berlin, Germany, June 14–19 2003. Wageningen Academic Publishers, Wageningen, The Netherlands. Hamrita, T.K., Hoffacker, E.C. (2005) Development of a ‘smart’ wireless soil monitoring sensor prototype using RFID technology. Applied Engineering in Agriculture, 21, 139–143. Hannan, M.W. and Burks, T.F. (2004) Current developments in automated citrus harvesting, Paper No. 04–3087. ASAE, St Joseph, MI. Hashimoto, A., Ito, R., Nakanishi, K. et al. (2007) An integrated field monitoring system for sustainable and high-quality production of agricultural products based on BIX concept with field server. In: Proceedings of the 2007 International Symposium on Applications and the Internet Workshops (SAINTW’07), Hiroshima, Japan, 15–19 January 2007. IEEE Press. Hollingum, J. (1999) Robots in agriculture. Industrial Robot, 26(6), 438–445. Huang, W. (2001) Optimal line-sweep-based decompositions for coverage algorithms. In: Proceedings of the 2001 IEEE International Conference on Robotics and Automation, 21–26 May 2001, Seoul, Korea. IEEE Press, New York. ISO (2007a) ISO 11783–1: 2007 Tractors and machinery for agriculture and forestry – serial control and communications data network. Part 1: General standard for mobile data communication. ISO (2007b) ISO/FDIS 11783–10: 2007 Tractors and machinery for agriculture and forestry – serial control and communications data network. Part 10: Task controller and management information system data interchange. Kondo, N. and Ting, K.C. (1998) Robotics for Bioproduction Systems. ASABE, St Joseph, MI. Kondo, N., Ninomoya, K., Hayashi, S., Tomohiko, O. and Kubota, K. (2005) A new challenge of robot for harvesting strawberry grown on table top culture. ASAE Paper No. 053138. ASABE, St Joseph, MI. Kondo, N., Monta, M. and Noguchi, N. (2006) Agri-Robot (II) – Mechanisms and Practice. [In Japanese]. McBratney, A., Whelan, B. and Ancev, T. (2005) Future directions of precision agriculture. Precision Agriculture, 6, 7–23. Morgan, M. and Ess, D. (1997) The Precision Farming Guide For Agriculturists. Deere, Moline. Oksanen, T. and Visala, A. (2007) Path planning algorithms for agricultural machines. Agricultural Engineering International: the CIGR Ejournal, Manuscript ATOE 07 009. Vol. IX. Available at: www. cigrjournal.org/index.php/Ejounral/article/view/900/894 (accessed October 2010). Papastavrou, J.D. (1996) a stochastic and dynamic routing policy using Branchin processes with state dependent immigration. European Journal of Operational Research, 95(1), 167–177. Pierce, F.J. and Elliott, T.V. (2008) Regional and on-farm wireless sensor networks for agricultural systems in Eastern Washington. Computers and Electronics in Agriculture Archive, 61(1), 1–3. Pilarski, T., Happold, M., Pangels, H., Ollis, M., Fitzpatrick, K. and Stentz, A. (2002) The Demeter system for automated harvesting. Autonomous Robots, 13, 1. Ryerson, A.E.F. and Zhang, Q. (2007) Vehicle path planning for complete field coverage using genetic algorithms. Agricultural Engineering International: the CIGR Ejournal. Manuscript ATOE 07 014. Vol. IX. July, 2007. Available at: www.cigrjournal.org/index.php/Ejounral/article/view/900/894 (accessed October 2010). Sadeh, N.M. and Fox, M.S. (1996) Variable and value ordering heuristics for the job shop scheduling constraint satisfaction problem. Artificial Intelligence, 86, 1–41. Sahin, E., Dallery, Y. and Gershwin, S. (2002) Performance evaluation of a traceability system: an application to the radio frequency identification technology. In: Hammamet, Y (ed.) Proceedings of the 2002 IEEE International Conference on Systems, Man and Cybernetics, Tunisia, October 6–9 2002. IEEE Press, Piscataway, NJ. Sangani, K. (2004) RFID sees all. IEE Reviews, 50, 22–24.

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Shibusawa, S., Anom, I. M., Sata, H. et al. (2000) Online real-time soil spectrophotometer. In: Robert, P.C., Rust, R.H. and Larson, W.E. (eds) Proceedings of the 5th International Conference on Precision Agriculture. ASA, CSSA, SSSA, USA. Søgaard, H.T. and Lund, I. (2005) Robotic weed control with plant recognition and micro-spraying. In: Stafford, J.V. and Thylen, L. (eds) Proceedings of the Fifth European Conference on Precision Agriculture, Uppsala, Sweden, 13–17 June 2005. Wageningen Academic Publishers, Wageningen, The Netherlands. Søgaard, H.T. and Sørensen, C.G. (2004) A model for optimal selection of machinery sizes within the farm machinery system. Biosystems Engineering, 89(1), 13–28. Solomon, M.M. and Desrosiers, J. (1986) Time window constrained routing and scheduling problems: a survey. Transportation Science, 22(1), 1–11. Sørensen, C.G., Bak, T. and Jörgensen, R.N. (2004) Mission planner for agricultural robotics. In: Proceedings of Agricultural Engineering 2004. Leuven, Belgium. Sørensen, S.G., Jørgensen, R., Maagaard, J., Bertelsen, K., Dalgaard, L. and Nørremark, M. (2008) Usercentered and conceptual technical guidelines of a plant nursing robot. 2008 ASABE Annual International Meeting, Rhode Island June 29–July 2, 2008. Paper Number 08. Stone, M.L., Kee, D.M. Formwalt, C.W. and Benneweis, R.K. (1999) ISO 11783: An electronic communications protocol for agricultural equipment. ASAE, St Joseph, MI. Tanigaki, K., Fujiura, T., Akase, A. and Imagawa, J. (2008) Cherry-harvesting robot. Computers and Electronics in Agriculture, 63, 65–72. Thysen, I. (2000) Agriculture in the information society. Journal of Agricultural Engineering Research, 76, 297–303. Tiusanen, M.J. (2007) Validation and results of the Soil Scout radio signal attenuation model. Biosystems Engineering, 97, 11–17. Van Henten, E.J., Hemming, J., Van Tuyl, B.A.J., Kornet, J.G. and Bontsema, J. (2003) Collision-free motion planning for a cucumber picking robot. Biosystems Engineering 86(2), 135–144. Wentworth, S.M. (2003) Microbial sensor tags. In: The 2003 IFT (The Institute of Food Engineering) Annual Meeting Book of Abstracts. IFT, Chicago. Wilson, J.N. (2000) Guidance of agricultural vehicles – a historical perspective. Computers and Electronics in Agriculture, 25, 1–9. WinterGreen Research (2005) RFID Network Equipment Market Opportunities, Strategies, and Forecasts, 2005 to 2010. WinterGreen Research Inc., Lexington, MA. Yang, I.C., Chen, S., Huang, Y.I. et al. (2008) RFID-integrated multi-functional remote sensing system for seedling production management. In: Proceedings of the Food Processing Automation Conference, 28–29 June 2008, Providence, Rhode Island. ASABE, St Joseph, MI.

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6

Telematics for Efficient Transportation and Distribution of Agrifood Products

Charalambos A. Marentakis

6.1

INTRODUCTION

For the agrifood industry the issue of product traceability over the supply chain is of great importance. Agrifood product companies use various methods and technologies to safeguard product quality and their market reputation. Moreover, management of contemporary complex and rapidly changing logistics systems require high availability of real-time information about the position and state of a company’s fleet and freight. Supply-chain management, and more specifically the freight transportation channel, is currently supported by technological innovations in information and communication technologies (ICT) in many ways, providing valuable information for carriers and shippers to manage fleets and goods effectively, and at the same time enhancing their capability of responding to changing customer requirements. ICT applications allow decision-makers and planners to effectively handle problems related to the daily operation of distribution centres, freight forwarding, urban distribution, long-haul freight transport, loading and unloading planning, route scheduling etc. The growing volume of data, coupled with the need for flexibility in daily operations, requires the support of suitable information technology. Recent advances in microelectronics and computing technology have enhanced the capability of electronic devices, for example display size, interfaces, portability and energy consumption. In addition, new portable devices (personal data assistants and personal navigation systems have been developed recently and do not require fixed installation in vehicles. Coherent combinations of ICT technologies and devices constitute specific classes of sophisticated information systems (typically referred to as ‘telematics’ or automatic vehicle location systems). These offer monitoring and interaction capabilities between fleet trucks, drivers and freight stakeholders at almost any level of management, covering the planning, the trip and route monitoring, and reporting needs. The need for ICT support in freight transport and distribution becomes even more important when transported goods are of high value, perishable, time-dependent, hazardous or related to just-in-time services for those companies aiming at supplying products in complex and continuously growing distribution networks. Typical examples of these are agricultural and food products. Such networks aim to deliver products to stores ranging from small retailers (offering a range of 1000–3000 stock keeping units (SKUs), 90% of which are agrifood products) to supermarkets (offering a range of 20 000–30 000 SKUs, 75–90% of which are agrifood products) and hypermarkets (offering Intelligent Agrifood Chains and Networks, First Edition. Edited by Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis. © 2011 by Blackwell Publishing Ltd. Published 2011 by Blackwell Publishing Ltd.

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40 000–150 000 SKUs, 60–70% of which are agrifood products). Moreover, recent nutritional trends require the delivery of fresh biological agrifood products to the consumer’s door. It is obvious that the operation of such sophisticated networks is difficult. The aim of this chapter is three-fold. Initially, it provides a non-technical review of the telematics sector, the relevant communications technologies and the typical IT architecture structures. Secondly, it summarises the special logistical and information requirements for the distribution of agrifood products and describes how telematics may enhance the quality attributes of products through product and fleet surveillance technologies. Finally, it addresses operations efficiency and yield management issues and gives some examples of how telematics may enhance the operational efficiency of the fleet. The chapter is structured as follows. In section 6.2 there is a brief overview of the technological prerequisites and components of telematics systems and applications, and then, in section 6.3, a discussion of the application of telematics to freight operations. section 6.4 outlines the value of information and the benefits a company may gain by investing in information gathering systems. Section 6.5 focuses on the distribution of agrifood products and related informational needs while section 6.6 presents how telematics may support the distribution of agrifood products. Finally, section 6.7 concludes by presenting some emerging applications in freight transport and distribution as a result of the combination of telematics and related information and communication technologies.

6.2

TECHNOLOGICAL PREREQUISITES FOR TELEMATICS

Telematics is the combination of the transmission of information over a telecommunication network and the computerised processing of this information (Goel, 2007). The rapid diffusion of telematics was a result of the development of several communication technologies, namely (Giannopoulos, 2004): wireless communications (the Global System for Mobile Communication (GSM) and the Universal Mobile Telecommunications System (UMTS) ), positioning technologies (Global Positioning System (GPS) ), broadband communications, first- and second-generation internet services, dedicated short-range communications (DSRC), general packet radio services (GPRS) and other improvements concerning the speed and capacity of computers and software. The core technologies for telematics are described below.

6.2.1

Wireless communications

Wireless communications allow transmission of information over the air by means of electromagnetic waves and using wireless devices. Equipment, frequencies and data format depend mainly on the desired geographic coverage. The major characteristics of some widely used wireless technologies are illustrated in Table 6.1.

6.2.2

Positioning systems

Numerous technologies for positioning have been developed over the years. A descriptive overview and comparison of different communication technologies in terms of area coverage and accuracy can be found in Vossiek et al. (2003), which also provides an overview of the different distance and location measurement methodologies. Most common positioning systems use the Global Navigation Satellite System (GNSS). These technologies are primarily focusing on detection of the spatial characteristics

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89

Wireless communications technologies.

Technology

Frequency

Bitrate

Geographic coverage

User

TErrestrial Trunked Radio (TETRA)

385–390, 395–399.9, 410–430, 450–470, 870–876, 915–921 MHz

7.2 kbps

Wide

Organisations, companies

Cellular

GSM: 890–915, 935–960 MHz (GSM) Terrestrial UMTS: 1900–1980, 2010–2025, 2110–2170 MHz

9.6 kbps

Indoor, urban, suburban

Organisations, companies, individuals

Downlink: 5–15 kbps Uplink: 55–165 bps

34% of Earth’s surface with 0.25 s delay (global coverage via four satellites)

Organisations, companies, individuals

Downlink: 4.8 kbps Uplink: 2.4 kbps

Global coverage with latency

Satellite UMTS: 1980–2010, 2170–2200 MHz

Satellite

Dedicated short-range communication (DSRC)

Geostationary orbit: Inmarsat-C 1530.0– 1545.0 MHz (downlink) 1626.5– 1645.5 MHz (uplink) Qualcomm 10.70–11.70, 12.50– 12.75 GHz (downlink) 14.00–14.25 GHz (uplink) Low-earth orbit: 137.00– 138.00 MHz (downlink) 148.00– 150.05 MHz (uplink) Microwaves: 5.795– 5.805 GHz, 5.805– 5.815 GHz

144 kbps (full outdoor) 384 kbps (limited mobility outdoor in urban and suburban areas) 2048 Mbps (low-mobility outdoor in indoor and urban areas)

Short-range vehicle-tovehicle and vehicle-toinfrastructure

Organisations, companies, individuals (e.g. toll collection, collision avoidance, etc.) (Continued )

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Table 6.1

(Continued ).

Technology

Frequency

Bitrate

Broadcasting

Radio data system (RDS)

1187.5 bps on FM radio broadcast

Digital audio broadcasting (DAB) 47–68, 174–240, 1452–1492 MHz

3 Mbps (2.3 Mbps for data 0.6–1.7 Mbps actually available due to redundancy)

Geographic coverage

User

Organisations, companies, individuals (e.g. traffic message channel)

GSM, Global System for Mobile Communication; UMTS, Universal Mobile Telecommunications System. Adapted from Goel (2007).

(geographical position and altitude, speed and direction) of an object or a human being. The evolution of positioning systems began in early 1960s with the US Navy, which developed Transit, a tool to help navigate ships and submarines. In 1973, the US Air Force and Navy developed the NAVSTAR (Navigation Satellite Timing and Ranging) global positioning system and, in 1989, the GPS constellation of satellites was put into orbit for the first time. In 1993, GPS was set free for civilian use internationally. Since then, numerous companies have designed and developed devices and applications for commercial use. The only fully operational GNSS is the US GPS, which is used for commercial, civil and military applications. Physically, GPS is a constellation of 24 satellites, orbiting the earth at approximately 20 180 km every 12 h on six different orbital planes, and constantly transmitting their relative positions. At any location and time at least four satellites are constantly visible above a 15° cut-off angle. All GNSS systems locate a moving object through trilateration (triangulation) – a technique utilising the exact position of three satellites, their relative distance from the moving object and a fourth satellite for time correction, fixing any problems of inconsistencies between the satellite and the moving object’s clocks. GPS technology consists of three segments (Figure 6.1): the space segment, the control segment and the user segment. 6.2.2.1

Control segment

The control segment is responsible for constantly monitoring satellite health, signal integrity and orbital configuration from the ground. The major components are: ● ● ●

monitoring stations; the master control station (MCS); ground antennas.

Monitoring stations are constantly monitoring and receiving information from GPS satellites and sending orbital and clock information to the MCS. The MCS, which is located in Colorado

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Satellite constellation

Space segment

Transportation (air, sea, land)

User segment

Earth station

Control segment

Figure 6.1 GPS-X-02007. Adapted from UBLOX (2007).

Springs in Colorado, constantly receives GPS satellite orbital and clock information from the monitoring stations, makes precise corrections to the data and sends back the information (ephemeris data) to the GPS satellites using ground antennas. Finally, ground antennas receive corrected orbital and clock data form the MCS and send them to GPS satellites. 6.2.2.2

User segment

The user segment consists of a GPS receiver that collects and processes signals from GPS satellites that are in line of sight. User devices use this data to display location, speed, time, mapped data and other information. 6.2.2.3

Space segment

Satellites are continuously sending signals down to earth, the time of which is precisely defined by atomic clocks. The earth-located GPS receiver receives signals from different satellites with different propagation delays, depending on the receiver’s current location, and measures the time of each signal’s arrival. It then calculates the difference between the measured times of arrival and the predefined time of signal departure and in this way can find the distance (range) from each satellite. Inaccuracies in the calculation of the range of satellites are commonly referred to as ‘pseudo-ranges’. The computation of latitude, longitude and altitude based on pseudo-ranges requires four satellites instead of three, the fourth being responsible for time. Information about the exact satellite position and time of signal transmission is necessary for the calculation of a GPS device’s position. For this reason each satellite also transmits a digital signal at 50 bps, with precise information on the satellite’s orbital parameters (called ephemeris).

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The precision of the calculated position is affected by many factors. The most important of them are device accuracy, satellite clock accuracy, satellite orbital inclination, atmospheric and climate influences (humidity, clouds etc.) and physical obstacles (tall buildings, tunnels, etc.). GPS technology was first developed in the 1970s for military purposes and offered limited accuracy (selective availability (SA) ) with typical errors of ±100 m for civilian applications. In early 2000, typical SA errors were 10 m horizontally and 30 m vertically. Recent commercial GPS utilises complementary methods like differential corrected GPS (DGPS) to improve accuracy and correct any errors. The European Position System (Galileo) is expected to provide measurements that will range from 3 to 5 m (Lee et al., 2008) or even centimetre-level accuracy. A concise but comprehensive description of the GPS system and its applications can be found in Mintsis et al. (2004), while a brief history of the evolution of GPS, its operation and potential applications may be found in Theiss et al. (2005). A technique called dead reckoning is used alongside GPS to overcome GPS signal loss problems, using simple devices like speedometers (for distance calculation) and gyroscopes (to retrieve direction). Other methods used for positioning purposes are cellular networks and signpost systems. Cellular networks use various positioning methodologies, for example: ●

●

●

●

cell of origin, which, using current communication cells, has accuracy ranging from 100 m in urban areas to 35 km in rural areas; propagation time for a signal to travel from base station to mobile device, ideally using three base stations; time difference of arrival, which uses the reception of signals from three base stations and then a calculation of the time difference between each pair of arrivals; angle of arrival, which involves measurement of the angle of arrival of a signal from or to a base station.

Signpost systems use fixed beacons and receivers to record a vehicle’s position when it passes the beacon. A detailed analysis of satellite navigation topics can be found in U-BLOX (2007). Besides the benefits described in the previous paragraphs, combined use of GPS and mobile communication technologies (GSM, GPRS) also has a number of technological shortcomings. Firstly, these technologies are not always reliable (or may even be non-operative) in indoor environments, shadowed and cloudy environments or narrow streets, canyons, tunnels, ships, etc. This problem has been partially solved with the development and use of indoor communication technologies, where necessary using Assisted GPS (AGPS). AGPS is different from the DGPS described above: instead of the amplification of accuracy, AGPS aims to improve the ability to detect GPS signals under conditions of low signal-tonoise ratio. Nevertheless, DGPS may be applied alongside AGPS. Importantly, the implementation of such technologies in problematic areas provides higher accuracy than simple GPS. An extended analysis of AGPS technologies and issues has been provided by Richton et al. (2002). Another problem is that the systems may become too slow, especially when the cell communication provider is not reliable. Nowadays most GSM providers compete to offer high quality of service and high geographic (besides population) GSM coverage.

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Telematics for Efficient Transportation and Distribution of Agrifood Products Table 6.2

93

Device-driver communication parameters. Format

Modality

Auditory Visual

Verbal

Spatial

Speech Print

Sound localisation and pitch Analogue pictures

The systems require costly and bulky devices to operate properly. However, recent advances in microelectronics have resulted in the development of lighter and cost-effective devices. Moreover, modern devices are not highly energy-consuming and can provide many hours of autonomous operation. The technology used, and more specifically in-vehicle human-machine interface devices, must be carefully designed to meet human cognitive capabilities. Obviously the presence of a large number of in-vehicle devices places high demands on the driver’s attention. Incorrect design may therefore be dangerous for the driver and public. A comprehensive model describing the relationship between different modes of information presentation (Table 6.2) and extensive information on ergonomic and design issues can be found in Garcia-Ortiz et al. (1995). The critical success factors for a telematics application are compatibility (openness) and scalability. Compatibility ensures that the various components of the telematics application will communicate effectively with the company’s other ICT applications. Scalability means that the telematics application will follow the growth of the company.

6.2.3

Geographical information systems

Geographical information systems (GIS) constitute a special class of information systems for the collection, processing and presentation of geographic data. Data collection is performed through the combined use of aerial images (rough-cut mapping) and mobile mapping (detailed mapping). The collected data are stored in a database and they are further processed by a number of special software programs. Depending on the scope and application, related geographic information is presented in a raster model format (as an array of cells, each assigned specific attributes) and/or in a vector model format (with representation of objects as geometric shapes: point, line or area). A more realistic representation of the road network is achieved for the development of road maps with the use of an international standard named geographic data file. This is based on sets of features (defining real-world objects, e.g. buildings, junctions, addresses), attributes (defining characteristics of features, e.g. direction, one-way streets) and relationships (defining relationships between features, e.g. road signs, roundabouts). Major applications of GIS are in geocoding (representation of locations with the use of geographic coordinates and postal codes), which is used to locate addresses and calculate Euclidean distances, routing (calculation of the shortest, fastest or lowest-cost route between two points) using special shortest-path algorithms like Dijkstra’s algorithm, and map matching (determination of the address of a specific actual location) via the use of special map-matching algorithms. GIS are able to store, process and provide data related to streets, postal codes, consumer data, demographic data and geopolitical boundaries. Depending on the use of the application, different combinations of data categories are used (Garzia-Ortiz et al., 1995).

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6.3

Intelligent Agrifood Chains and Networks

APPLICATION OF TELEMATICS IN FREIGHT TRANSPORT AND DISTRIBUTION

Current and future logistics trends focus on offering fast and accurate services to individual customers, in an efficient and economic manner, as was predicted by Crowley (1998). Moreover, practices like just-in-time, cross-docking, continuous replenishment, efficient consumer response and on-demand transportation services (like taxis, courier, ambulances, etc.) have already been widely adopted by companies aiming to reduce logistics costs and improve customer service. The evolution of e-commerce and e-business have affected the introduction and adoption of new technologies (Roy, 2001) in two ways: firstly as a response to better supply-chain performance and secondly as a pressure for supply-chain improvement, better quality of service, immediate response (also called express logistics) and the need to handle large amounts of data and information. Direct transactions between consumers and companies (B2C) resulted in the elimination of physical supply-chain intermediaries (e.g. wholesalers, retailers) and, as a result, the role of freight transportation and distribution operations become even more demanding. Real-time coordination of distribution fleets and well-structured information availability is a necessity in order to support these new processes and reduce the relative complexity arising from them. Perhaps the most important and challenging application area of telematics is the freight transportation and distribution operations functions of logistics. Logistics functions benefit from telematics by combining trip planning and dispatching with seamless tracking and tracing and proof of delivery. The benefits of telematics are more obvious when applied in third-party logistics companies who operate large owned or leased fleets and provide shared warehousing and distribution services to numerous clients, often consolidating multiple freight loads and visiting several clients for pickup or delivery of freight. Thus the use of telematics applications for planning and monitoring is indispensable to these companies. Depending on company size and business area, telematics applications and their special requirements may vary; frozen food distribution companies mostly require temperature monitoring while courier companies particularly require map guidance. Telematics infrastructure applies to almost any kind of fleet, type of transported asset and business, even where there are different operational requirements. Focusing on freight transport and distribution functions for business applications, telematics applications and services are summarised in Table 6.3. A brief description of some services of special interest follows, while detailed analysis will follow later in the chapter. When planning a trip, a decision maker uses telematics systems to derive information about the route, such as means of transport, points of interest, specific addresses, specific roads, tolls, distances and duration. During the trip, telematics provides information to the planner and to the driver as well. Such information can pertain to remote vehicle monitoring (e.g. variation from scheduled trip, door openings, transported goods’ temperature, breakdowns, safety, weight, fuel consumption), guidance, location-based services (e.g. nearest fuel stations, repair stations etc.). Moreover, a fleet planner may use the telematics infrastructure to replan a vehicle’s route dynamically, according to the current vehicle location, road traffic information and new requirements. A wide range of information can be available to the planner, such as the location of the vehicle, the state of the transported goods, times of departure and arrival between loading and unloading points, respectively, the route

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Telematics for Efficient Transportation and Distribution of Agrifood Products Table 6.3

95

Telematics applications and services for logistics.

Application area

Service

Examples

Traffic and travel information

Pre-trip information On-trip driver information Personal information services Route guidance and navigation

Road network, tolls, weather conditions Traffic information, maps, speed limits Telephony, SMS, e-mail, points of interest (POI) Guidance, re-routing

Vehicle information

Vision enhancement Automatic vehicle operation Longitudinal collision avoidance Lateral collision avoidance Safety readiness Pre-crash restraint deployment

Remote unlocking Telemetry

Commercial vehicle information

Commercial vehicle pre-clearance Commercial vehicle administrative processes Automated roadside safety operation Commercial vehicle on-board safety monitoring Commercial vehicle fleet management

Route control Reporting Maintenance planning/ diagnostics Door opening Climate control

Emergency management

Emergency notification and personal security Emergency vehicle management Hazardous material and incident notification

112/911/999 emergency telephone numbers Malicious threads notification Stolen vehicle recovery

Adapted from Goel (2007).

evolution, length of personnel break, stops for refuelling and many others. All raw data collected during the trip are stored in a database for later processing, with the aim of providing accurate and realistic information for trip evaluation and planning purposes. Modern on-board devices and sensors have strong capabilities and are capable of providing numerous truck, driver and travel parameters (Table 6.4) (Baumgartner et al., 2008). An extensive analysis of the use of telematics in urban real-time distribution operations has been made by Zeimpekis and Giaglis (2006) (Figure 6.2). Although they focus on Greek market, the authors’ core research results can be generalised to almost any logistics market. They focus on the application of telematics to real-time routing, re-routing and monitoring of a distribution fleet, aiming to meet dynamic requirements that appear during the route execution, and describing inter-vehicle wireless communication, back-end wireless connectivity with the distribution centre and real-time decision support in response to intrinsic and exogenous stochastic problems. The data interchange between fleet and fleet owner is accomplished via a fleet telematics system (FTS), which is usually offered by an external provider/intermediary and is supported by GPS and a cellular communications services provider. Integration between realtime FTS and information processing systems leads to the development of real-time fleet management systems (RTFMS). There are three core components of these applications. Firstly, the truck telematic equipment, which includes a GPS receiver for position sensing, GSM/GPRS receiver for voice

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Information available from on-board device.

Parameter

Example

General data

Date and time Position (geographical coordinates and altitude) Vehicle, driver, trailer Status (driving/rest) Change of tachograph Distance driven Fuel consumption Speed

Driving behaviour

Braking behaviour Gear-changing behaviour Driving pedal movements Constancy of speed

Trip difficulties

Gross vehicle weight Number of stops Duration of stops Average gradient

Vehicle technical information

Brake wear Refrigerant level Oil level Disturbance reporting Maintenance scheduling Tyre pressure Load-space temperature pattern

Other

Adapted from Baumgartner et al., 2008.

Depot

Initial vehicle routing & scheduling

On-the-move TRUCK

Delivery point

Real-time monitoring of parameters

Proof of Delivery (PoD)

Order tracking & tracing

Real-time services during delivery

Delivery errors

Figure 6.2 Freight distribution overview (adapted from Zeimpekis and Giaglis, 2006).

and data transmission, on-board monitor/communication device, and sensors for the door, temperature and so on, for continuous measurement. Advanced portable devices may serve as computers too, offering capabilities for data capture, barcode scanning, proof-of-delivery, reconciliation, etc. Obviously, all these devices should be ruggedised terminals, i.e. they must be durable against shocks, high or low temperature and liquids. They should also be equipped with large readable screens, with high visibility and possibly with voice recognition functionality as well. Finally, they should provide connectivity options besides GSM/ GPRS and GPS, such as infrared and Bluetooth.

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The fleet owner’s software may consist of: ●

● ●

routing software (standalone, client or web-based decision support system), which is integrated or interfaced with the fleet owner’s logistics software; fleet-monitoring software; a GIS application containing geographic data and mapping software offering identification of vehicles and points of interest (customers, retailers, distribution centres, etc.), using static or dynamic coordinates that are matched against map data.

The final component of this kind of application is the FTS provider’s infrastructure (computer hardware, software applications and communication infrastructure). In a typical application, the vehicle’s spatial and state data are collected via GPS signals and sensors, respectively. Communication between the fleet and the FTS provider is over wireless or cellular networks, such as SMS messages. The evolution of 2.5G and 3G communication technologies dramatically increased the bandwidth available to fleets, allowing the transmission of high volumes of data (not solely text) and offering always-on functionality. A reference RTFMS is described by See (2007) and is depicted in Figure 6.3. A typical architecture of a telematics system implementation is depicted in Figure 6.4. Any user (carrier, shipper, vehicle driver, etc.) may have access to a variety of information related to trip planning and evolution or may utilise the telematics infrastructure to provide value-added services, such as location-based services. The latter will be further described below. The telematics infrastructure may also be integrated with existing supplier and customer relationship management systems and operations support software (such as warehouse management systems), providing real-time information and value-added services during pick-up and delivery operations. These services might include billing, ex-van sales and credit control. Moreover, telematics applications may be integrated with a company’s backbone enterprise resource planning (ERP) system, operating as a source of real-time automatically collected data, and using them for improved financial analysis, forecasting and reporting. A more detailed analysis of value-added services and facilitation of mobile commerce applications will be presented later in the chapter. Summarising the aforementioned issues, telematics applications offer different degrees of real-time services (Transport Energy, 2003): ● ● ● ● ● ● ●

information on vehicle and driver data; vehicle tracking; trailer tracking; text messaging and provision of information to fleet planners and customers; paperless manifests and proof on delivery; traffic information; on-board navigation.

While it is out of the scope of this chapter, it is useful to state the environmental benefits from the application of telematics. The efficient use of a transportation fleet leads to noticeable reductions in fuel consumption and greenhouse gas emissions due to an increase in the trucks’ load factors and a consequent reduction in kilometres driven. In their qualitative survey, Baumgertner et al. (2008) found that major telematics services like combination of automatic routing systems and GPS, semi-automated route optimisation, monitoring of loading space utilisation and comparison between planned and actual trips are all beneficial

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TRUCK

Database

MDT

Tc

baseStation

commSW

appSW

Ta

Tb mComGateway

enterpriseGateway

ISP

inhouseUser

Internet externalUser

Legend Query Vehicle communication Event announcement LIS: Logistics Information System Database: LIS database MDT: Mobile Data Terminal ISP: Internet Service Provider Ta: Time required for a message to travel from MDT back to LIS Database Tb: Processing time for LIS user service request Tc: Application event announcement time mCommGateway: network gateway of mobile communication operator enterpriseGateway: enterprise Internet gateway Figure 6.3 RTFMS architecture and information flow (adapted from See, 2007).

for the reduction of greenhouse gas emissions. In the same context, Lee et al. (2008) designed a real-time GPS-based vehicle control system to alter the control of the engine, aiming to reduce fuel consumption and greenhouse gas emissions. Examining the application of GPS in commercial bus routes, Hickman (2004) states that GPS has direct impacts on air quality due to reduction in pollutant emissions and an indirect impact due to changes in passengers’ travelling habits as well.

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Application service provider

Mobile network

Ground station

TRUCK

99

Common transportation information portal (e.g, traffic, weather conditions)

Location server (CMR, map database)

Vehicle data portal User monitoring

WWW

Carrier, shipper, fleet owner, customer etc. Stakeholder Shipper

Carrier

Customer

Forwarder

Recipient

Vehicle owner

Freight No special reqts. Dangerous Perishable

Continuous surveillance (e.g. medicine, medical, etc.)

Cold chain Positioning Safety Area restrictions Fleet grouping

Tachograph operations

Sensoring Fuel consumption

Speed Stops

Driving: gas, acceleration, braking

Idle Door / Window opening

Temperature Humidity

Figure 6.4 Typical architecture of a telematics application.

6.4

INVESTING IN VALUE OF INFORMATION

Because of the rapid and global diffusion of ICT and related devices, the costs involved decreased very quickly, making their operation affordable for almost any supply-chain member. More than a decade ago, Anderson et al. (1996) performed a cost–benefit analysis of the use of transport telematics by European small and medium-sized enterprises and concluded that: … we would argue that, operationally, such technology can bring benefits to the road freight transport sector. Without question, satcom equipment is a high-cost technology. As a result, payback periods are only just considered acceptable by road freight operators. However, given

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that investment and exploitation costs are now some 15% lower than they were three years ago, it appears the payback periods would be more attractive.

Since then, dramatic evolution of technology and increased adoption by companies has considerably reduced the fixed and variable costs, while the range and quality of services has become even more efficient. Consequently, telematics services are currently available and affordable for almost any type of company; either an individual carrier or a large thirdparty logistics service provider. In a typical logistics system a number of stakeholders can benefit from the use of telematics systems. In the following paragraphs the benefits for two core stakeholders are presented: the carrier (owner of the fleet) and the shipper (owner of the freight transported). The value gained by carriers is twofold. Firstly, by analysing recorded historical data, a carrier is able to adjust route schedules, fleet size and loading, making vehicle routes more efficient and cost-effective by significantly reducing fuel and labour costs. Secondly, the centralised real-time monitoring of a carrier’s fleet generates numerous benefits. In his early but well-timed research, Hamilton (1993) discovered core monetary and non-monetary benefits that reduce operational costs. The monetary benefits included additional revenue (from capacity utilisation based on understanding of the actual vehicle location), savings in dispatch labour, reduced mileage costs for drivers and reduced telephony costs). In addition, continuous monitoring and protection of transported goods against risk may reduce insurance premiums. The non-monetary benefits included improved communication with and between truck drivers, reduced driver downtime through minimisation of communication calls, improved customer service, increased driver productivity and the additional income generated by using telematics as a marketing and sales tool. From a strategic business point of view telematics may act as a component for safeguarding a company’s reputation. Shippers, meanwhile, are able to use information from the carrier’s telematics system to continuously monitor the state and location of the goods, and to estimate, accurately and with confidence, the spatial and temporal characteristics of the freight, such as loading, unloading, waiting and transit times, temperature, etc. As a result, information provided by telematics systems may add value to shippers by reducing operational costs through better and more accurate planning. Nevertheless, the penetration of telematics systems is not high yet and varies globally. Besides differences in economies, the most important reason is that potential industrial users are not able to determine the infrastructure and the combination of stand-alone systems and applications they need. When a number of IT providers realised this weakness, they began to invest in such technologies on a large scale, aiming to offer telematics services as outsourcers. In their extensive research Zeimpekis and Giaglis (2006) characterised the most important factors that discourage companies from the adoption of telematics systems: investment costs, unclear returns on investment, attitudes to change management, running costs, integration and interfacing with existing information systems, staff training, labour acceptance, lack of confidence in standards and difficulties in selection of telematics service suppliers. Obviously the acquisition and operation cost of telematics services should be balanced against potential benefits arising from the information. As real-time monitoring entails high communication costs, an effective way to reduce operation costs but retain an operationally effective information service level is to transmit telematics information on a per request or per alarm/event basis. In the first case, data are transmitted when a user in a control station submits a request, while in the second, data are transmitted whenever a measured value diverges from a predefined value (e.g. travel area, goods temperature).

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Of course, the depth of use depends strongly on the size of the company and varies according to product and fleet type. For example, companies that distribute chilled or frozen agrifood products focus mainly on vehicle tracking and cold-chain operation surveillance. On the other hand, international forwarders focus mainly on guidance tools that help drivers to reach customers’ addresses.

6.5

DISTRIBUTION OF AGRIFOOD PRODUCTS: CURRENT STATUS AND NEEDS

Scientific research into the formation and operation of supply chains for agrifood products is relatively limited. Until 2001, only 123 peer-reviewed scientific papers had been published globally (Cunningham, 2001), while the first mention of supply-chain management in agrifood products was in 1987. The distribution of agrifood products requires the formation and operation of advanced logistical systems, with high complexity arising from special product-related requirements. These systems have been described in detail by van Beek et al. (1993). A coherent analysis of the complexity of agrifood supply chains and possible improvements from the application of ICT has been presented by Fritz and Hausen (2009) through an extended case study of the movement of a crop from end to end of the supply chain. A summary of special requirements and recent trends for the distribution of agrifood products is as follows: (i) Usually the production and distribution flow of the products must be continuous from the producer/manufacturer to a significantly large, complex and geographically dispersed network of sales points, ranging from large and small supermarkets and outlets to the end customer’s door through a series of multiple tiers and supply-chain functions. (ii) Elimination of geographical and trading barriers enables food product manufacturers, wholesalers and retailers to seek suppliers in new geographically dispersed markets, resulting in the expansion of the length and number of nodes of transportation routes. (iii) For some categories of product, demand is highly seasonal. The planning and scheduling processes of the supply chain become very complex, requiring support from particular IT tools (like decision support systems), engaging models and methods from scientific areas like operational research. (iv) The range of agrifood products is growing constantly, while the stock levels in each tier of the supply chain needs to be kept as low as possible, ideally only on the trucks and on the display shelves at the sales points. To achieve this, companies apply modern logistics methodologies (e.g. continuous replenishment and just-in-time) that substantially increase the number and frequency of transport routes on a weekly or even daily basis. Due to high product differentiation, the overall control of the supply chain becomes extremely complex and in some cases unpredictable. (v) Although the quality of raw materials used for the delivery of finished products varies, the final product must still comply with strict specifications. This is very important, especially when products are more or less perishable (which is the typical case). (vi) The quality of materials throughout the supply chain is strongly influenced by logistical and environmental parameters, such as transportation trip duration, temperature, humidity, exposure to light, atmospheric condition, etc. Such factors may cause ripening, weight loss, softening, colour and texture changes, physical degradation and

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(vii)

(viii)

(ix)

(x)

(xi)

(xii)

(xiii)

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bruising, and attack by rot and moulds. As a result they affect negatively the freshness, desirability and marketability (and of course the safety) of the food product (Jedermann et al., 2009). Transported goods must be protected and handled under conditions that ensure that the value of these parameters remains between acceptable ranges. For example, the truck’s internal temperature for transportation of deep-frozen meat should be between –20 and –30°C, while the temperature for chilled products should be maintained at 0°C. Such requirements become indispensable when the company wishes to conform to standards (e.g. ISO) and control processes (e.g. HACCP). To safeguard quality standards a number of quantitative characteristics must be measured during the production and distribution of agrifood products. Recently many countries and organisations have developed regulations requiring full traceability in all stages of the food supply chain, for example European Union Regulation No 178/2002 (EC, 2002). Although packaging is designed to protect the products, sometimes it is inconvenient for physical handling due to processing (packing, unpacking, bundling, mechanical processing, etc.) and physical characteristics (fluidity, appearance, colour, etc.). Linkages and complementarities between agrifood products exist, resulting in bundles of transported goods with the degree of participation in the bundle requiring coordinated operations, planning and scheduling. On the other hand, transportation of some agrifood products may require different climate conditions or different requirements for adjacency or closeness, making compartmentalisation of a truck inevitable. Without compartmentalisation, transportation costs increase due to the use of multiple trucks (usually with non-optimum capacity utilisation). The downstream supply chain is extended and reaches the point of consumption (kiosks, restaurants, etc.) through a complex network of various modes of transportation, generating demanding requirements for customer service and product quality. Additionally, in each stage of the supply chain many types of equipment are used, ranging from manual handling to automatic guided vehicles and heavy forklift trucks and stacker cranes. The cost of distribution is, in most cases, very high, sometimes exceeding 300% of the cost of the raw materials, so the design and operation of the agrifood supply chain should focus on the rationalising of relevant costs. New distribution channels are continuously being created, based on traditional remoteordering practices (e.g. catalogues) or the recently fast-growing electronic retailing practices, especially those for fresh and bio-products, which require rapid delivery of products to the consumer’s door, making express logistics systems even more demanding. Home delivery operations are an emerging distribution channel, especially for grocery products. These require trucks/vans of small capacity (usually eight or nine customer orders per truck) in order to distribute orders in a timely manner (intraday or next-day with strict time windows). This results in the reduction on the number of trips and the number of kilometres per vehicle, while the number of required trucks increases. Alternative traditional channels (like vending machines and van sales by the producers) are still present, increasing even further the number of points of sale and the complexity of distribution operations. The general market trend for quick-response logistics strongly affects the food supply chain. This trend generates strong demand for frequent delivery of small shipments. This need then requires the possession (or lease) and management of large fleets of small-capacity vehicles (usually vans) for small shipments, instead of large trucks and bulk shipment (of pallets).

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103

Agrifood product categories.

Agrifood product categories

Examples

Deep-frozen Frozen Fresh Chilled Beverages

Fish, meat Ice-cream Meat, fruit, vegetables Dairy Refreshements, beer, wine

Adapted from van Beek et al., 1993.

The major categories of agrifood products are shown in Table 6.5 (van Beek et al., 1993). The common denominator in these categories is that all of them relate more or less directly to the fact that agrifood products are perishable. Consequently each of these categories involves a bundle of different degrees of special characteristics and requirements for the storage and distribution layers of the logistics chain as previously described.

6.6

THE USE OF TELEMATICS IN DISTRIBUTION OF AGRIFOOD PRODUCTS

While agrifood product manufacturers are able to reach the desired product quality standards quite easily, when the problem reaches the distributor, who is responsible for maintaining this quality at some strictly defined level until the point of sale or consumption, a number of inefficiencies appear. The use of telematics is crucial for the operation of the agrifood supply chain, mainly because of the large number of autonomous participants (producers, manufacturers, distributors and point of sales) and because high quality standards are required. To this extent the present chapter will focus on the physical distribution part of the supply chain and specifically on the application of telematics technologies to it. Fifteen years ago van Beek et al. (1993) claimed that application of telematics in agrifood supply chains ‘allows improvement of the competitive edge of enterprises by increasing reach and/or flexibility’. They also described three core applications: (i) Data acquisition and processing: upstream transmission of collected data used for improved planning (inventory replenishment, shipment redirection, etc.) and downstream transmission of information related to product conditions (quality life, required conditions, recommendations and peculiarities). (ii) Inventory management: ability to better manage inventory, applying not only FIFO (first-in-first-out), but also automatically controlled FEFO (first-expired-first-out) inventory policies, based on a product’s remaining quality life. (iii) Monitoring of critical product conditions through the application of various sensors and further processing of the raw data. These telematics applications are usually defined as ‘telemetric supervision’ (Jedermann et al., 2006), and offer real-time tracking of predefined conditions (e.g. door opening), measurement (e.g. temperature and relative humidity of goods or loading area) and immediate notification of problems to freight planners and truck drivers through SMS and Internet communications. In most

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Reason for delay %

Schedule deviation %

%, Collection point problem, 9

%, Equipment breakdown, 2 %, Lack of driver ,1

%, Unscheduled delay, 29

%, No delay, 71

%, Own company actions,16 %, Unknown, 16

%, Traffic congestion, 31

%, Delivery point problem, 25

Figure 6.5 Reasons for schedule deviation in food supply chain (adapted from McKinnon and Ge, 2003).

cases, raw data are collected through the use of sensors appropriately located in the loading area of the truck. The raw data collected are transferred to an information system for further processing. In a typical application, raw data are transferred to the information system in batch form after the arrival of the truck at the control station. In the most advanced applications raw data are periodically transmitted to the control station over heterogeneous communication networks, such as mobile communication networks, in the form of an SMS message. Special technologies have been developed to monitor the state of the transported goods instead of the conditions of the loading area. An example is the SmartTrace technology (http: //www.smart-trace.com), which is based on the use of smart tags in the shape of a credit card, directly attached to each product’s packaging (box or pallet) and measuring its temperature during the trip. The collected data are then continuously transmitted to a dedicated server (SmartTrace server) and can be retrieved by consignment owners via the internet. The European Union published Regulation 178/2002 (EC, 2002). This regulation established the European Food Safety Authority and defined the general principles and requirements of food law and procedures in matters of food safety that would apply at all levels of the food supply chain. Importantly, Article 18 of this regulation focuses on the full traceability of agrifood products at all stages of their production, processing and distribution. The applications and advances described above can remedy these special requirements related to traceability. Typically, an agrifood distribution supply chain extends to the whole downstream chain: from raw material producer to the consumer. The major problem a planner faces is the performance variations occurring in different tiers of the supply chain due to unexpected incidents that are usually amplified in the subsequent downstream tiers. In their research, McKinnon and Ge (2003) estimated that delays occur in 30% of trips and studied the major causes (Figure 6.5).

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Application of telematics technology may enhance the problem-solving capabilities of these businesses, reduce significantly the percentage of these delays and consequently improve the performance of the supply chain as follows: ●

●

●

●

●

Problems in delivery and collection point: the planner/dispatcher is notified about problems in real time and gives proper instructions to truck drivers. Traffic congestion: integrated applications of GPS and telematics systems use real-time traffic data and offer guidance in avoiding congested roads via on-board terminals. Unknown causes: benefits from the use of telematics may be twofold. Firstly, telematics systems may make these causes clear. Secondly, they offer capabilities for collection, storage and analysis of statistical data that can be useful for improvement actions. Equipment breakdown: telematics systems not only detect such events in a short time, but also they are able to locate nearest fleet trucks. With this information available the dispatcher is able to reassign routes to nearby or ancillary trucks. Own-company actions: this is intentionally created slack – a buffer time to respond to the deviations described above, although increasing operational costs at the same time. It is obvious that the partial improvements attained from the application of telematics systems, as described above, may result in the elimination of this buffer time.

A endogenous shortcoming of GPS systems is that they cannot automatically record/provide details at an item level. Li et al. (2006) determine that this type of information may be collected through integration between identification systems and GPS technologies and they describe a radio frequency identification (RFID) enabled dynamic route-planning system applyied in a three-level supply chain. This aims to minimise value loss of products due to perishability, and maximise profits. More recently, Ruiz-Garzia et al. (2010) described an ICT infrastructure to enable crosslinking between different sources of information (including telematics) in a food supply chain enabling product tracing.

6.7

POTENTIAL FOR ADVANCED AND VALUE-ADDING APPLICATIONS

The integration between telematics and other information and communication technologies creates the potential for the development of a variety of important services. As a conclusion, this chapter provides a short description of three emerging applications for fleet planning and operations, which combine telematics services and other technologies to improve efficiency and safety. Finally, it describes a value-added application that incorporates telematics into a mobile marketplace to allow dynamic yield management and effective pricing of freight transport services.

6.7.1

Vehicle routing and monitoring

Many years ago, Eibl et al. (1994) described the need for vehicle routing and scheduling software for the cost-effective management of truck fleets. They also described the application of such software in the brewing industry, which faced a number of geographical and time constraints. Their study analysed an interesting software acquisition process (decision related to either ‘make’ or ‘buy’), that is still applicable in today’s companies. Tarantilis and

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Kiranoudis (2001) underlined the importance of the time between loading and delivery of food products and developed a specialised routing algorithm aiming to optimise distribution schedules for milk products. Later, Prindezis et al. (2003) proposed an e-business application operated by an application service provider for use by the stakeholders of a central food market. This would enable web-based routing of a food product distribution fleet, offering the related distribution companies vehicle routing services on a daily basis at considerably lower costs. A rather challenging issue for such applications is the integration with telematics services, in order to provide real-time information and controlling opportunities during the evolution of the planned routes. In this context Giaglis et al. (2004) proposed an architecture for a real-time mobile decision support system, while Zeimpekis et al. (2007) proposed a detailed design framework for a vehicle management system that supports intelligent re-routing.

6.7.2

Safety

Recently, Jedermann et al. (2009) proposed an application of RFID technology to capture temperature conditions in truck compartments (instead of transported items) during thetransportation of chilled products. An obvious shortcoming of this methodology is that the temperature report is not real time; it is developed and analysed only after the arrival of the truck in a facility. Integration of the proposed architecture and telematics may potentially provide additional value through the timely provision of such reports while the products are still on-the-move.

6.7.3

Value-added applications

In addition to fleet monitoring and reporting, telematics and wireless networks can be combined to provide integrated value-added applications. Zeimpekis et al. (2003) proposed a taxonomy framework of positioning technologies, based on the criterion of location accuracy, for various business-to-business (B2B) and B2C applications. Auctioning over wireless networks constitutes an attractive emerging class of mCommerce application. It is a procurement negotiation tool and involves the announcement and execution of geographically focused auctions. Various combinations of heterogeneous communication services like internet, mobile and GPS can be applied to form value-added applications, which are usually called locationbased services (LBS). Emiris et al. (2007) demonstrated the coupling of LBS and mCommerce in auction environments to create an m-auction environment for use in logistics-related services. In particular, they examined the case of auctions where several bidders compete to win a freight contract by offering a lower price. They designed an LBS system that was used in conjunction with an appropriate database to pre-select potential bidders who fulfilled a set of criteria, such as appropriate equipment and proximity to the pick-up point. An mCommerce environment was used as the information exchange platform between the auctioneer and potential bidders. Emiris and Marentakis (2009) also examined a location-sensitive, reverse, mAuction application in the freight transport market. Here, potential suppliers (carriers) were able to place bids for less-than-truckload shipments while on the move, aiming to gain from economies of scope (economies achieved from geographical continuity and closeness of freight transportation trips). Given that participation via internet or mobile device is inexpensive and depends only on wireless communication, the telematics-based marketplace is accessible to carriers of almost any size, with numerous benefits:

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cost-effective accessibility to small carriers; reduction of empty miles (deadheading) and better capacity utilisation; generation of collaboration or subcontracting opportunities, especially for individual carriers, to offer adjacent long-haul services independently of their license, or to increase their capacity to undertake large shipments.

REFERENCES Anderson, S., Jorna, R.A.M., Verweij, C.A. (1996) Satellite communication in road freight operations: the METAFORA experience. International Journal of Physical Distribution & Logistics Management; 26(1): 49–61. Baumgartner, M., Leonardi, J., Krusch, O. (2008) Improving computerized routing and scheduling and vehicle telematics: A qualitative survey. Transportation Research Part D; 13: 377–82. Crowley, J. (1998) Virtual logistics: transport in the marketspace. International Journal of Physical Distribution & Logistics Management; 28(7): 547–74. Cunningham, D. (2001) The distribution and extend of agrifood chain management research in the public domain. Supply Chain Management: An International Journal; 6(5): 212–15. EC (2002) European Commission Regulation (EC) No 178/2002 laying down the general principles and requirements of food law, establishing the European Food Safety Authority and laying down procedures in matters of food safety. 28 January 2002. Eibl, P., Mackenzie, R., Kidner, D.B. (1994) Vehicle routing and scheduling in the brewing industry: A case study. International Journal of Physical Distribution & Logistics Management; 24(6): 27–37. Emiris, D., Marentakis, C.A. (2009) The expansion of e-marketplace to m-marketplace by integrating mobility and auctions in a location-sensitive environment: application in procurement of logistics services. In: Kotsopoulos, K. and Ioannou, K. (eds), Handbook of Research on Heterogeneous Next Generation Networking: Innovations and Platforms. IGI Global. Emiris, D., Marentakis, C.A., Laimos, P.P. (2007) Towards an integrated LBS-enabled, mobile auctions marketplace for logistics services. In: 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC’07), 3–7 September 2007, Athens, pp. 1–5. Fritz, M., Hausen, T. (2009) Electronic supply network coordination in agrifood networks: Barriers, potentials, and path dependencies. International Journal of Production Economics; 121: 441–53. Garcia-Ortiz, A., Amin, S.M., Wootton, J.R. (1995) Intelligent transportation systems – enabling technologies. Mathematical Computer Modelling; 22: 11–81. Giaglis, G., Minis, I., Tatarakis, A., Zeimpekis, V. (2004) Minimizing logistics risk through real-time vehicle routing and mobile technologies: research to-date and future trends. International Journal of Physical Distribution and Logistics Management; 34(9): 749–64. Giannopoulos, G. (2004) The application of information and communication technologies in transport. European Journal of Operational Research; 152: 302–20. Goel, A. (2007) Telematics. In: Goel, A. (ed,), Fleet Telematics – Real-time Management and Planning of Commercial Vehicle Operations. Springer, New York. Hamilton, J. (1993) Wireless communication systems: A satellite-based communications approach for competitive advantage in logistic and transportation support services. Computers in Industry; 21: 273–78. Hickman, M. (2004) Bus automatic vehicle location (AVL) systems. In: Gillen, D., Levinson, D. (eds), Assessing the Benefits and Costs of ITS. Springer US, pp. 59–88. Jedermann, R., Schouten, R., Sklorz, A., Lang, W., Kooten, O.V. (2006) Linking keeping quality models and sensor systems to an autonomous transport supervision system. In: Proceedings of the 2nd International Workshop on Cold Chain Management, 8–9 May 2006, University of Bonn, pp. 3–18. Jedermann, R.., Ruiz-Garcia, L., Lang, W. (2009) Spatial temperature profiling by semi-passive RFID loggers for perishable food transportation. Computers and Electronics in Agriculture; 65: 145–54. Lee, S., Walters, S.D., Howlett, R.J. (2008) Intelligent GPS-based vehicle control for improved fuel consumption and reduced emissions. In: Anonymous (ed.), Knowledge-based Intelligent Information and Engineering Systems. Springer, Berlin. Li, D., Kehoe, D., Drake, P. (2006) Dynamic planning with a wireless product identification technology in food supply chains. International Journal of Advanced Manufacturing Technologies; 30: 938–44.

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McKinnon, A., Ge, Y. (2003) Analysis of transport efficiency in the UK food supply chain. Logistics Research Centre, Heriot-Watt University, Edinburgh. Mintsis, G., Basbas, S., Papaioannou, P., Taxiltaris, C., Tziavos, I.N. (2004) Application of GPS technology in the land transportation system. European Journal of Operational Research; 152: 399–409. Prindezis, N., Kiranoudis, C.T., Marinos-Kouris, D. (2003) A business-to-business fleet management service provider for central food market enterprises. Journal of Food Engineering; 60: 203–10. Richton, B., Vannucci, G., Wilkus, S. (2002) Assisted GPS for wireless phone location – technology and standards. In: Tekinay, S. (ed.). Next Generation Wireless Networks: Springer, The Netherlands. Roy, J. (2001) Recent trends in logistics and the need for real-time decision tools in the trucking industry. In: 34th Hawaii International Conference on System Sciences 2001. IEEE. Ruiz-Garcia, L., Steinberger, G., Rothmund, M. (2010) A model and prototype implementation for tracking and tracing agricultural batch products along the food chain. Food Control; 21: 112–21. See, W. (2007) Wireless technologies for logistic distribution process. Journal of Manufacturing Technology Management; 18: 876–88. Tarantilis, C., Kiranoudis, C.T. (2001) A meta-heurestic algorithm for the efficient distribution of perishable foods. Journal of Food Engineering; 50: 1–9. Theiss, A., Yen, D.C., Ku, C.Y. (2005) Global postitioning systems: an analysis of applications, current development and future implementations. Computer Standards & Interfaces; 27: 89–100. Transport Energy (2003) Telematics Guide; Good Practice Guide 341, Department for Transport. Available at: http://www.dft.gov.uk. U-blox AG (2007) Essentials of Satellite Navigation. Available from http://www.u-blox.com; GPS-X02007C. van Beek, P., Koelemeijer, K., van Zuilichem, D.J., Reinders, M.P., Meffert, H.F.T. (1993) Transport logistics of food. In: Macrae, R., Robinson, R.K. (eds). Encyclopedia of Food Science, Food Technology and Nutrition. Academic Press, London. Vossiek, M., Wiebking, L., Gulden, P., Wieghardt, J., Hoffmann, C. (2003) Wireless local positioning – concepts, solutions, applications. In: Radio and Wireless Conference (RAWCON ‘03), Boston, 10–13 August 2003. Zeimpekis, V., Giaglis, G.M. (2006) Urban dynamic real-time distribution services. Journal of Enterprise Information Management; 19: 367–88. Zeimpekis, V., Giaglis, G.M., Lekakos, G. (2003) Towards a taxonomy of indoor and outdoor positioning techniques for mobile location-based applications. Journal of ACM, SIGecom Exchanges; 3(4): 19–27. Zeimpekis, V., Tatarakis, A., Giaglis, G.M., Minis, I. (2007) Towards a dynamic real-time vehicle management system for urban distribution. International Journal of Integrated Supply Management; 3(3): 228–43.

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7

RFID: An Emerging Paradigm for the Agrifood Supply Chain

Louis A. Lefebvre, Linda Castro and Élisabeth Lefebvre

7.1

INTRODUCTION

Radio frequency identification (RFID) technology has been recognized as “one of the ten greatest contributory technologies of the 21st century” and “the next wave of the IT revolution”, mainly due to its mobility, organizational, and technological capabilities (Chao et al., 2007; Tzeng et al., 2007). RFID has the potential to transform business processes and promote new levels of collaboration among supply-chain players through: ● ● ●

the development of new business models; the redesign of existing intra- and inter-organizational business processes; the elimination of non-value-added processes.

RFID tags can provide a unique identity to items, products, or livestock, store data, display pertinent information, and, more importantly, trigger “intelligent business processes”, facilitating the incorporation of “dispersed intelligence applications in our day-to-day life” (McFarlane, 2002; Wong et al., 2002; Zaharudin et al., 2002; Lefebvre et al., 2005; Fosso Wamba et al., 2007; Corchado et al., 2008). The British Air Force was a pioneer in adopting RFID technology to identify friendly aircraft during World War II. Since then, a few discreet applications were implemented in the 1970s for tracking animals, and in the 1980s for automatic toll collection (Landt, 2001). RFID has also been used for other niche applications, such as library access and antitheft systems. Nevertheless, RFID attained considerable momentum when industry leaders such as Wal-Mart, Metro Group, and the US Department of Defense required their major suppliers to apply RFID tags to all shipments (Li et al., 2006). As noted by Heinrich (2005), RFID is expected to be one of the fastest developing technologies in the next generation of business intelligence applications. Indeed, the management and business applications markets for RFID technology have grown steadily in recent years due mainly to recent technological developments, falling cost of infrastructure, initiatives to establish standards, and satisfactory results from pilots (Castro and Fosso Wamba, 2007; Leimeister et al., 2007). According to research reports by IDTechEx, the worldwide market for RFID, including hardware, software, and services, will jump from US$5.29 billion at the end of 2008 to over US$26.88 billion in 2017 (Das and Harrop, 2007, 2008). Intelligent Agrifood Chains and Networks, First Edition. Edited by Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis. © 2011 by Blackwell Publishing Ltd. Published 2011 by Blackwell Publishing Ltd.

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The retail industry, which is recognized as a key driver of RFID adoption (Poirier and McCollum, 2006), has led numerous projects to evaluate the potential of RFID technology for improving operational efficiency and enhancing supply chain visibility and asset management. Although current academic research and industry deployments are directed at this industry, some niche market segments are rapidly rising to prominence, including healthcare, and livestock and food traceability (Ericson, 2004; Das and Harrop, 2008). In recent years, increased concerns regarding bioterrorism threats, food recalls, and food counterfeiting, as well as stringent government legislation about global food traceability have pushed the adoption of RFID technology in an attempt to improve food safety and control end-toend in the agrifood supply chain (Harrop and Napier, 2006; Attaran, 2007). The growing complexity of the agrifood industry has driven stakeholders to adopt more effective solutions for ensuring higher levels of food safety and quality and reacting to global challenges (Harrop and Napier, 2006). In an attempt to surmount these challenges, agrifood organizations are shifting towards the adoption of automatic identification and data capture (AIDC) technologies. In particular, there is a great deal of attention given to investigating the capabilities of RFID to leverage food safety and control, and to gain a competitive advantage. RFID usage for animals, food, and farming in the agrifood chain is escalating, and is projected to become the largest area of RFID application (IDTechEx, 2006). A recent survey conducted by the European Commission (2005) in more than 5000 enterprises from ten different industries in seven EU member states revealed that RFID has a “substantial and growing importance in the food industry”. By 2006, several hundreds of millions of RFID tags were applied to food products and more than 70 million tags to livestock, a trend that is projected to continue rising in coming years. IDTechEx forecasts that by 2015 about 900 billion food items and 824 million heads of livestock could be RFID-enabled (Harrop and Napier, 2006; IDTechEx, 2006). This chapter, which focuses on RFID and its potential, is organized as follows. It starts with a review of RFID technology, including a brief description of RFID system components and a discussion of some barriers to its adoption (Section 7.1). Section 7.2 investigates RFID potential at all levels of the agrifood supply chain. Sections 7.3 to 7.8 analyse the potential of this technology for different core business processes in the agrifood supply chain, namely traceability processes, quality-control processes, warehouse and distribution processes, asset-management processes, and point-of-sale management processes. Finally, the chapter concludes with the examination of foreseeable trends towards an increasingly intelligent agrifood supply chain.

7.2 7.2.1

RFID TECHNOLOGY Overview of RFID technology

RFID is considered to be a wireless AIDC technology that uses radio signals to automatically and precisely identify, track, and trace objects, items, individuals, or animals (Fosso Wamba et al., 2006; Corchado et al., 2008). AIDC technologies include barcoding, optical recognition, biometrics, card technology, touch or contact memory technology, and RFID technology. Currently, the main alternative in use for tracing and tracking objects is barcoding, which relies on optical laser or imaging technology to scan and read a printed label. In comparison to barcoding systems, RFID technology offers real advantages (Table 7.1),

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RFID: An Emerging Paradigm for the Agrifood Supply Chain Table 7.1

111

Key features differentiating RFID from barcoding.

Barcode features

RFID tags

Require line of sight Scan one item at the time Read-only capabilities Depend on external data store Inexpensive Widely used Existing standards Provide license plate information Restricted read range Cannot be read in harsh environments

Line of sight not required Multiple items at the time Digital, read-write capable Can store data/trigger access to external data More expensive Emerging Standards developing Can store relevant data Broad read range Can operate in harsh environments

Enterprise applications Enterprise applications business partners

WMS Desktop

MES

RFID Tag

ERP

Others

WMS

LAN

RFID Tag

ERP Reader

Middleware

Server

WiFi

Firewall

Internet Others

Tablet PC, PDA etc

Figure 7.1 RFID system.

including its capability to read multiple tags simultaneously, provide unique item-level identification, store data, and trigger access to external data. An RFID system (Want, 2004) is fundamentally composed of three major layers: (i) a tag or transponder, containing integrated circuits and a antenna, is embedded in or attached to a physical object; (ii) a reader called the interrogator and its antennas, which communicate with the transponder without requiring line of sight; (iii) host server equipment comprising a middleware, which manages the RFID equipment (e.g. readers), filters data, and transmits information to the different enterprise applications. Figure 7.1 depicts an RFID system configuration. 7.2.1.1

RFID tags

The RFID tag’s antenna enables the chip to respond to the signal transmitted from the RFID reader. RFID tags can stock unique product information (e.g. product ID, serial number, expiration date), which can be used through the lifecycle of RFID-enabled products.

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Memory, design, power source, carrier frequency, communication mode, read range, and data storage capacity are among the features of RFID tags. Based on their memory capabilities, tags may be read only, write once/read many times, or have read/write capabilities. Tags can work at low frequencies, high frequencies, and ultra high frequencies and according to their power source tags may be passive (no power source), semi-passive (battery-assisted), or active (self-powered). Active tags use a battery to obtain their power and have a larger communication range, higher data-transmission rates, and broader data-storage capacity than passive tags (Asif and Mandviwalla, 2005; Castro and Fosso Wamba, 2007). Passive tags are more widely used for tagging goods since they are less expensive than active tags, with an estimated cost ranging from US$0.05 to US$0.25 per passive tag compared with more than US$20 and up per active tag (Attaran, 2007; Curtin et al., 2007). The largest segment of the RFID market is RFID labels and active tags, with a projected 2.16 billion tags to be sold in 2008, representing sales of US$2.26 billion (Das and Harrop, 2008). 7.2.1.2

RFID readers

RFID readers are electronic devices that emit and receive radio signals through the antennas coupled to them, remotely identifying the presence of intelligent objects and capturing all data stored. Readers are responsible for the information flow between the tags and the host system via the RFID middleware. Besides antennas, RFID readers are composed of three other subsystems: (i) the reader API, which permits the capture of RFID tag events; (ii) the communications component that deals with networking functions; (iii) the event management module that manages the data captured (Glover and Bhatt, 2006). There are two main types of RFID readers: (i) (ii)

fixed readers; mobile readers.

Fixed readers are usually portal-based (e.g. mounted to walls, portals, or conveyor belts) and therefore only allow the identification of any tagged item as it passes through the reader’s coverage area. On the other hand, mobile readers can be mounted onto a forklift or used as a handheld device and hence increase flexibility by allowing equipment to be used at different locations in a facility. This leads to a reduction in costs since fewer readers will be required. Mobile readers allow reading of the RFID-enabled item, and send and receive information related to the product and execute transactions in a mobile and wireless manner in real time (Bendavid et al., 2006; Patil et al., 2008). 7.2.1.3

RFID middleware

RFID middleware can be considered as the central nervous system of any RFID system (Sandip, 2005). It is the critical element in the intelligent collection, management, and processing of the information captured by RFID readers. In fact, the RFID middleware filters, processes, and aggregates all the read data, and provides information to the different

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enterprise applications, including the enterprise resource planning (ERP) system, the warehouse management system (WMS), and the manufacturing execution system (MES). Once the middleware has processed the information, the appropriate organizational information systems use this information to trigger several business processes. Additionally, the information can be used to manage, monitor, and control RFID readers’ infrastructure (Liard, 2004; Sandip, 2005). The RFID middleware market covers a representative portion of the total RFID software market and it is forecast to grow significantly in coming years. The RFID middleware global market surpassed US$37 million in 2006, and is anticipated to escalate at a compounded annual growth rate (CAGR) of 58% through to 2011, reaching US$1557.5 million (WinterGreen Research, 2005; VDC Research Group, 2007). 7.2.1.4

Adding intelligence with RFID

The appropriate RFID solution, including hardware and software components, as well as configuration of system components (e.g. suitable tags, tag location, etc.) will greatly depend on the requirements of the application and the specificities of the environment where the RFID implementation will be undertaken. For instance, passive tags are frequently used for high-volume, low-cost products in the retail industry, livestock tracking, airline baggage tracking, and library book tracking. Active tags are better adapted to track high-value products such as medical equipment in the healthcare industry and expensive wines in the food industry. According to some authors, the potential of RFID to enable object-to-object wireless communication is anticipated to introduce intelligent capabilities into organizations, enabling the integration of intelligent value-added applications within the supply chain (Chao et al., 2007; Curtin et al., 2007; Tzeng et al., 2007). RFID holds much promise for closing the gap between the physical and the virtual worlds, thus facilitating coordination of product flow and information flow, since information travels seamlessly with the RFID-enabled product (Want et al., 1999; Leimeister et al., 2007). For instance, global positioning system (GPS) technology or mobile telephony can enable the real-time localization functions of an RFID system, which can then be interconnected to networks and the internet, meaning that objects can be instantaneously identified anywhere in the world, thus allowing the transition towards what is known today as “the Internet of things” (ITU, 2005, p. 2; OECD, 2007).

7.2.2

Current drawbacks to RFID adoption

Regardless of the broad interest in RFID and its demonstrated benefits, there are some limitations restraining its adoption, namely the lack of established standards, the high cost of RFID infrastructure, some technical challenges, and several privacy and legal issues. 7.2.2.1

Lack of global standards

With competing and sometimes incompatible standards, some standardization problems had to be solved. For instance, the electronic product code (EPC) has emerged as the dominant standard to identify each item with a unique serial number (EPCglobal, 2004). The EPC is a standard proposed and developed by the Auto-ID Center, a partnership between universityaffiliated research centers and leading industry partners. The EPC code provides the means

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for unique identification of any object across a supply chain. Hence, once an EPC code is integrated into a RFID tag attached to a physical object, this object turns into a “unique” object worldwide. On the other hand, ISO/IEC standards are divided into a wide number of series: ISO 18000 protocols mainly focus on air interface communications, ISO 15693 defines specifications for identification and vicinity cards, ISO 15961 defines how data should be transferred among components of a RFID system (e.g. tags and readers), ISO 17364–17367 specifies regulations for RFID in the supply chain, and ISO 11784–85 and 14223 deal with animal tagging, as well as transmission protocols (Cooney, 2006; pp. 210–215). According to Cooney (2006, p. 208), putting in place RFID standards could lead to cost reductions and the enhancement of quality and confidence in RFID. 7.2.2.2

Justification of investment

From a management perspective, the complexity of quantitatively assessing the return on investment of an RFID adoption project represents a major area of concern (Reyes and Jaska, 2007). Although in the past few years most RFID adoptions were implemented with a “closed-loop” approach, companies are now moving progressively towards an “openloop” model. Closed-loop applications have mainly been adopted to comply with client mandates, where the majority of suppliers have followed the “slap-and-ship” approach, in which RFID tags are put on products before they leave a warehouse and are sent to retailers. This represents an increased cost for the supplier since it does not exploit the benefits of RFID within their facilities and usually implies the usage of proprietary solutions, thereby increasing the cost of deployment and the raising of compatibility issues among supplychain members (Stroh and Ringbeck, 2004; Jones et al., 2007). Indeed, according to Watson (2005, in Hingley et al., 2007), some of Wal-Mart’s suppliers have spent an average of US$500 000 to conform with the demand to implement RFID-enabled shipments of cases and pallets. Consequently, instead of just complying with a customer mandate, companies must assess the potential of RFID to generate competitive advantages within their internal operations and should also consider the many intangible benefits offered by the technology, such as increased consumer satisfaction (IDTechEx, 2006; Leimeister et al., 2007). Moreover, as the number of industrial adoptions of RFID technology continues to rise, the price will drop and reach more affordable levels, with passive tag prices expected to drop below 1 cent each. 7.2.2.3

Technological challenges

The management of the high volume of data generated by the RFID system (120 to140 signals per second) raises technological issues concerning interoperability and scalability of the system. Other technological challenges include multi-tag collisions, potential interference under certain conditions, and reading-rate reliability. For instance, the presence of metal, moisture, or liquids can generate noise in the electromagnetic field, making it difficult to maintain the transmission (Jones et al., 2004; Gandino et al., 2007). Additionally, severe environmental conditions, such as temperature variability, can also hamper RFID capability. 7.2.2.4

Ethical and legal issues

RFID could further strengthen the rise of a surveillance society (OECD, 2006) and its use raises several ethical and legal concerns about information control and privacy. Consumers

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fear privacy invasion since they feel that they could be tracked once they buy RFID-enabled items. Protection of consumers’ privacy has mainly been an issue in retail applications, where consumer-action groups such as the Electronic Frontier Foundation and the Consumer Against Supermarket Privacy Invasion and Numbering have been active (Federal Trade Commission, 2006; Glover and Bhatt, 2006). A report from the office of the Privacy Commissioner of Canada also highlights the need to ensure that RFID “do not erode informational privacy rights” (Privacy Commissioner of Canada, 2005). Because of this, data security policies have to be examined in order to ensure that customer information is not put at risk. Nevertheless, there are numerous ways to prevent tags tracking once products are sold: ● ● ● ●

“kill” the tags; set up passwords or encryption; implement a cage approach; ensure active-jamming (Boulard, 2005, in Reyes and Jaska, 2007).

Among these, the “kill the tag” approach is the easiest way to promote consumer privacy since it can destroy the tag at the point of sale (Glover and Bhatt, 2006).

7.3 7.3.1

RFID POTENTIAL IN THE AGRIFOOD SUPPLY CHAIN RFID drivers in the agrifood industry

The agrifood industry worldwide is facing a rising number of issues, including increased globalization and competition, greatly segmented food production, increased efficiency in organization and processes, strict requirements on quality assurance, reliability in food provisioning, and consumer trust sustainability, among others (Schiefer, 2004). Adding pressure to an already complex environment, contemporary security threats related to the agrifood chain are becoming a major concern for industry stakeholders. Bioterrorism threats, animal disease outbreaks (e.g. avian flu and mad cow disease), food contamination recalls, and food counterfeiting are encouraging stringent legislation and demands for total traceability in the agrifood supply chain to capture products’ lifecycle history. 7.3.1.1

Government legislation

Governments around the world are increasingly establishing draconian regulation in order to assure the safety of every food product. For instance, the EU has opted for a new approach, involving strict supervision and control and traceability of feed and food “from the farm to the fork” (European Commission, 2004). Since 2005, EU regulation 178/2002 on food safety makes it obligatory for firms that produce and distribute agrifood products to supply information on the products, their origin, and destination, as well as to label food in order to facilitate traceability (European Commission, 2004). In the USA, the Farm Security and Rural Investment Act stipulates country-of-origin labeling for a variety of food products, including perishable agricultural commodities. The US Bioterrorism Act requires lot codes or other similar identification for food products, and the US Homeland Security legislation is demanding unprecedented levels of traceability (Harrop and Napier,

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2006; Bernardi et al., 2007). The US Department of Agriculture commissioned the National Animal Identification System (NAIS), which will use RFID tags to track livestock from birth to slaughterhouse. Information about the 200 million head of livestock in the USA will be stored in a national database (Brewin, 2003). Moreover, in 2003, the European Council of Ministers adopted a law throughout Europe mandating the individual electronic tagging of sheep and goats through the use of RFID. In Canada, electronic tagging has been compulsory since January 2005 and in Australia a mandatory RFID-based National Livestock Identification Scheme has been in place since 2002 (Using RFID, 2004a and 2004b). 7.3.1.2

Consumer safety demands

Consumers are calling for higher quality practice within the food chain, since they are increasingly aware that they have the right to be informed and to select the products they consume based on “transparent information” (Harrop and Napier, 2006). Driven by reports of food contamination and livestock diseases, consumers want to be assured that the food they are giving to their families is not a threat. Consumers are demanding answers to questions such as where the food is coming from, who handles the food along the supply chain, if there is a recall on the product, what the ingredients of the food are, and if the food might contain allergens (Harrop and Napier; 2006).

7.3.1.3

Industry mandates

Mandates from key players in the agrifood industry are also pushing the adoption of RFID. For instance, McDonald’s fast food chain, which spends more than US$14 billion on farm products a year, including buying 1.1 million metric tons of beef, has required complete traceability from suppliers in order to promote consumer safety and keep consumer trust. The Metro group, Wal-Mart, and Tesco have required that an increasing number of their suppliers integrate RFID tags in their shipments.

7.3.2

RFID opportunities in the agrifood supply chain

Food producers, manufacturers, distributors, transporters, retailers, consumers, and regulatory agencies are getting ready to use RFID technology with the objective of increasing food product visibility and quality within their supply chain (chain traceability) and within their facilities (internal traceability). This technology has the potential to allow all supply-chain members to identify, track, trace, and manage each individual product, depending on the desired level of granularity (e.g. item, pallet, case, batch), in a flexible manner and providing information in real time. According to Hayes Weir (2007), item-level tagging of food products could boost food safety and lower costs, since it has the potential to enhance stock management, improve theft controls, and expedite checkout processes at the point of sale. Figure 7.2 outlines a non-exclusive list of 30 or so potential RFID applications in the agrifood supply chain. All these applications appear to be good candidates for adding intelligence into several key processes. These processes can be broadly classified as producttraceability processes, quality-control processes, warehouse and distribution processes, asset-management processes and point-of-sale management processes. Sections 7.4 to 7.8 discuss the RFID potential on these processes.

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Upstream chain tracking • In transit visibility • Inventory management • Environment monitoring • Warehouse management • Mobile asset management • Food quality management • Product recall management

• Food source tracking • Inventory management • Environment monitoring • Animal health monitoring

Producer

Manufacturer

Distributor/Transporter

Retailer

• Food source tracking • W.I.P material tracking • Environment monitoring • Mobile asset management • Food quality management • Product recall management

• Automated payment • Automated-check-out • Smart shopping applications

Consumer

• Smart shelf • Theft prevention • Automated check-out • Inventory management • Environment monitoring • Food quality management • Mobile asset management • Product recall management • Product return management • Dynamic shelf and price management

Downstream chain tracing

Figure 7.2 An overview of potential RFID applications in the agrifood supply chain.

7.4 7.4.1

RFID AND TRACEABILITY PROCESSES IN THE AGRIFOOD SUPPLY CHAIN Tracking and tracing

Tracking and tracing is a core issue at all levels of the extended agrifood supply chain (Figure 7.2). Tracking and tracing is necessary in order to document a product’s history backward or forward in the supply chain, improving business responsiveness and efficiency. Upstream tracking is demanded by government regulation, while downstream tracing is needed to act efficiently in case of product recalls (Thiesse and Michahelles, 2006). Traceability can be defined as “the ability to follow an item, or a group of items, whether animal, plant, food product or ingredient, from one point in the supply chain to another, either backwards or forwards” (Hobbs et al., 2007). The implications of poor food quality procedures have proven to be catastrophic for consumer health and business turnover. Traceability systems have only recently been adopted in the agrifood chain, with many small and medium-sized businesses still relying on paper-based systems to trace product history (Mousavi et al., 2002; Bernardi et al., 2007; Gandino et al., 2007). RFID has been recognized as a key facilitator of supply-chain integrity (Sahin et al., 2002; Kumar and Budin, 2006). RFID technology holds the potential to enable end-to-end traceability in the agrifood supply chain, since it facilitates the unique identification of particular items at any point along it. Bernardi et al. (2007) suggest that operators in the food chain could add any necessary information directly to the tag that is attached to food products, making possible the creation of an ubiquitous database. Such close integration demands new approaches for cooperation between supply-chain members (Piggin and Brandt, 2006). As we narrow down the level of granularity of RFID applications, higher levels of traceability accuracy can be attained, although this implies an increase in management costs as well as in the complexity of data management, due to the large amount of data generated by the system (Kelepouris et al., 2007).

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7.4.2

Food-source tracking and animal-health monitoring

RFID appears particularly suited to livestock, allowing food-source tracking and animalhealth monitoring. Animal traceability at each stage of the chain is of paramount importance for the cattle industry, since it is a core factor in ensuring and maintaining consumer trust. Outbreaks of animal disease, including bovine spongiform encephalitis (BSE), foot and mouth disease, and avian influenza, occur recurrently in different places around the world, adversely impacting the meat market. Incidents of BSE, better known as mad cow disease, in the UK, EU member countries, Canada, and the USA have disrupted the beef industry, leading to bans of beef imports from affected countries and drops in world prices (Hennessy et al., 2004). Most importantly, these incidents have a deep impact on the attitude of consumers toward meat products, since consumption of the affected products could have serious implications for consumer health, with recent studies on food safety revealing that about seven million people are affected by foodborne illnesses every year (Sarig, 2003, in Regattieri et al., 2007). Today’s food chain is becoming global, increasing the likelihood of rapid contamination across borders, therefore the implementation of effective tracing systems – timely systems that uniquely identify and trace animal products back to their origin – is imperative in order to ensure safety and quality across the world’s food-supply chain (Mousavi et al., 2002). RFID technology has been used for many years to identify animals, for tracing and monitoring cattle from birth by inserting a tag into the ear or stomach (e.g. cow, pig, sheep), and for facilitating precise records of animal source, location, history, and health as they pass through the different layers of the supply chain. RFID ear tags are presently the most commonly used form of animal tracking. Most RFID tags used in this industry are based on ISO 15693 or EPC, and operate at low frequency of 134.2 kHz and a high frequency of 13.56 MHz. However, these frequencies represent a challenge because of the limited read range of 1–36″. Increasingly, RFID applications include temperature-sensing tags, which are able to measure an animal’s body temperature for early detection of any symptoms of disease. Digital Angel Corporation has developed the Bio-Thermo passive RFID tag, which incorporates a sensor that makes it possible to measure an animal’s body temperature (http://www. digitalangel.com). Somark Innovations have concluded a field demonstration of their patented Biocompatible Chipless RFID Ink Tattoo animal ID system, which is injected and read beneath the skin of animals (http://www.somarkinnovations.com). Some research has been undertaken into the potential for coupling RFID and DNA technologies to ensure animal traceability from “farm-to-fork”. For instance, in Canada, bovines have been tagged with an RFID tag and a DNA tissue-collection tag in order to follow animals from birth to slaughtering plant (http://www.foodtech-international.com). Moreover, the Kansas Animal Health Department and Kansas State University are applying a system integrating RFID, GPS, and cellular technologies to track cattle as they are loaded onto trucks (Hegeman, 2005). RFID technology can help to spot which products/animals are potentially contaminated in case of animal disease outbreaks, permitting ranchers to increase their profitability and governments to manage animal health issues in a timely manner. Individual and herd information can then be easily transferred between all parties involved in the production and retail of meat products. Information-sharing thus allows the food industry to meet the strict demands of the marketplace. Richmond Meats, a meat processor based in New Zealand, has investigated RFID applications for animal tracking in order to trace food products through processing plants and back to the livestock (iStart, 2004). Brandt Beef, a California beef producer, is using low frequency RFID ear tags and barcode tracking systems to keep track of its cattle, from birth to beef and from retailer back to its origin (Swedberg, 2006). Also, two Thai

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shrimp exporters are using low-frequency RFID tags to trace the food’s origin, processing, and expiry data in case a product recall occurs (O’Connor, 2007). In New Zealand, the supermarket group Progressive Enterprises and meat processing company PPCS are testing RFID to track meat from processing plants to its butcheries (iStart, 2005).

7.5

RFID AND QUALITY CONTROL MANAGEMENT PROCESSES

Some products are hard to handle since they are time-sensitive, with limited shelf-life, and require an efficient supply chain (Salin, 1998; Liu et al., 2008). In these markets, ordering represents a challenging problem, since only a limited amount of safety stock can be held. Effective stock rotation to ensure that oldest products are taken from the storage and shelves first, as determined by their sell-by date is of paramount importance, particularly for retailers (Sahin et al., 2002; Kärkkäinen, 2003; Liu et al., 2008). Spoilage is an important concern affecting the short-shelf-life-product supply chain. It is caused mainly by inventory management issues, such as excess stock and faulty stock rotation. The extent of the problem is remarkable: according to a 2003/2004 survey conducted by The National Supermarket Research Group, perishables are responsible for 56% of total store shrinkage – about US$250 000 per store, of which 46% (US$115 000) is caused by temperature-related incidents. This represents a multibillion problem every year (Di Rubio; 2005). Through integration of RFID tags into perishable food, logistic firms, distributors, and retailers will be able to monitor the state of short-shelf-life products as they move through the supply chain. RFID tags can provide extensive information, such as product history and origin, bills of material, and expected expiry dates. Item-level information can be key for locating a specific item or batch, say for locating spoiled or expired perishables or product from a particular production run in the case of a product safety recall. Retailers can use the information gathered through the RFID system to use dynamic discounting processes to sell the perishable food before it has expired (Pramatari, 2007). Perez-Aloe et al. (2007) report a study in the cheese industry to evaluate the possibility of carrying out individual batch-quality control of cheese using RFID tags. The results show that the RFID-based traceability system improves the monitoring and control of the cheese fabrication process. Regattieri et al. (2007) describe an RFID-based traceability system used by Parmigiano Reggiano, a well-known Italian cheese producer, which permits precise tracing of the cheese throughout the entire chain and facilitates time-efficient recall strategies. Campofrio, a Spanish leader in the meat industry, is using RFID tags for the tracking of cured hams, with the aim of offering the highest quality and security of the final product in the marketplace. The systems will allow access to accurate information about the source of their products, as well as the processes they have gone through.

7.5.1

The cold chain

The cold chain for processed food quality management is a temperature-controlled chain in which temperature-sensitive products must be maintained within a precise temperature range from the time they are produced until the time they are sold to the end-user in order to guarantee their integrity and quality. Temperature-sensitive products represent a major challenge for grocery retail managers, mainly because a breakdown in the cold chain at any point in the supply chain may lead to the exposure of products to abnormal temperatures and

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therefore a change in their chemical characteristics, loss of freshness, quality, and integrity, and so to the jeopardization of food safety (Sellitto et al., 2007). Fruit, vegetables, meat, and dairy products are very sensitive to temperature changes and thus must be handled within the appropriate conditions in order to avoid spoilage and bacteria growth. RFID technology could be combined with other technologies in order to leverage its capabilities. Recent advances in RFID technology involve the introduction of sensor-embedded active RFID tags, which can be used to gather environmental information, such as temperature, humidity, pressure, vibration, etc., and give notice of changes and mishandling during transportation. Furthermore, RFID has the capability to communicate with products, facilitating the automation of data capture and product item visibility. This capability is particularly important for the management of the cold chain, since frozen products must be maintained at the correct temperatures at all times during transportation and warehousing, as well as on the shelf at the point of sale (European Commission, 2005; Liu et al., 2008).

7.5.2

Product recalls

Food recalls are a problem that seriously affect suppliers, distributors, and retailers. The US Food and Drug Administration (FDA) has reported that 1307 processed-food product recalls, for the most part due to failures in goods manufacturing practices, occurred between 1999 and 2003 (Kumar and Budin, 2006). Among the causes for these recalls, the document points to avoidable errors due to ineffective employee training and incorrect packaging / labeling, use of undeclared or unapproved ingredients, and food contamination. For instance, in 2006 fresh spinach vanished from grocery store shelves for 2 weeks due to a recall by the FDA after E. coli-tainted spinach leaves affected hundreds of people, costing this industry US$74 million (Hayes Weier, 2007). According to Zebra Technologies (2004), factors such as size, scope, and expense of a recall depend greatly on the established level of product traceability. An effective traceability system could enable the recall and withdraw only of products produced on the one compromised production line rather than the whole factory (Kumar and Budin, 2006). RFID tags present remarkable opportunities for retailers and manufacturers to deal in a timely and efficient manner with product recall issues (Hingley et al., 2007). Since RFID tags allow tracing of the history of each ingredient in a package of food, prompt information could be made available to agencies in order to avoid the spread of illness and save consumers’ lives (Hayes Weier, 2007). Moreover, RFID can cut down costs associated with recalls, since it provides the capability of identifying the affected food products and thus reduce the amount of products to be discarded, as well as accelerating the time of response (Homs, 2003, in Attaran, 2007). Woods (2005) presents various scenarios for RFID use in a product recall context. For instance, the grocery employees at the retailer store could react to a product recall by going to the RFID-enabled shelf, also called a smart shelf, check whether or not there are any of the recalled lots on the shelf, and react accordingly.

7.6 7.6.1

RFID AND MANUFACTURING PROCESSES Work in progress

According to Zhen-hua et al. (2007), manufacturing is prone to a range of issues, including impurities and additives. RFID has been a recognized facilitator of increased materials visibility within the supply chain (Angeles, 2005). Individual intelligent products and materials

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can be identified and monitored during the diverse food manufacturing processes, with all information embedded in the RFID tag (Li et al., 2006). For instance, United Biscuits has used RFID to monitor food ingredient movement, as well as the mixing and baking processes of biscuits. Benefits reported include: ● ● ● ●

increased information accuracy; improved food product tracking; enhanced plant efficiency; reduced error rates (Angeles, 2005).

7.7 7.7.1

RFID AND WAREHOUSE AND DISTRIBUTION PROCESSES Warehouse processes

RFID suggests numerous solutions to optimize basic warehouse processes, such as reception, put-away, picking, and shipping, by automating almost all information-based processes, decreasing inventory errors, and reducing or eliminating human intervention (Lefebvre et al., 2006). Multiple RFID-enabled products can be read at the same time, hence there is no need for individual scans of pallets or cases (Hingley et al., 2007). RFID can therefore reduce or eliminate problems due to human errors, which are mainly related to product counting and stock control, particularly as regards receiving and picking activities. For instance, RFID permits the elimination of manual and visual verification of each received product, speeding up receiving processes and avoiding bottlenecks at distribution centers, warehouses, and store entrance docks. Additionally, RFID integration into warehouse activities promotes cross-docking business models, where products move from inbound vehicles to outbound vehicles without any need to be stored, thus significantly reducing laborintensive and costly activities such as put-away and picking (Lefebvre et al., 2006). Substantial cost savings could be attained from RFID adoption. For instance, cost savings derived from the adoption of RFID in the put-away process could reach 50% (Capone et al., 2004). Additionally, RFID has the potential to improve temporary storage at the warehouse: since RFID tags do not need line of sight, they can be read remotely and thus RFID-embedded products, cases and pallets do not have to be placed in specific or assigned locations, so promoting the use of virtual put-away spaces (Capone et al., 2004). Moreover, picking is a highly labor-intensive operation, demanding up to 50% of the warehouse labor force; it is also a very capital-intensive operation, accounting for about 65% of the total operating costs of a typical warehouse (Coyle et al., 2003; De Koster et al., 2007). RFID-enabled warehouses could allow the reduction of warehouse picking errors and labor costs by 36% (Capone et al., 2004). Analysts predict that Wal-Mart could save over US$8 billion annually through the use of RFID, by reducing the labor costs of scanning items, out-of-stock items, and item theft, while making improvements in the supply chain (Curtin et al., 2007). During shipping activities, information collected in real time from intelligent cases and pallets may be used to verify the sender’s data and indicate the designated truck. This would ensure that orders were placed in the right vehicle, preventing any discrepancies and misplaced orders (Aberdeen Group, 2006). Given the great potential of RFID for improving warehouse operation, numerous real-life tests have taken place to verify the potential in the agrifood supply chain. Ballantine, one of the largest US fruit suppliers, has used RFID to tag nectarine shipments to Wal-Mart in

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order to gain competitive advantage and to deliver a fresher, more consistent product to consumers, as well as to track raw materials at the warehouse level to improve product inventory and reduce shrinkage (O’Connor, 2005). Publix, a US supermarket chain, have evaluated the potential of integrating the EPC network to improve the distribution of fresh produces as they move from suppliers in California and Florida to one of its distribution centers (Zhen-hua et al., 2007).

7.7.2

Inventory processes

According to Prater et al. (2005) the grocery industry is a chief candidate for RFID adoption since it faces remarkable inventory-level issues. At the retailer, “RFID can enhance the shopping experience by reducing the number of out-of-stock items, ensuring products are on the shelf when consumers want to buy them”, and leading to an increase in consumer satisfaction and loyalty (Intel, 2004a, in Attaran, 2007). Moreover, opportunities for decreasing stock shrinkage through increased inventory accuracy and better control of stock rotation, and for improved replenishment productivity through increased asset visibility are obviously worth evaluating. Krivda (2004, in Attaran, 2007) mentioned that by adopting RFID technology, retailers can: ● ● ●

decrease the costs of receiving, inventory, and shrinkages by 11–18%; diminish the incidence of out-of stock merchandise by 9–14%; reduce logistics delays by up to 5%.

Indeed, research from the University of Arkansas demonstrates that Wal-Mart has been able to diminish stockouts by 16% by tracking RFID-enabled cases of goods arriving from suppliers (Roberti, 2005). As noted by the Chief Information Officer of Wal-Mart, a reduction of 10% of their out-of-stock problems and inventory inaccuracies represents a potential saving for Wal-Mart and its suppliers of about US$250 million each year (IDTechEX, 2007). Additionally, as reported by Kärkkäinen (2003), British retailer Sainsbury’s has gained from introducing RFID to track food transportation crates as they move from suppliers to retailers. Among the many benefits identified by the retailer, there are considerable cost savings from the decrease of stock shrinkage, through increased inventory accuracy and better control of stock rotation, as well as improved replenishment through increased asset visibility.

7.8 7.8.1

RFID AND ASSET MANAGEMENT PROCESSES Mobile asset management

At present, companies are encountering rising concerns regarding asset management, due mainly to the fact that products and materials are not managed individually and information about their location is rather inaccurate (Lampe and Strassner, 2002). Warehouse facilities could handle on a daily basis demands for between thousands and hundreds of thousands of logistics units. Manufacturers, logistics firms, and retailers are looking at asset management applications such as reusable pallets, bins, trays, roll cages, dollies, and container tracking and visibility as well as optimization and utilization. Knowing where logistics assets are located is vital for the efficient operation of manufacturing and distribution companies. Time wasted looking for assets lowers productivity, and consequently affects profitability.

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Good practice in asset management could lead to the isolation of bottle-necks in the retailers’ supply chains, reduction of overstocking or the location of spoiled freight. RFID technology appears to hold much promise with respect to asset management optimization. Experts perceive RFID as the enabling technology that will empower and improve asset management and they believe that RFID is the number one reason for diverse industries having undertaken an RFID implementation (Belkin, 2006). According to a recent report from Aberdeen Group (Belkin, 2006), the main incentive for companies to introduce RFID is the potential of this technology to leverage the performance of their internal operations, including logistics asset management. Additionally, Aberdeen Group (2006) has reported that many companies lose at least 10% of their pallets and shipping containers, a problem that affects operational performance. RFID capabilities could facilitate the automatic identification and location of assets when and where needed, as well as the monitoring of asset condition (Want et al., 1999). Many organizations have thus started exploring the opportunities to introduce this technology in order to ensure the efficient utilization of their mobile logistics assets. Early-adopter Marks & Spencer, a British retailer, is using high-frequency RFID tags at its food division to track 3.5 million reusable plastic trays and dollies. The project has led to some interesting benefits, including a reduction of 83% in read time of RFID-enabled dollies, a decrease of 15% in shrinkage, as well as a reduction in lead time (Li et al., 2006). Moraitis, an Australian tomato grower, is using RFID to tag tomato trays in order to handle the processing of tomatoes as they are being graded (for size and quality), packed, and shipped. This solution will allow the tomato grower to respond instantly to retailer needs, to purchase its inventory via a variable cost structure – related to actual yield after processing – and to redeploy staff efficiently (IBM, 2005). Scottish Courage, a large British brewer, is using low-frequency RFID tags to track nearly 2 million kegs of beer, permitting a reduction in distribution overheads and a decrease of keg losses from 4% to 2% (Li et al., 2006).

7.8.2

In-transit visibility

Sensitive-life food products are more susceptible during handling and transportation, making them a great concern for logistics operators (Kumar and Budin, 2006). Intelligent food packages integrating RFID facilitate the monitoring of food condition during transportation (Kerry et al., 2006). RFID tags can be coupled with sensors to monitor and, if necessary, control conditions during transportation, thus increasing product security while providing logisticians and clients with accurate product information (Leimeister et al., 2007). RFID can also be combined to GPS technology to track the location of valuable food products in real time while they are in transit from the distributor’s warehouse to the retailer’s location. There has been some investigation of opportunities to use RFID in in-transit visibility applications. For instance, Safeway, a US supermarket chain, has used active RFID tags and readers to track cargo containers transporting groceries as they leave distribution centers in Washington State and travel across Alaska to the chain’s stores and distribution centers (Swedberg, 2007). Unipart Logistics is offering its global costumers a new service that combines active RFID, GSM/GPRS, and GPS technologies for the tracking of containers of goods and fleets of trucks and trailers (Bacheldor, 2007). Starbucks, a popular coffeehouse franchise, is adopting RFID to track temperatures of perishable food while in transit from supplier to their cafés. According to Starbucks’ director of global quality assurance and regulatory affairs, the RFID solution allows improvement of supply-chain visibility and better monitoring of processes, ensuring optimal efficiency and continuous improvement

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(RFID Journal, 2006).The Smart and Secure Tradelanes for Africa project is evaluating the potential of an RFID-based tracking system to increase the quality management of perishable products that are shipped from Namibia to the UK (Hudson, 2006).

7.9 7.9.1

RFID AND POINT OF SALES PROCESSES Automated check-out

RFID technology is considered a promising tool for automating the checkout process at supermarkets. The idea of a retail store where consumers could have a seamless shopping experience has been described in detail by Roussos et al. (2002). Intelligent shopping carts offer a whole new experience for consumers. Intelligent food items can be automatically identified, since items could be read as they are put in the cart. Thus, consumers could access product information, including allergy warnings, product promotions, merchandise prices, etc. (Roussos et al., 2002; Leimeister et al., 2007). At the checkout, all items in the cart can be instantly scanned, eliminating the need for point-of-sale terminals, waiting times, and unnecessary cashiers (Angeles, 2005). Hence, consumers could proceed to a seamless checkout, where grocery charges are billed to the consumer’s credit or debit account as they leave the store. The Metro Group’s “future store” initiative is a preview of how supermarkets will be in the future. Metro Group has deployed RFID within its supermarkets in order to accelerate payment processes. For instance, intelligent carts at Metro Group automatically recognize all tagged products as the customer puts them in, and monitor how much the purchases are going to cost. Moreover, customers only need to pass the products over the RFID reader themselves, bag them, and pay in cash or by card (http://www.future-store.org).

7.9.2

Smart shelves

Supermarket shelves could become “smart” through the integration of RFID readers, which would be able to monitor the movement of RFID-enabled products at the item level, thereby triggering the dynamic replenishment of shelves (Heinrich, 2005). Smart shelf initiatives could help to improve stockouts, reduce theft, diminish inventory shrinkage, and decrease labor costs for retailers. According to Pramatari (2007), RFID could open opportunities for a collaborative shelf-management initiative between retailers and suppliers.

7.9.3

Marketing improvement

From a marketing perspective, RFID can increase consumers’ satisfaction, since it has the capability to provide consumers with real-time information on the location and conditions of perishable food moving across the supply chain. More importantly, RFID can provide an auditable electronic trail of events, from source to consumption, giving the necessary information to reassure consumers about the quality of food (Liu et al., 2008). Moreover, RFID could have major effects in sales processes, since it offers opportunities for: ● ● ●

diminishing waste and returns; setting up new promotion tools; optimizing inventory management (European Commission, 2005).

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According to Roussos et al. (2002), the advantages of RFID do not end at the point of sale. RFID can be also helpful in the aftersales environment. Intelligent products will be able to interact with certain home appliances, since RFID enables object-to-object communication, therefore extending aspects of the supply chain into the consumer’s home (Sellitto et al., 2007). For instance, one potential application could be the automatic re-ordering of products stored in the fridge (Zaharudin et al., 2002). Also, RFID could support customer service and remote maintenance processes, since relevant information, such as proof of purchase and warranty, are embedded in the product (Zaharudin et al., 2002).

7.10 CONCLUSIONS As highlighted earlier in this chapter, there are still several drawbacks to RFID adoption, since standardization, benefits assessment, and technological, legal, and ethical issues need to be solved prior to deploying RFID solutions on a wider scale. In particular, uniform product coding and frequency standards, from the processor to the retailer, is a major issue since the agrifood supply chain is global in nature. In fact, products move constantly through different countries, from the moment they are produced until the time they are consumed. However, regulations concerning traceability and food label information change according to the country. Cost represents another area of concern. This is particularly the case for some RFID applications in the agrifood supply chain, such as attaching a tag to individual livestock. Livestock tags cost 10 times as much as food tags in most cases. The reason is that livestock tags usually take the form of ruggedized, biocompatible implants, pellets in the stomach or ear tags, whereas food tags are usually in the form of basic labels that are not in contact with the food (IDTechEX, 2006). However, it has been demonstrated in this chapter that RFID applications could span the whole supply chain, from farm to fork, and could cover numerous processes such as product traceability, quality control, warehouse and distribution, and asset management. Trends suggest that RFID has a wide potential in the agrifood supply chain, although it is now mostly used by the food processing industry for high-value products (rare cheeses, wines, etc.) due to the technology’s relatively high cost. Recent technological developments and more widespread application will drive the costs down. Since RFID represents an interactive or networking innovation, its utility (perceived or real) increases for all adopters with each additional adopter (Rogers, 1995). Once a critical mass is reached, its diffusion will become self-sustaining. We foresee that RFID will gain additional momentum due to its unique capacity to trigger intelligent processes within and between organizations, at all levels of the agrifood supply chain, thereby making the whole supply chain intelligent.

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8

Food Quality and Safety

Ilias Vlachos

8.1

INTRODUCTION

Supply-chain management (SCM) has attracted increasing attention in academia and in companies looking for practical, effective ways to improve their competitive position. In the European Union (EU), there is an increased awareness that coordination among supplychain members is essential to further improve the competitive position of the European agribusiness and food industries (Folkerts and Koehorst, 1998; Fearne and Hughes, 2000; Hayenga, 2000). In the EU, food safety has become a top priority for consumers, businesses, and government. Recurring food incidents exhibit that food safety is more difficult to assure than initially thought. Responding to food crises, the EU has adopted an integrated approach to food safety, which involves the development of legislative and other actions in order to assure a high level of food quality and safety. It achieves this through coherent fork-to-farm measures and adequate monitoring (European Commission, 2004). The food industry also responded by implementing mandatory and voluntary quality control, management, and assurance schemes. More often than not, delivering safe food to consumers requires coordination among supply-chain partners. Virtually all supply-chain activities might have an effect on food safety. For example, the transportation of meat products may result in pathogen growth, cross-contamination of products, and/or introduction of new pathogens. Although there is little doubt that appropriate SCM can deliver safe food to end consumers, there is scarce evidence on its effect on company performance. Do companies with effective SCM regarding their food safety gain profits or sustain a competitive advantage? Which supply-chain factors, if any, have a distinctive, significant effect on company performance? In order to answer the above questions, we first review the relevant literature on food SCM and its effect on food safety. Then we describe the method we used to collect empirical evidence from the food sector in Greece. We next present analysis of the data and its interpretation. Finally, we discuss our results and suggest directions for future research.

Intelligent Agrifood Chains and Networks, First Edition. Edited by Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis. © 2011 by Blackwell Publishing Ltd. Published 2011 by Blackwell Publishing Ltd.

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8.2

FOOD SUPPLY-CHAIN MANAGEMENT

It is evident that companies in the agribusiness and food industries have to co-operate to achieve mutual benefits (Iijima et al., 1996; Hayenga, 2000; Ghisi et al., 2001; Myoung et al., 2001; Vlachos, 2004). As consumers are becoming increasingly knowledgeable about products and more demanding about price and food quality, organizations have turned to SCM to find ways to create and deliver value to customers (Seth et al., 2006). Successful implementation of SCM in the agribusiness sector means that all supply-chain participants from fork to farm should trust each other and gain mutual benefits (Myoung et al., 2001). However, it is not always easy to form and maintain supply-chain partnerships. Focusing on the food supply chain, Wilson (1996) and Fearne and Hughes (2000) note that partnership formation increased after 1991, especially in the UK food chain. Food retailers, in particular, are extremely keen to employ such partnerships and make use of them in their promotion activities. In the EU, food companies are currently reshaping relationships with their suppliers, producers, distributors, retail stores, and customers. Emerging market trends are: ●

●

greater integration with raw material suppliers regarding long-term relationships in order to reducing costs for the manufacturer and increase security of demand for the producer; increasing collaboration in distribution, which focuses upstream on distribution and retail chains (European Commission, 2004).

It is worth remembering that although traditionally the food manufacturing sector has been more concentrated, in the last decade retail internationalization, merger and acquisition activity, and format diversification have led to high concentration levels in most European retail markets (Dawson, 2004). This implies that retailers are in a position of power relative to manufacturers/suppliers, which makes it difficult to embrace a partnership/collaboration philosophy (Fernie and McKinnon, 2003). Partnerships in the food chain often take a formal shape, as in the case of efficient consumer response, an initiative between food manufacturers and retailers, that requires uninterrupted information flow and good co-operation and trust between key chain participants (Mitchell, 1997; Institute of Grocery Distribution, 2004).

8.2.1

Food safety

Food safety, which can be defined as the assurance of safety and at the same time the absence of food-borne pathogens, is an issue of growing importance among European consumers and food companies. Consumers are increasingly concerned about recurring food scandals and incidents. Food safety is a worldwide concern: in less-developed countries, 70% of deaths among children under 5 are linked to biologically contaminated food, mycotoxins are more prevalent, and foodborne parasites (e.g. cysticercosis) are more common than in developed countries (Unnevehr and Hirschhorn, 2000). The growing movement of people, live animals, and food products across borders, combined with the emergence of new pathogens or antibiotic resistance in pathogens make food safety a critical issue in food-chain management. Food safety is a prerequisite for exporting to the EU. Mowat and Collins (2000) demonstrated that emerging fruit industries can

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improve the performance of the whole chain by implementing better food quality and safety management. Candidate countries for EU accession need to comply with EU standards on food quality and safety.

8.2.2

Quality assurance schemes

The Food Quality Schemes Project, after studying the food supply-chain dynamics and quality certification in the EU, defined quality assurance and certification schemes (QASs) as follows: … any code of practice, standard or set of requisites, which enables stakeholders of the food supply chain to guarantee compliance with what is declared and to signal this to the end or next user, underlying this statement there is some independent verification process that adds authority to the stakeholders’ statement. (Food Quality Schemes Project, 2006)

QASs for food and agriculture are constantly growing in number, backed either by public entities, both national and regional, or by private initiatives. Popular QASs include the Hazard Analysis Critical Control Points Code (HACCP), the British Retail Consortium Global Food Standard, the International Food Standard, the Safe Quality Food protocol and the Euro-Retailer Produce Working Group Good Agricultural Practices standard (EurepGAP). EurepGAP is the result of an initiative taking place in a group of 26 retail organizations belonging to the Euro-Retailer Produce Working Group (EUREP), and aims to develop and harmonize widely accepted standards and procedures for the global certification of good agricultural practices. Representatives from around the globe and from all stages of the food chain, including consumer and environmental organizations, have been involved in the development of these documents. EurepGAP includes topics such as integrated crop management, integrated pest control, quality management system, HACCP, worker health, safety, and welfare, and environmental pollution and conservation management. Published in September 2005, the ISO 22000: 2005 is an international, auditable standard which defines food safety management along the entire food chain. ISO 22000: 2005 specifies requirements for a food safety management system where an organization in the food chain needs to demonstrate its ability to control food safety hazards in order to ensure that food is safe at the time of human consumption. The objective of ISO 22000 is to complement existing food safety schemes in managing food safety along the food chain. ISO 22005, published in 2006, sets out the general principles for tractability in the feed and food chain. When companies do not implement a vendor certification program, they usually have to go through an inspection process. Product inspection is necessary due to the high costs associated with poor food quality. In this case, companies need to justify the trade-offs between inspection cost and the cost of a food crisis. The higher the number of units inspected, the higher the inspection cost, but at the same time the risk of paying a high cost due to poor food quality decreases.

8.2.3

Food safety in supply chains

A safe chain is not an easy thing to achieve and manage. In order to ensure suitable and consistent product, the safe chain must not be broken, e.g. by one product or material not meeting the requirements of the next internal/external customer. A supply chain therefore needs to safeguard food safety across all supplier/customer relationships from farm to fork.

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This requires the development of an effective chain-management system to ensure that the product and service complies with defined criteria at key stages and can be traced to its ingredients or suppliers further back in the supply chain. It is also important that there is consistency from one batch to another. An organization within the supply chain needs to develop its own food safety criteria in order to address both internal food safety as well as ensuring that external safety parameters are consistently met. HACCP principles can be applied throughout the food chain from the primary producer to final consumer. The application of HACCP systems can aid inspection by regulatory authorities and promote international trade by increasing confidence in food safety. A food chain can affect food safety in many ways. Take the meat chain, for example. Pathogens can be introduced and or amplified at many stages along the chain. Transportation may cause stress in animals, increasing shedding of body parts and the spread of pathogens. In slaughter houses, poor safety standards may allow pathogens to spread among animals, carcasses, and cuts of meat. Loose control over the transportation of meat products may result in pathogen growth, cross-contamination of products, and/or introduction of new pathogens. In retail stores, storage and display of food in a hasty manner may affect pathogen growth, through inadequate management of temperature, cross-contamination, and length of shelf-life. Although food quality has been examined in the literature, few studies have shed light on the supply-chain factors that affect food safety. Northen (2001) surveyed UK abattoirs and found that buying farm-assured livestock facilitates selling meat to large multiple retailers, which indicates that farm assurance is a credible signal of food safety attributes. King (2002) pinpointed that quality products require specific supply-chain design. For example, global markets for products with a strong local identity, such as protected denomination of origin products from the EU, are expanding rapidly. Robson and Rawnsley (2001) investigated food quality in the context of power relationships and ethical issues in the food industry in the UK. They argued that general theories dangerously ignore the complexity of such contexts and concluded that partnering in the supply chain brings benefits to all members. The relationship between SCM and food safety may be bidirectional. SUS-CHAIN (2005), a research project co-financed by the European Commission and aiming to assess the potential role of food supply chains in the enhancement of sustainable food production and rural development, found that food safety and hygiene regulations can affect the development of food supply chains, e.g. packaging requirements affect the supply chain of organic food. In 2000, the Global Food Safety Initiative (GFSI) was launched by a group of international retailers who identified the need to enhance food safety, ensure consumer protection, strengthen consumer confidence, set requirements for food safety schemes, and improve cost efficiency throughout the food supply chain (Rossignol, 2004). Thus, a safe chain can also be driver for change. Wilson and Clarke (1998) developed an internet-based traceability system capable of managing food safety data and exchanging it among food-chain members. Wilson and Clarke tested the “Food Trak” system on UK fresh produce – home-grown fruit and vegetables – with pilot projects for homegrown potatoes, carrots, onions, salads, peas, and “top fruit” In this way, retail multiples have access to data on a complete food section as well as being able to reassure UK growers that imported food can and will be subject to the same standards and regime. Green differentiation is a type of market differentiation based on the green characteristics of the products, which can also bring in efficiencies in food chains: environmental management, sustainability, and other production-system attributes can differentiate supply chains and their products from one another (Westgren, 1999).

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Food safety activities in food chains.

Farm production

Transport Slaughterhouse, of animals packing house, and first distributor agricultural products

Transport Industrial of products process

Retailers, food services

Hygiene of facilities

Cleaning

Hygiene of establishments

Cleaning vehicles

Hygiene of Hygiene of establishments establishments

Hygiene of personnel

Disinfection

Hygiene of personnel

Cooling

Hygiene of personnel

Hygiene of personnel

Use of water

Hygiene of Ante and personnel post-mortem inspection and hygiene handling

Hygienic handling of products

Hygienic handling of products

Sewage contamination

Hygienic handling of products

Microbiological monitoring

Labeling

Control of use of agricultural pesticides, veterinary pesticides, antibiotics, hormones

Monitoring of agrichemical residues, residues of antibiotics, hormones, microbiological monitoring

Labeling

In order to preserve food safety, sufficient coordination is necessary. For example, Zylbersztajn et al. (2003) studied the competitive structure of the meat system in Brazil and found that coordination was necessary in order to communicate information about consumers’ needs regarding beef products upstream to slaughterhouses and producers. Kennett et al. (1998) examined bread-wheat quality and its effect on vertical co-ordination in the wheat supply chain and concluded that wheat quality control is directly related to SCM. In particular, better bread quality requires millers and bakers to develop closer vertical linkages with wheat suppliers. Starbird (2001) showed that rewards for better quality and penalties for poorer quality, conditioned by the type of inspection policy, are among the most common quality-related provisions of supply-chain contracts. Furthermore, penalties and rewards can be substitutes for one another. Thus there exists a unique reward/penalty combination at which the buyer’s expected cost of quality is zero. Geiger (1998) studied issues and practices of SCM for small rural manufacturers and found that the most important concept of a successful business partnership is the ability to deliver a top quality product. Table 8.1 summarizes food safety activities across the supply chain.

8.3

INFORMATION SYSTEMS

Many food industries have developed information technology (IT) systems that are focused primarily on economic aspects of the business and the supply chains or the laboratories and the models of production. As a result, a significant number of existing systems are

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designed to optimize the outcome and the level of supply, from continuously improving the quality of supply, to reducing risk and being prepared for the unexpected (Deasy, 2002). Boaden and Lockett (1991) investigated the definition of “information technology” from a management perspective and found that although there are major overlaps and confusions, the term “information systems” is the one in most widespread use. The information can be text, images, data (numbers), signals (control signals), or audio. The management includes collection, storage, processing, transmission, and presentation of the information. IT is based on computer technology, telecommunications, office machinery, and electrical equipment. Regarding the management of food safety, its use is considered important for making decisions at short notice and in real time. Databases with information on microorganisms associated with foodborne pathogens, which determine the response of microbial populations in the environment, food characteristics, and processing conditions are the cornerstone of food safety management (systems). Such databases find applications in the following areas (McMeekin et al., 2006): (i) Identification of pathogens in food at a genus or species level. (ii) Recognition of pathogens below the species level by molecular subtyping, a successfully applied approach in epidemiological investigations of foodborne disease and the basis for national monitoring programs. (iii) Software prediction models, such as the Pathogen Modeling Program and the Growth Predictor, in which the raw data were combined for the genesis of an international online research database (ComBase). (iv) Expert systems combining databases on microbial characteristics, food composition, and processing of information, used to pattern match and demonstrating the problems that may arise from changes in the formation of the products or processing conditions. (v) Computer software packages to assist in the implementation of HACCP, the risk assessment and decision trees to bring logical sequences to establish and modify the management practices of food safety. (vi) Quick dissemination of information on the outbreak of foodborne illness through the internet or through central computers, with comments from many sources, including the press and interested groups, regarding the reasons for and consequences of foodborne illness incidents. (vii) Active monitoring networks, which allow fast transmission of information on molecular subtyping between public health authorities, for the investigation of foodborne diseases and reduction of the spread of human disease. (viii) Traceability of each animal and crop from conception or germination through to the consumer as an integrated part of supply-chain management. (ix) Provide high-quality, online educational packages to food industry personnel.

8.3.1

Information systems and foodborne diseases

The surveillance of public health is defined as “the ongoing systematic collection, analysis, interpretation and dissemination of data appreciating a fact related to health for use in public health action to reduce the morbidity and mortality” (Centers for Disease Control and Prevention, 2001). The monitoring/surveillance of foodborne diseases tends to involve public health researchers identifying the food involved and to prevent future similar cases. The monitoring of these diseases often depends on medical and pathological laboratories for

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the recording of patients who have been infected with microorganisms such as salmonella, campylobacter, and listeria. The proportion of infections transmitted through food varies depending on of the pathogen and can be confirmed by research into multiple proportional human cases (Mead et al., 1999). The nature of foodborne diseases has changed significantly over the past 10 years, mainly because of the production of greater food quantities and the possibility of more choices becoming available to consumers. Also, there has been a significant improvement in laboratory diagnosis of many foodborne infections. All these changes have led to a better understanding of major crises distributed in a large geographical area. Therefore, researchers have been led to change the way they approach a food crisis and are now more reliant on IT to do the hard work (Hedberg et al., 2003). Over the last 10 years, IT has revolutionized the management of foodborne diseases. Many free software applications have been developed for collection of epidemiological data, such as Epi Info (http://www.cdc.gov/epiinfo/) and Epidata (http://www.epidata.dk/), as well as various online databases for the surveillance of infections and seizures. In countries like the UK (http://www.hpa.org.uk/infections/default.htm) and Australia (http://www.cda.gov.au/index.htm), there is continuous monitoring of food contamination data, which are available on the internet. Similar databases exist in the USA (http://www. cdc.gov/ncidod/dbmd/outbreak/us_outb.htm) and New Zealand (http://www.surv.esr.cri.nz/ surveillance/annual_outbreak.php) (McMeekin et al., 2006). Doctors and laboratories in many countries are mobilized for the collection of data on infectious diseases, using standardized electronic recording systems (Effler et al., 1999). These systems are highly effective and provide better information than simple manual systems (Effler et al., 1999; Backer et al., 2001). In practice there are problems with obtaining data from the internet for many health departments. Such problems are related to secrecy, standard terminology and many technological difficulties (Bean and Martin, 2001). The electronic recording of surveillance data from several institutions and countries will have many advantages for surveillance of foodborne diseases, based on early registration information from respondent infected patients. The progress of IT has enabled the development of monitoring tools, which has then helped in the investigation of foodborne crises. These tools include databases for the collection of recorded infections and algorithms to determine whether the number of cases has increased over time. Geographic information systems have improved the ability of epidemiologists to detect spatial clustering (Hightower and Klein, 1995). The biggest change in the monitoring and control of foodborne infections is the use of molecular techniques combined with databases of genetic information (McMeekin et al., 2006). An example of a database for genomic information on foodborne pathogens is the PulseNet system, which is coordinated by the Centers for Disease Control and Prevention (Swaminathan et al., 2001). The PulseNet system isolates the pathogens, salmonella, listeria and E. coli O157: H7 using pulsed field gel electrophoresis and is based on harmonized laboratory protocols (Swaminathan et al., 2001). The resulting patterns are imported into a bio-mathematics database, which is shared by the participating laboratories. This system has helped to identify large complex foodborne crises and provides a library of DNA images for future reference (Centers for Disease Control and Prevention, 2000). There are also web databases that allow genetic comparison of foodborne pathogens. For example, for more than 10 years, the UK’s database of norovirus concatena tion files has recorded microbial strains that cause infections (http://www.hpa.org.uk/srmd/bioinformatics/

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norwalk/norovirus.htm). These databases are decisive for the determination of origin of foodborne infections and potential trends in infections (Lopman et al., 2004). For immediate response to crises, the various global health authorities are based on communication networks. This is particularly important as the foodborne crises spread over a large geographical area, sometimes even internationally. The advantage of rapid communication through e-mail has improved the investigation of widely dispersed crises (Sobel et al., 2002). When a food is ascertained as the reason for the crisis, the internet is a useful means for the distribution of this information worldwide. Two such mailing lists are FSNET (http:// www.foodsafetynetwork.ca/) and Promed (http://www.promedmail.org). The inputs to these central mailing lists of the foods that are considered responsible for causing foodborne crises has helped in the detection of international crises (Kirk et al., 2004). The World Health Organization has established the Global Outbreak and Alert Response Network, which monitors impending crisis reports that circulate on the internet (Heymann and Rodier, 2004). The primary aim of this type of monitoring is the detection of and the response to emergencies of international importance, which are caused by contaminated food.

8.3.2

Forecasting food safety

Predictive microbiology involves the development of mathematical models of the changes in microbial populations in foods. It is based on the assumption that the correspondence of populations of micro-organisms to environmental factors can be replicated. Thus, by characterizing the environment in terms of factors which influence microbial growth and survival, it is possible to predict the behavior of those microorganisms in similar environments from past observations. For the modeling of microbial correspondences in foods an of two-step approach is used worldwide. First, models are used for the expression of changes in concentrations of organisms with the passage of time, by using a limited number of kinetic parameters, such as years of adjustment, pace of growth or inactivation, and maximum achievable population, which together describe the change in the population size. Then, secondary models express the effect of environmental parameters, e.g. temperature, sodium chloride levels and pH, on the kinetic parameters (Ross et al., 2000). Models of predictive microbiology are important tools for the management of food safety as they provide a scientific base of support for key aspects of the HACCP system and for quantitative microbial risk assessment. The models of limits of growth help in the determination of potential microbial risk factors in specific foods. The growth and inactivation models provide a quantitative link between the measurements used to monitor the production processes (e.g. time, temperature, pH, and salt content) and possible responses of specific pathogens. This information is useful when the limits to the critical control points must be determined or when identifying corrective actions to achieve compliance with the performance criteria (McMeekin and Ross, 2002). Growth or inactivation of pathogens in food, along the chain from farm to table, is essential for microbial risk assessment. The predictive models are therefore essential tools in the assessment of consumer exposure to food pathogens at time of consumption. Moreover, models of predictive microbiology are considered valuable for teaching and advisory purposes (McMeekin and Ross, 2002). The Pathogen Modeling Program (PMP) is available free on http://www.arserrc.gov/mfs/ pathogen.htm and with more than 5000 transhipments per year it is among the most widely used software applications of prospective microbiology. The PMP has been available for 15 years and has been continually updated and expanded. The current edition contains more

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than 35 models for 11 pathogenic bacteria (Tamplin et al., 2004). The program allows the development or the inactivation of pathogens to be foreseeable for different combinations of constant temperature, pH, salt content, and in some cases other conditions such as type and concentration of organic acid, atmospheric conditions, or nitrate content. These predictions can be learned and the program contains references to studies from which models were developed. The PMP program falls short of information from evaluation studies which show the performance of models in specific foods and general facilities in forecasting the effect of varying temperature conditions on growth and inactivation (McMeekin et al., 2006). The commercial software, Food MicroModel, which is similar to the PMP program, is no longer available. However, data from the Food MicroModel are incorporated in the Growth Predictor software, which is available free on http://www.ifr.ac.uk/safety/growthpredictor/. Growth Predictor version 1.01 includes 18 models and allows predictions at constant temperature conditions, pH, and salt content. These predictions can be made, but the Growth Predictor software is simple and contains little information on the development model and the attribution of models to different foods. The reason for the simplicity of the software’s operation is that it constituted a fast solution before a new integrated ComBase-PMP (Combined Database and Predictive Microbiology Program) system was launched on the market. This will combine the best features of the ComBase database and the predictive program, PMP, and will be equipped with new, improved models that are also available on the internet (McMeekin et al., 2006). Symprevius (http://www.symprevius.net/) is a decision-support system in French, which includes a database of responses of the development of microorganisms in food and predictive development models of pathogenic bacteria (Leporq et al., 2003). The Food Spoilage Predictor (FSP) (Neumeyer et al., 1997), the Seafood Spoilage and Safety Predictor (SSSP, http://www.dfu.min.dk/micro/sssp/) (Dalgaard et al., 2003) and the Safety Monitoring and Assurance System (SMAS) (Koutsoumnis et al., 2003) are more concrete examples of the implementation of proactive microbiology programs. These software systems allow the reading of the temperature profile of the product and predict the effect of variable temperatures on the growth of microorganisms (McMeekin et al., 2006). Various programmatic tools are used for the development of proactive microbiology programs. There are no widely accepted specifications and standards for the input (temperature profile, product characteristics) and for the output (kinetic parameters and changes in concentration over time). These aspects require further study and research as it will increase the possibility of integrating these systems with other information systems such as traceability systems or HACCP (McMeekin et al., 2006).

8.3.3

Decision-support systems for food safety management

Decision-support systems are software systems that support the decision-making process, helping the responsible person to understand the implications of their decisions. They provide opportunities for organizing and processing data and information through databases. They contain computer tools for system analysis, such as algorithms for simulation, optimization, and decision analysis. They are designed to assist responsible individuals in taking appropriate decisions on complex and unstructured problems by formulating a detailed study and a series of options. Decision-support systems should not be considered as replacements or substitutes for human decision-making. They are there simply to assist.

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Under continuous pressure from retailers, many food companies have introduced quality procedures such as total quality management, ISO (International Standards Organization) and HACCP, but they continue to maintain control and standards at the statutory minimum level (Deasy, 2002). Information systems, including ComBase, of predictive microbiology software, software to determine the risk and decision-support systems are useful when the risk factors, the critical control points and critical limits are identified in the development of a HACCP plan. Information systems facilitate the use of structured approaches that include recording of the details and actions required in order to provide evidence that the safety management system operates and all the risks are under control during the production process (McMeekin et al., 2006). Information about HACCP software is available on the websites at http://peaches. nal.usda.gov/foodborne/fbindex/-HACCP.asp?subtopic=general and http://www.foodsafetycentre.com.au/fstoolkit/. A well-implemented and documented HACCP system is the core around which the rest of the system of quality assurance will be incorporated (Jouve et al., 1998).

8.4 8.4.1

CASE STUDIES Methodology

In order to assess the use of IT in food safety management, a case research methodology was followed. Four case studies with Greek food companies were conducted using a case protocol. Case studies were given Greek letters in order to guarantee confidentiality of interviewees. Case studies were based on in-depth, semi-structured interviews with key decision makers. The aim of the case research was to draw valuable and useful conclusions for the implementation and use of information systems in the management of food safety, considering the difficulties food companies face, the benefits accrued, and the reasons for the adoption of these systems.

8.4.2

Food company profiles

(i) Case Alpha Case Alpha is a food company active in the biscuit and the bakery product sector. The annual income is approximately €100 000 000. They invest approximately €1 000 000 per year in information systems for managing food safety. The company employs approximately 1000 people and is notable for its consistency and seriousness in dealing with issues of human resources. The current climate in human relations allows the development of a teamwork spirit, collaboration, initiative, and potential for growth and development. Seven people work in the information systems department. The company, because of its industrial and commercial activities, covers almost the entire range of skills in management and technical scientific personnel. The executives at all levels of the hierarchy are graduates of institutes of higher education or technological education institutes and hold postgraduate qualifications from Greek or foreign universities. Continuous education, in the form of training and information programs and seminars, constitutes a particular concern for the company and a basic tool of growth and the staff development, in order to maintain competitive advantage. The company has four factories, in Athens, Thessaloniki, Volos, and Oinofyta. The main market of Case Alpha is Greece. However, it exports to about 48 countries. Case Alpha also collaborates with approximately 2000 wholesalers, which strengthen the distribution and

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circulation of its products in all distribution channels. The company gives priority to working with the most suitable importers/distributors in each country in order to sell its products abroad. However, the expansion of export activity is one of the main strategic objectives. It is a large company, which invests in information systems in order to achieve high quality and safety for its products. (ii) Case Beta Case Beta is active in the production and marketing of standardized also-served ice-cream, juices, croissants, frozen dough, and sweets. The annual income amounts to roughly €150 000 000. The company employs approximately 150 people as permanent staff, plus some seasonal staff (approximately 1000) due to the needs of its products. Under the policy of quality and safety applied by Case Beta, the enterprise allocates sufficient, capable staff and attends to the continuous improvement of capabilities of all its partners. The employees commit themselves to the adoption of measures and economically feasible technical solutions leading to the least possible burden on the environment, following the doctrine of sustainable development. The scientific personnel are suitably trained and are continuously informed so that they support all the efforts of the company for a cleaner environment, and produce technological solutions and innovations that improve environmental performance. There are 10 employees who deal with the implementation of information systems and they belong to the management information systems department. The company has two factories – one in Athens and one in Aspropyrgos – plus branches in Rhodes, Thessalonica and Bulgaria, and a large dealer network for the wider distribution of its products. The company is 95% focused on the Greek market but aims to become an internationally competitive enterprise and to offer high-quality innovative products and services. (iii) Case Gamma Case Gamma is a food company that operates in collection and packing of honey. The annual income amounts to about €23 000 000. Over the last three years they have invested about €110 000 in software and hardware for the management of food safety, and it is expected that the company will make a further investment of €40 000 for extensions of these systems. The company employs 105 people. Its participation in the government-funded program “Positive actions of men and women in small to medium-sized and large enterprises” strengthens its activities in achieving equal opportunities between men and women, equal participation in positions of responsibility and reconciliation of work and family life. Moreover, these actions require gender-blind recruitment, which still describes the responsibilities of the position, the knowledge required, and the experience and skills for the position. The criteria for development partners and employees are their qualifications and their effectiveness as well as the suitability of their personal and corporate goals. The development and motivation of staff follows the corporate strategy, whose main slogan is “growth through the development of our people”. The working environment and the frame of work within the company are intensely anthropocentric and friendly. Beta responds to the particularities of each worker with the aim of achieving corporate and individual quality and as well as satisfaction. The number of employees who deal with the implementation of information systems is 70. The company has a factory, which is based in Athens, a facility for offices and a warehouse of raw materials and finished goods. It also owns a sales office in Thessaloniki. The main market for the enterprise is Greece, which is responsible for 85% of profits, principally from

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supermarkets. With a complete network of salesmen – dealers and special partners – the company has a presence throughout Greece. Also, it ensures the wide distribution of its products in European countries, the Middle East, the USA, Canada, Cyprus, Japan, Australia, Singapore and recently in China. Twenty per cent of the company’s turnover comes from exports of its products. (iv) Case Delta Case Delta operates in the production and packing of a wide range of cooking, pastry making, and infant food products. Its annual income amounts to about €52 000 000. In the sector of subsidized investment, over the last five years, the company invested €5 million in equipment, in order to fully automate the receipt and transportation of raw materials and the processing of end products. The company employs approximately 300 people, of whom 70% are qualified personnel, 40% hold a university degree, and 20% have done postgraduate studies. Out of 300 personnel, just two work in the information systems department. The company wants staff to be well trained and therefore supports specialized seminars and postgraduate studies. The company promotes teamwork and cooperation by giving common objectives in the development, the production, and the promotion of products. This has led to all departments of the company being in close daily cooperation, improved services, and the development and promotion of products so that they meet the increasing demands and continuously evolving needs of consumers. The company tries to ensure a good working environment and quality of work by rewarding its people appropriately. The company has two factories, which have the most modern mechanical equipment in Europe, as well as offices occupying 30 000 m2 in Athens. The products of the company are targeted at the Greek market but are also exported to the USA, Canada, Latin America, the EU, Russia, Ukraine, Albania, the former Yugoslav Republic of Macedonia, the Middle East, Australia, and Africa. The export policy of the company is based on the study of the needs of local markets, with adaptation of the specifications of products to the trends and consumption habits of each country’s consumers. It is characteristic that the products circulate in every country in packages translated into local languages. Case Delta, through its high-quality products, which are in accordance with international quality standards, has earned the trust and preference of consumers in each of these countries.

8.4.3

Results

The Case Alpha company uses custom-made software applications that deal with the quality and safety of its products. Created by specialized software houses (the NHRF Papadopoulos SA, YIOTIS, ETAT SA and MANTIS) the food safety systems have been in operation for two years. The Case Alpha company does not have laboratories for food analyses but relies on external laboratories, such as ETAT SA. The company uses the polymerase chain reaction method for detection of genetically modified organisms in raw materials. Educational seminars are occasionally given on the use of certain models, such as the Pathogen Modeling Program, Growth Predictor v. 1.01, and the Safety Monitoring and Assurance System. The HACCP system was adopted by the company in 1996, as its use resolves many problems. The company is certified by International Quality Management System ISO 9001: 2000.

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Regarding traceability, Case Alpha uses a single software application that includes and controls all management functions of production, from receipt of raw materials and packaging materials to the traceability of finished goods to the final customer. The traceability system is capable of tracing and tracking goods at the supply side (trace – 1) and at the consumer side (trace + 1). Trace – 1 consecutive traceability covers the movement of goods between the company and its suppliers, the internal traceability system covers the movement of goods within the firm itself and the successive trace+1 covers the movement of goods between the company and its customers. The system was created by a Greek software house called MANTIS. The main reason for the use of traceability system is to facilitate the recall of products in the event of a problem. The benefits resulting from the adoption of traceability is the reduction of time (to only a few minutes) for checking the products and the savings in filing time (employees are no longer required to photocopy, fill in forms, etc.). With the automation of traceability, many functions have become automated, such as the monitoring from the Athens office of production lines and the analysis of plants. As for the cost of the software, this is low for the value it offers. Case Alpha gains specific advantages as a result of implementing food safety applications and, in particular, it better controls product safety, increases its competitive advantage and reduces production costs. More specifically, Case Alpha has managed to reduce incidence of unsafe and unacceptable products, complaints from consumers, and has increased competitiveness and productivity. However, the costs arising from the use of information systems are not only related to software and equipment. The main obstacle to the introduction of these systems was their acceptance by employees. Interestingly, resistance to change increased as one moved up the hierarchy, that is, top management were sceptical about the success of the system. The company evaluated that the cost of software and equipment would return as a profit in the future. The investment in the information systems totaled €2.5 million, which also included the training of personnel. Case Beta uses many software applications to manage food quality and safety because of the huge amount of information gathered at different points. For example, the commercial software from DCW Software Hellas is a control system that creates invoices. Also, the company uses special machines for pricing manually, from which it also receives information on problem lots. Information systems for managing food safety at the company were adopted three years ago. In the future, the company foresees changes in the systems in order to achieve integration. The requirement by the state and legislation for the implementation of information systems, especially for traceability, is another reason for adoption of new software applications by Case Beta. Case Beta outsources microbiological analyses to an accredited laboratory abroad. Case Beta accesses the database ComBase, but it does not use it because it does not cover the specifics of its products. The laboratory uses API test strips for the control of fruit juice quality but the implementation is not sufficiently simple to be used on a daily basis. Chemical-based technologies for identification of bacteria or molecular techniques are not used. If it is found that there is a bacterial population that should be identified, the sample will be sent to an accredited laboratory. Along with all the modern techniques, the company also performs controls with plates, which requires experienced staff. Microbiology prediction software is only used in the planning stage or in the identification of microorganisms. The company has installed the Food Security System, which is based on the principles of HACCP, as defined by the Codex Alimentarius, European and national legislation.

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It is continuously monitored for the safety of products by national authorities (EFET, Prefecture). In December 2006, the company was certified to the new international standard, ISO 22000. Case Beta uses the traceability system Aberon to achieve forward and backward tracing of products. Aberon is a flexible logistics and distribution management information system and is the main solution for managing and optimizing the supply chain. Aberon provides continuous monitoring of the flow of information and materials on each link in the supply chain, from production, receipt, storage, collection of orders, loading and delivery of the orders to customers. The company has adopted traceability systems to meet the requirements of legislation and Regulation 178/2002, but also to facilitate cases of withdrawal of products and determination of the locale of the problem. With traceability systems, public health is protected and a valid diagnosis of problems in the production process is achieved. The controls throughout the supply chain are improved and the transparency of the production chain is increased. Since the traceability system is a legal requirement, the cost is not calculated. As for radio frequency identification technology, the company does not use it, at least for the moment, because it is expensive in relation to its products. The benefits of using information systems in the management of food safety are summarized in the increase of productivity and the reduction of response time in cases of the appearance of unsafe products. Better response times are crucial in crisis management. For example, it is too late when a contaminated lot goes to customers. Rapid respond allows pinpointing of contamination and a cessation of production before the contamination spreads out of the production line. A barrier to using information systems is the cost of acquisition of software and equipment as well as the increase of the total cost of personnel, particularly with regard to the education of employees of company. Case Gamma uses an integrated ERP system, which focuses on the needs of the accounting, financial, and commercial areas of the business. This is a software solution that integrates several functions of the company, but does not cover the requirements of the food product itself. It a general business software application that is only customized for the food product particularities. As a result, the company is not meeting its legal obligations and currently it plans to upgrade its ERP system to one that will cover food quality and safety in a straightforward way. However, the automation of production and operations do have benefits for food quality and, in particular, Case Gamma has reported: ● ●

better control of safety of produced products; cost reductions due to diminution of contamination.

Furthermore, consumer complaints have been reduced, which helped in improving the corporate and brand image and reputation of the firm, since there are few complaints from consumers and customers. Another side-effect has been the improvement of the relations between the enterprise and service control authorities. However, information systems are quite expensive for Case Gamma, especially now that it is considering the upgrade of the software and the renovation or building of a new corporate headquarters, as well as dealing with the increasing need to maintain and keep records of food quality and safety operations. Case Gamma does not perform microbiological analysis, molecular techniques, and chemical-based tests for identification of bacteria because of the nature of the product. It also does not use a forecasting model for microbiology. Since 1998 it has been certified by ISO9001 by TUV HELLAS (TUV NORD).

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Case Gamma uses the Tracer Factory for traceability but in the future this is expected to change. The Tracer Factory system is a tool for the implementation of traceability in the agricultural industries. The traceability system is in line with legislative requirements and simultaneously minimizes withdrawals, confirms the origin of products and, in the end, assists in early detection of any problem. The implementation of the traceability system facilitates the company in achieving a reduction in the likelihood of losses from defective products, minimization of withdrawals, carrying out of corrective actions and withdrawal of products, complete monitoring of the production process, protection of public health and optimization of supply-chain control. Moreover, the company believes that the traceability system is part of the integrated management of product quality. The costs for the enterprise are the purchase and installation of the traceability system as well as training personnel for its proper operation. RFID technology is not needed for this product. The software for the quality and safety of Case Delta’s products was first developed in 1992 and it is integrated with the enterprise information system, which was initially developed by Greek software houses in collaboration to food quality laboratories. The company uses advanced technology equipment for quantitative analysis and quality control of foods, but also for the processing of data on quality and production. Since 1995, all of the data have been recorded and processed in specialized databases. Since 2000, the company has used as its main software the SAP ERP production data management system. SAP covers the following functional areas: financial management, audit, materials management, sales and distribution, production planning, project management, facilities maintenance, quality control, and human resource management. The aim of the company is to mobilize more and more applications of the SAP system, particularly for monitoring the full traceability of products and the complete implementation of safety of HACCP products. Case Delta gained concrete benefits from the use of food safety software applications. In particular, returned goods due to safety or quality problems were reduced, contamination events were reduced significantly, and corporate image among business partners and customers improved significantly. The reputation of Case Delta was significantly improved. Case Delta has its own laboratories for running the necessary food quality tests. It uses API test strips and conducts microbiological tests and a body of rapid measurements of microbiological alterations, the BACTRAC. Case Delta also performs a lot of chemical analyses in its laboratories. It uses gas chromatographs equipped with detectors incorporating the latest technology for qualitative and quantitative determination of nutrients (such as vitamins, sugars, and fats), but also contaminants in the raw materials (e.g. pesticides, dioxins, and polychlorinated biphenyls, known as PCBs). It uses spectrographic infrared spectroscopy for qualitative and quantitative analysis of raw materials and intermediate and final products, high pressure liquid chromatographs for analysis of vitamins, preservatives and other nutrients, UV spectrographs for the determination of protein and mineral content, and color analysis of mixtures. The most widespread molecular technique carried out is polymerase chain reaction, for the qualitative and quantitative determination of possible genetic modifications to raw materials. For its microbiology prediction software the company uses the Pathogen Modeling Program and the Food Spoilage Predictor). Since 1997, the company has been certified to ISO 9001: 2000, HACCP, and the British Retail Consortium standards. One problem resulting from the use of the HACCP system is the need to control and monitor a a wide variety of products, which makes daily operation more complex than before. Case Delta uses integrated computer software, which is linked to the quality system. In addition, the company uses laboratory information management system (LIMS) software as

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a business solution for managing the lifecycle of the laboratory procedures, from the traceability of raw materials and samples when these are entered, and following the flow through the laboratory to the analysis of samples, management of collected data, and their recording by transmission to the corporate system. The LIMS software allows the company to manage lots, quality assurance, the laboratory analyses, environmental monitoring, and connection to instrumentation. The traceability system is a legal requirement and is used for the diagnosis of problems in the production process, to confirm the origin of the food, for surveillance, control and the elimination of disease, and for conformity with customer requirements. However, the company believes that the benefits of using the traceability system are not direct, but appear only in the event of a crisis or if requested by competent authorities. The cost of the system is covered by a grant. RFID technology is used by this enterprise.

8.5

DISCUSSION

This study’s aim was to understand how SCM relates to food safety. The results of the study provide an initial framework for the firms in food industry to profit from their management of food quality in their supply chains. Based on the study’s results, we conclude that food companies are expending a remarkable amount of effort in order to safeguard food quality. Apart from applying quality assurance and certification schemes, food companies have to deal with a vast number of quality issues throughout their supply chain. Threats to food quality exist in every supply-chain activity, making SCM a big responsibility. Based on the results of this study, we can identify a number of managerial implications. First, it highlights the role of SCM in controlling and assuring food safety. Second, it provides SCM managers with a useful tool for evaluating the efficiency of their current SCM practices with respect to food safety. Finally, we find evidence that supply-chain factors do have an effect on firms’ performance. Food safety can be a burden to some companies but it can also set them on the way to change and competitive advantage. Although current research focuses on the relationship between the supply chain and food quality and safety, we acknowledge that the present study has limitations. First, we drew our sample from the Greek food industry, a mature industry that is characterized by a proliferation of small and medium-sized enterprises. Results from studies on a specific industry may have limitations when generalizing to other sectors of the economy. On the other hand, there are only a few studies on supply-chain factors in Greece and northern Europe in general, and the findings of this study can thus be useful in future comparative studies. This chapter has provided empirical justification for a framework that identifies six factors of SCM in food quality. Managing directors provided their own experiences and knowledge on how to establish and maintain a safe food chain and at the same time have more benefits than costs.

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9

Traceability in Agrifood Chains

Ulla Lehtinen

9.1

INTRODUCTION

Food safety and food quality have increasingly come to the forefront of consumer concern, industry strategies, and government policy initiatives. A variety of private sector and public policy traceability initiatives have emerged in various countries, ostensibly with the objective of reducing consumer information asymmetry with respect to food safety and food quality attributes (Hobbs et al., 2005). Traceability can be part of a strategy to reduce the risks or minimise the impact of a foodborne disease. It can also be part of a larger quality assurance strategy, facilitating the verification of specific quality attributes (Hobbs et al., 2005). There are a number of motivations for traceability such as: ●

●

● ● ● ●

improving food safety by providing added information about suppliers and processing stages; improving the effectiveness of product recalls after the discovery of a food-safety or product-quality problem; protecting or regaining the general reputation of a product, a firm, an industry, or a country; differentiating products by providing traceability; guaranteeing product origin (e.g. ‘local food’, organic food, GMO, fair-trade etc.); reducing operating costs and increasing productivity by transmitting accurate, timely, complete, and consistent information about products through the supply chain (Hobbs et al., 2005; Regattieri et al., 2007).

Traceability is of an importance at the chain level, as well as at the company level. Since the 1990s government, especially within the European Union, has paid lot of attention to traceability because of food scandals and product recalls. In Table 9.1 the benefits of traceability for different stakeholders are highlighted. There is no international agreement on the definition of traceability. Typically, it is defined as the ability to follow and document the movement of food through specified stages of production, processing, and distribution (van der Vorst, 2004; Hobbs et al. 2005). The ISO 9000: 2000 standard defines traceability as ‘the ability to trace the history, application, or location of that which is under consideration’. The ISO guidelines further specify that traceability may refer to the origin of the materials and parts, the processing history, and the Intelligent Agrifood Chains and Networks, First Edition. Edited by Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis. © 2011 by Blackwell Publishing Ltd. Published 2011 by Blackwell Publishing Ltd.

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Table 9.1

Benefits of traceability for different stakeholders.

Consumer

Business

Government

Protect food safety by effective product recall Enable avoidance of specific foods and food ingredients, whether because of allergy, food intolerance, religious, or lifestyle choice Gives certainty of the origin of food and helps consumers’ food choices

Protect pubic health through the effective withdrawal of food products. Enable control with regard to human and animal health in emergencies Losses are minimised by efficient recall process Information about raw materials and processes improves process and quality management Improved information retrieval simplifies audits

Comply with relevant legislation Be able to take prompt action to remove products from sale Be able to diagnose problems in production and pass on liability where relevant Assure food products and maintain market and consumer confidence

Based on van der Vorst (2004).

distribution and location of the product after delivery. EN ISO 22000: 2005 states that an organisation, or indeed an integrated supply chain, should establish and apply a traceability system that ‘enables the identification of product lots and their relation to batches of raw materials, processing and delivery records.’ Lot identification marking or coding is a basic element in traceability. In Article 18 in EU regulation 178/2002 it is stated that food or feed that is placed on the market or likely to be placed on the market must be adequately labelled or identified to facilitate its traceability, through relevant documentation or information that is in accordance with the requirements of more specific provisions. In general, a lot is processed from same raw materials in the same processing conditions, and has been limited to at most the size of one day’s production (Aarnisalo et al., p. 9). In the literature, the concept of traceability is often used as a synonym for tracking and tracing (e.g. Wilson and Clark, 1998; van Dorp, 2002). Tracking refers to the determination of the ongoing location of items during their way through the supply chain, as shown in Figure 9.1. Tracing aims to define the composition and the treatments an item has received during the various stages in the production lifecycle. Upstream (backward) tracing aims to determine the history of items or lots and downstream (forward) tracing aims at the determination of the location of items that were produced using for example, a contaminated batch of raw materials (van der Vorst, 2004). Within the food supply chain there are two types of traceability (see Trace, 2010). Internal traceability refers to data about companies’ own production processes. Many companies have good routines and software systems for internal traceability. This kind of software is often linked with dedicated production management software and general enterprise resource planning (ERP) systems. Chain traceability deals with the data received and data sent by the company. Chain traceability typically: ● ● ● ●

occurs between companies and between countries; depends on internal traceability being present; involves major privacy issues; requires standards for recording and exchange of data.

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Tracking (pro-active gathering of data)

Forward tracing (reactive gathering of data)

Suppliers

Farmers / grower

Processor

Retailer distribution centre

Outlet

Consumers

Processor

Retailer distribution centre

Outlet

Consumers

Backward tracing (reactive gathering of data)

Figure 9.1 Tracking and tracing. After van der Vorst (2004). Reproduced with permission.

The enforcement of chain traceability implies the development of systems providing information on the entire life cycle of food products, ‘from farm to fork’. A company located in one specific link of a supply chain may well have completely manual systems for recording traceability information. However, electronic solutions facilitate business partners in reconstructing the complete process history of any food efficiently and quickly. There are six essential elements of an integrated agricultural and food supply chain traceability system (Opara, 2003). These elements are: (i) Product traceability defines the physical location of a product at any stage within the supply chain. (ii) Process traceability ascertains the type of activities that have affected the product during the growing and post-harvest operations (what, where, and when). (iii) Genetic traceability determines the genetic composition of the product and includes information on its type and origin (source, supplier). (iv) Inputs traceability determines type and origin (source, supplier) of inputs, e.g. fertilisers, or the additives used for preservation or transformation of the raw materials into processed products. (v) Disease and pest traceability records the epidemiology of microbiological hazards and pests, which may contaminate food products. (vi) Measurement traceability relates individual measurements, through calibrations, to reference standards and assures the quality of measurements by observing various factors that may have an impact on results (such as environmental factors, operator, etc.).

9.2

TRACEABILITY AND FOOD SAFETY LEGISLATION

Food safety has been a growing concern among people over recent decades. Traceability is a risk-management tool that allows food-business operators or authorities to withdraw or recall products that have been identified as unsafe.

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Table 9.2

The traceability system in action (European Commission, Food Traceability factsheet). Overall responsibilities

Actions taken when a risk is identified

Food and feed businesses

Identify and document information on products ‘one step forward and one step back’ in the food chain

Immediately withdraw the affected products from the market and, if necessary, recall them from customers Destroy batch, lot, or consignment of feed that does not satisfy food safety requirements Inform the competent authorities of the risk and of the action taken

Member state authorities

Monitor production, processing, and distribution of food and feed produces to ensure that operators have traceability systems in place Fix and enforce penalties for operators that do not meet EU requirements on traceability

Ensure that operators are meeting their obligations Take appropriate measures to secure food safety Trace the risk backwards and forwards along the food chain Notify the Rapid Alert System and Feed (RASFF*)

The EU

Establish sector-specific legislation and traceability as appropriate Food and Veterinary Office of the European Commission carries out regular inspections to ensure that food and feed operators are meeting food safety standards, including the implementation of traceability systems

The European Commission alerts members of the Rapid Alert System for Food and Feed of the risk Requests information from operators to enable traceability May impose import/export restrictions

* The RASFF network, set up in 1979, was enhanced by the General Food Law in 2002. This warning system supports the traceability system by enabling the rapid exchange of information whenever a risk to food or feed safety is indentified. If a member of the network becomes aware of a potential risk to human health, it notifies the European Commission, which immediately transmits this information to the other members.

Under EU law, ‘traceability’ means the ability to track any food, feed, food-producing animal, or substance that will be used for consumption, through all stages of production, processing, and distribution. The EU’s General Food Law came into force in 2002 and makes traceability compulsory for all food and feed businesses. It requires that all food and feed operators implement special traceability systems. They must be able to identify where their products have come from and where they are going and to rapidly provide this information to the competent authorities. In addition to the general requirements, sectorspecific legislation applies to certain categories of food products (fruit and vegetables, beef, fish, honey, olive oil) so that consumers can identify their origin and authenticity (see Table 9.2). There are also special traceability rules for genetically modified organisms (GMOs), which ensure that the GM content of a product can be traced, and which require accurate labelling so that consumers can make an informed choice (European Commission, 2007). The requirement for ‘one step backward – one step forward’ traceability is similar in the USA to Europe. For the USA, the requirements for documentation and traceability are even more detailed, as a result of the Public Health Security and Bioterrorism Preparedness and

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Response Act of 2002, which came on force on 12 August 12 2004. This law requires the registration of all facilities, domestic and foreign, supplying food to the USA and mandates records to identify the suppliers and recipients of all food products. Food manufacturers, processors, and packers must also record lot-specific information (i.e. a lot number, a code number, or other identifier) to the extent that this information exists. Lot-specific information distinguishing one production batch from another can be a number printed on the packaging or some other identifier, such as a ‘best used by’ date. Finally, the records must be available for inspection and copying as soon as possible, but not exceeding 24 h from the receipt of an official request (Levinson, 2009). In addition, the Farm Security and Rural Investment Act of 2002 requires ‘country-of-origin’ labelling on beef, lamb, pork, fish, perishable commodities, and peanuts. The organic farming control system (Regulation (EEC) No 2092/91) was the first to demanded a traceability system from producers in the EU. Member states must ensure that the control system is set up so as to allow for the traceability of each product at all stages of production, preparation, and distribution (Regulation (EC) No 178/2002). Detailed accounts must be kept to ensure optimum traceability. Producers of organic products of animal origin must also keep records providing a full description of the herd or flock management system, which must detail livestock, by species, entering and leaving the holding, as well as any animals lost, details of feed, and of any veterinary treatment. Organic production rules also concern wild food items such as wild berries and herbs. In Finland, the public right of access to nature regardless of the ownership or occupancy of the area allows berries, mostly lingonberry, bilberry, and cloudberry, to be picked from the forest. Wild berries can also be picked and marketed as organic berries, where based on an organic picking system. Certain areas are considered acceptable for organic collecting: those forests that have not been fertilised for five years and are situated far enough from roads and industry. When a picker sells berries to a local buyer, he or she must confirm the picking area on a map. The berry companies must maintain these picking records to ensure that raw materials are organic. Every stage of the supply chain documents information on berries and products ‘one step forward and one step back’. By following these documents it is possible to determine the picking area of the berries.

9.3

TRACEABILITY SYSTEMS

EN ISO 22000: 2005 Food safety management systems requires a traceability system as following (ISO 22000: 2005 7.9): The organisation shall establish and apply a traceability system that enables the identification of product lots and their relation to batches of raw materials, processing and delivery records. The traceability system shall be able to indentify incoming materials from the immediate suppliers and the initial distribution route of the end product. Traceability records shall be maintained for defined period for system assessment to enable the handling of potentially unsafe products and in the event of product withdrawal. Records shall be in accordance with statutory and regulatory requirements and customer requirements and may, for example, be based on the end product identification.

Traceability systems are constructions that enable traceability. ISO 22005: 2007 ‘Traceability in the feed and food chain’ gives the principles and specifies the basic requirements for the

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design and implementation of a feed and food traceability system. According to the ISO 22005: 2007 standard, traceability system should be able to document the history of the product and/or locate a product in the feed and food chain. Traceability systems contribute to the search for a cause of nonconformity and the ability to withdraw and/or recall products if necessary. Traceability systems can improve the appropriate use and reliability of information, and the effectiveness and productivity of the organisation. A traceability system is a tool that should be designed within the context of a broader management system. The choice of traceability system is influenced by regulations, product characteristics and customer expectations, and should result from balancing the different requirements, technical feasibility and economic accessibility. The traceability system should be verifiable. Each element of a traceability system must be considered and justified on a case-by-case basis, taking into account the objectives to be achieved. In the design of a traceability system, the following shall be included: ● ● ● ● ● ● ● ● ●

objectives; regulatory and policy requirements relevant to traceability; products and/or ingredients; position in the feed and food chain; flow of materials; information requirements; procedures; documentation; feed and food chain coordination.

Markets give food suppliers three primary motives for establishing traceability: supply-side management, product differentiation, and food safety and quality control. First, traceability systems help food firms minimise the production and distribution of unsafe or poor-quality products, which in turn minimises the potential for negative publicity, liability, and recalls. The traceability system is firm’s key to finding the most efficient ways to produce, assemble, warehouse, and distribute products. Many food products have attributes that are impossible or difficult for consumers to detect. The only way to verify the existence of these attributes is through a bookkeeping record that establishes their creation and preservation. The basic characteristics of a traceability system – product identification, information, and the links between them – are common for all systems independent of the type of product, production, and control system involved. In practice, traceability systems are record keeping procedures that show the path of a particular product or ingredient from suppliers into the business, through all the intermediate steps that process and combine the ingredients into new products, right through to consumers. Both products and processes may form key components in a traceability system, with information stored about each. In the simplest systems, the only information carried is that showing the path along which products can be identified through the chain of production, distribution, and retail. Additional information may be carried, e.g. information enabling processing efficiencies or information concerning ingredient quality or origin. The amount of information can be extended as required by the system, and it may be carried for only part of, or throughout the whole, food chain (Food Standards Agency, 2002). Traceability costs and benefits vary across firms and industries. The dynamic interplay of different levels of costs and benefits has spurred different rates of investment in traceability across various food supply sectors. The breadth, depth, and precision of each system will

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Seed, A Variety Purchase lot Pesticides register number Net weight Production country Tuber size

Figure 9.2 An example of a plant passport certificating the origin of a seed potato lot.

vary depending on the objectives of the systems and the corresponding benefits and costs to the firm. A system for tracking every input and process to satisfy every objective would be enormous and very costly. Firms determine the necessary breadth, depth, and precision of their traceability systems depending on the characteristics of their production process and their traceability objectives (Golan et al., 2004). ‘Breadth’ is the amount of information collected. A recordkeeping system cataloguing all of the food’s attributes would be enormous, unnecessary, and expensive. For example, for a cup a coffee (see Figure 9.2), the beans could come from any number of countries, be grown with any variety of pesticides or just a few, be grown on huge corporate organic farms, be harvested by children or by machines, be decaffeinated using a chemical solvent or with hot water, etc. Only a few consumers would be interested in all this information. A traceability system for one attribute does not require collection of information on the other attributes (Golan et al., 2004) The ‘depth’ of a traceability system is how far back or forward the system tracks. For example, a traceability system for decaffeinated coffee would extend back only to the processing stage. A traceability system for fairtrade coffee would extend only to information on price and terms of trade between coffee growers and processors. A traceability system for fair wages would extend to harvest; for shade grown to cultivation, and for non-genetically engineered (GE) to bean and seed. In other cases, the depth of the system is determined by quality safety control points along the supply chain. In this case, traceability systems may only need to extend back to the last control point, i.e. the point where quality or safety was established and verified (Golan et al., 2004). ‘Precision’ reflects the degree of assurance with which the tracing system can pinpoint a particular food product’s movement and characteristics. The unit of analysis used in the system and the acceptable error rate determines precision. The unit analysis, whether container,

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truck, crate, day of production, shift, or any other unit, is the tracking unit for the traceability system. Systems that have large tracking units, such as entire feedlot or grain silo, will have poor precision in isolating safety or quality problems. Systems with smaller units, such as individual cows, will have greater precision. Likewise, systems with low acceptable error rates, such as low tolerances for GE kernels in a shipment of conventional corn, are more precise than systems with high acceptance error rate. Lots are the smallest quantity for which firms keep records. Firms may choose among an infinite array of units, shapes, or time, defining their own lot size by the quantity of product that fits in a container, that a forklift can move on a pallet, or that fills a truck. A lot may be an individual animal or group of animals or production from an entire day or shift. In choosing lot size, firms typically consider a number of factors, including accounting procedures, production technology, and transportation. There is no standard traceability unit. Furthermore, a firm is likely have a different lot size for incoming and outgoing products. The size and the shape of a lot are likely to change at each processing juncture. Some firms may find it efficient to maintain the depth of traceability by linking incoming and outgoing lots, while others may not. For example, an apple packer and shipper may use accounting procedures to choose the incoming lot size. The shipper may receive apples from a number of growers and must pay each grower based on the type, size, and grade of the product. Since these attributes are known only after the apples have been sorted, each grower’s apples need to be kept separate on the packing line. These accounting procedures thus influence the lot size of the product entering the packing house. As apples are sorted, packed and shipped, a packing house may choose to make a lot the number of boxes than can be loaded onto a truck. One or several growers’ apples could be loaded together – it is most cost-effective to fully pack a truck. There may be food safety and quality concerns that motivate a shipper to keep a lot size no larger than a truckload. In the case of food safety the shipper may want to limit the size of a recall and limit the number of affected growers (Golan et al., 2004). The cattle/beef sector has a long history of identifying and tracking animals to established rights of ownership and to control the spread of animal diseases. Producers in the meat sector, both in Europe and the USA have developed traceability systems to improve product flow and to limit quality and safety failures. Producers must now tag every one with details of their origin and, when animals are taken to slaughter, stamp them with the traceability code of the abattoir. The tools used (ear tags, passports, barcodes) may vary from one country to another, but must carry the same information (European Commission, 2007). Ear tags and other relevant information are transferred to the carcass at slaughter, after which animal tracking becomes increasingly difficult. Conventional traceability is achieved through manual or computer-assisted paper-based tracking systems. Particularly in recent years, new solutions, especially radio frequency identification (RFID) devices, have been developed (Mousavi et al., 2002; Kelepouris et al. 2007; Shanahan et al., 2009). To enable the traceability of animals across borders, in April 2004 the EU introduced the TRAde Control and Export Systems (TRACE, 2010; https://sanco.ec.europa.eu/traces). This system provides a central database for tracking the movement of animals both within the EU and from third countries (European Commission, 2007). Meat must be traceable from the selling point to the animal of origin. Records begin from the farm, where each calf must be marked with two ear tags. The main ear tag is put in the left ear not later than 20 days after birth. It records country code and birth code, both as barcodes, and the last four numbers of the birth code. The other ear tag, in the right ear, also includes the birth code, together with a control number. All calves in Finland are entered into a national register that gives information on the birth, death and selling date of a calf, etc. Also, the cattle

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Attributes of interest Decaf

Fair trade

Fair wage

Shade grown

Non-GE

Safety

Stages of production

• Processing • Sales from producer to wholesaler/retailer

??

• Transportation • Storage • Harvest • Cultivation • Bean/seed Necessary depth of traceability

Figure 9.3 The depth of traceability system. After Golan et al. (2004). Decaf, decaffeinated; Non-GE, not genetically engineered.

farm must keep its own calf register. If the cattle is not earmarked or registered or if the origin of the cow cannot be traced within two days, the animal is destroyed. In the slaughter house, ear tags are first removed and attached to the carcass so that the ear tag data can be integrated with other slaughterhouse information. A label is produced during classification, where the information about the animal is stated (origin, birth identification, date of slaughter, and number of the slaughterhouse). This label follows the carcass to the cutting room. In the cutting and packaging step the birth identifications of the animals are combined into a lot identification, which is placed on the consumer packaging (Lihatiedotus, 2009). Also, within the Single Market, a plant passport system has been developed. Plant material, which may host the most serious quarantine pests and diseases, requires a plant passport to facilitate its movement within EU. Plant passports may be issued by growers who are registered and authorised for the purpose. In Figure 9.3, a passport of seed potatoes is shown. The passport is added to a sold lot, and gives information about the origin of the seed potatoes. By following the field and inventory records, the origin of the seeds of retail potatoes can be traced.

9.4

TRACEABILITY TECHNIQUES

The basis of all supply-chain technology is the ability to identify the things that move: pallets, packages, and units of products. The simplest type of identification is a label with a name or number written on it. However, machine-readable labels are being rapidly developed. The handling of traceability information at primary production, food production, distribution centres and transport consists of the following essential components in each step (Aarnisalo et al., 2007): ● ● ● ●

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lot identification – lot information; reading and handling of the information – automatic or manual; storage the information – electronic, papers; content of lot information; transformation of the information to customers – electronic, papers; content of the lot information.

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The problem with the traceability system is that part of the important information is often still stored on paper, rather than electronically. Information technology has the potential to revolutionise product traceability. The most common tools for traceability are labels containing alphanumerical codes, barcodes, or RFID, of which barcodes seem to be the most frequently used system.

9.4.1

Global Trade Item Numbering and other barcode systems used in traceability

Barcodes are optical, machine-readable systems that use a simple coding system based on different thicknesses of bars and spaces. The components of a barcode system consist of a scanning device, a portable terminal, and a label. Scanners read barcodes by using red light to recognise the contrast between the bars and spaces of the symbol (Mousavi et al., 2002). There are several regulations for recognising and numbering single products. The Global Trade Item Number (GTIN) is the foundation of the GS1 System (formerly the EAN.UCC system) for uniquely identifying trade items, which includes both products and services that are sold, delivered, and invoiced at any point of supply chain (GS1 US, 2006). The European Article Numbering (EAN) Organisation’s EAN.UCC system was developed to provide a simple standardised system for recognising units in national and international food chains. In electronic tracking and tracing systems, EAN-UCC (2002) has been universally accepted as an identification and communication system that uniquely indentifies products, locations, services and assets, and which also includes a series of standard data structures known as Application Identifiers (AIs), which allow secondary information about a product, such as batch, expiry and lot number, to be encoded. The system consists of three components (Schwägele, 2005): (i) Identification numbers – used to identify a product, location, logistic unit, service or asset. (ii) Data carriers – the barcodes or RFID tags used to represent these numbers. (iii) Electronic messages – the means of connecting the physical flow of goods with the electronic flow of information. With the tGTIN (formely EAN) code, a product can be recognised at different stages of the delivery chain. The ‘number’ consists of two parts: a number individualising the product and a machine readable barcode corresponding to the number. In Europe, a 13-digit EAN code has been used. A marking code used for packed products in delivery packages is EAN-128, which can be used when additional information is needed for packages (e.g. best-before date, measurement data, lot and serial numbers, etc.), and is consequently a more flexible system than EAN-13 (Morrison, 2003). In the USA and Canada, a 12-digit Universal Product Code (UPC) is used for tracking trade items in stores. Products marked with EAN codes will also be accepted in North America, in addition to those products already marked with a UPC. Each product, including those with different sized packaging, contains a unique UPC code. When a package is scanned under a laser beam at the checkout counter, the store’s central computer reads the UPC number, records the sale, and marks the change in inventory (Golan et al., 2004). GS1 (see http: //www.gs1.org/) is an international not-for-profit association dedicated to the development and implementation of global standards and solutions to improve the efficiency and visibility of the supply chain, globally and across multiple sectors. GS1 was

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formed in 2005 to consolidate the work of the North American UCC (formed in 1974) and the EAN (formed in 1977 by 12 European organisations). GS1’s main activity is the development of the GS1 System, a series of standards designed to improve the management of supply chains. The GS1 System is composed of the following standards: (i) GS1 barcodes: global data and application standards for barcodes that use GS1 identification keys to automatically identify things such as traded items, locations, logistic units, and assets. (ii) GS1 traceability is a robust solution for tracking and tracing items through the supply chain. GS1 traceability standard (see http: //www.gs1.org/traceability) is a business-process standard describing the traceability process independently from the choice of enabling technologies. In order to give an understanding of how GS1 traceability solutions work in practice and how to implement the GS1 traceability standard in food chains, GS1 has so far published application guidelines for traceability in the wine supply chain and an implementation guide for traceability of fresh fruits and vegetables. (iii) GS1 eCom are global standards for electronic business messaging, which allow rapid, efficient and accurate automatic electronic transmission of agreed business data between trading partners. They are based on two components: GS1 EANCOM and GS1 XML. (iv) The Global Data Synchronization Network™ (GDSN™) is an automated, standardsbased, global environment that enables secure and continuous data synchronisation, allowing all partners to have consistent item data in their system at the same time. (v) GS1 EPCglobal is a global standards system that combines RFID technology, existing communications network infrastructure and the Electronic Product Code (a number for uniquely indentifying an item) to enable immediate and automatic identification and tracking of an item through the whole supply chain globally. (vi) GS1 MobileCom aims to provide open standards to enable the mobile sector to link product information with consumers and business through mobile devices. (vii) GS1 Upsteam Integration is the GS1 solution to address the challenges in supplychain integration between manufacturers and their suppliers. (viii) GS1 standards carry data, which allow supply chain participants to track and trace products. The application of these standards requires manufacturers, importers/ exporters, carriers, distributors, and retailers to keep records of serial numbers of logistics units (SSCC), identification numbers of trade items (GTIN), and their attribute information (Application Identifiers) and local numbers of their origin (GLN) (GS1, 2008). The Global Trade Item Number (GTIN) is a number used for the unique identification of trade items worldwide. A trade item is any item on which there is a need to retrieve predefined information and that may be priced, ordered, or invoiced for trade between participants at any point in any supply chain. The Global Location Number (GLN) is a numeric code that identifies any legal (e.g. company, division), functional or physical entity (e.g. plot of land) within a business or organisation. Each location is allocated a unique number. The use of a GLN is a pre-requisite for efficient electronic data interchange. The Serial Shipping Container Code (SSCC) is a number that is used for the unique identification of logistic units. A logistic unit is an item of any composition, established for

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transport and storage that need to be managed throughout the supply chain. The SSCC provides an unambiguous identification for logistic units (e.g. a container, etc.). All parties of the supply chain can use it as a reference number for the relevant information held in electronic or human readable files. An Application Identifier (AI) is any variable information required over and above the trade unit or logistics unit identification (e.g. batch number, production date, or customer purchase order). Attribute information is barcoded in the GS1-128 barcode symbol. GS1 barcodes allow automatic data capture of GS1 numbers. The GS1 numbering and barcoding system allows data input into computer systems, automating the flow of information into business processes.

9.4.2

Radio frequency identification

RFID is a generic term for technologies that use radio waves to automatically identify objects. Storing a serial number, and perhaps other information, on a microchip that is attached to an antenna performs the identification. RFID enables identification of an object from a distance without requiring a line of sight. An RFID tag, also known as a transponder, is a small device that can be attached to an object to be identified and tracked. The tag is composed of a microchip, an antenna and a substrate or encapsulation material. The microchip stores data while the antenna transmits and receives the data. The microchip and the antenna attached to the substrate are referred to as the inlay. The inlay is encased in protective material, such as paper, plastic, or a film. Tags are available in many different shapes, sizes, and protective housings (Kumar et al., 2009). The smallest tags commercially available measure 0.4 × 0.4 mm2 and are thinner than a sheet of paper (Roberts, 2006). The initial entry of data into a tag is known as the commissioning of the tag. Tags can be classified as: ● ● ● ●

read-only; write-once, read-many (WORM); electrically erasable programmable read-only memory (EEPROM); read–write tags (see Brown, 2007).

Most of today’s tags have reprogrammable memories, so that the memory content can be changed or added to at various parts of the product chain. Although commonly referred to as a ‘reader’, reprogramming is performed wirelessly using the same device. To secure the tag data from unauthorised reprogramming, parts of the tag memory can be locked or protected with a password. The radio waves are able to penetrate the commonly used packaging material – paper, cardboard, or plastic – and thus line of sight between the tag and the reader is not required. In these products, no identification code (e.g. barcode) is needed (Aarnisalo et al., 2007, p. 25). In supply-chain management, RFID tags are used to track food products during distribution and storage. RFID technology serves as a replacement for barcode scanners for this particular application (Kumar, 2009). RFID systems reduce labour costs as no manual scanning operations are required. An RFID reader can scan numerous tags at the same time and identification is very simple and rapid. In the food industry, RFID provides improved management of perishable food items by continuous monitoring of item routing, reduces waste, and improves customer service levels. It offers improved tracking and tracing of quality problems by using individual product

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codes, as well as improved management of product recalls (Regattieri et al., 2007). An RFID tag is durable and enables reading in, for example, dirty and cold conditions, which may be almost impossible with barcodes. RFID tags’ large memory enables individual recognition of products. The main limitation of RFID has been the costs of tags – approx. €0.08–10 each (Madge, 2005; Regattieri et al., 2007). They are still expensive compared to barcode labels, which cost less than 1 cent (Kumar et al., 2009). In near future, RFID-based systems will also be used to monitor the quality of the products and the supply chain itself. RFID-based remote sensing will enable, for example, online spoilage detection of vacuum-packed food products and monitoring of the continuity of the cold chain. As an alternative to conventional barcodes and RFID, new electrically readable coding techniques have also been developed. These electrically readable codes are cheaper than RFID tags but still have some of the major benefits of RFID technology. Electrically readable code can be attached to a product using conventional printing techniques combined with special links. Electrical code itself can be invisible and is not as sensitive to dirt and other visible disturbances as conventional barcodes. It is possible to embed some sensor properties into these codes, as with RFID tags (Aarnisalo et al., 2007). Wal-Mart stores Inc. was the first major company to push for RFID implementation in its supply-chain management. Walt-Mart required its top 100 suppliers to ship goods with RFID incorporated, by the beginning of 2005 (Krivda, 2004). EPCglobal (http://www.epcglobalinc.org/) is a non-profit organisation that develops and implements the standards for the Electronic Product Code™ (EPC), in order to support the use of RFID in fast-moving, information-rich, trading networks. EPCglobal was founded in 2003 by the international organisations for global standards. eProvence (Bordeaux Cedex, France) has developed an RFID-based tracking system to preserve the quality of fine wines and to trace their origins. The RFID system consists of three components. The first is a 13.56 MHz semi-active RFID tag placed inside each case of wine. The semi-active tag enables wine producers and distributors to monitor and log ambient temperatures in each case of wine three times a day. The second component is a proprietary and tamper-proof neck seal at the base of the capsule of each bottle. The seal has a unique identifying code printed with invisible ink, which contains identification numbers of both the semi-active and passive tags. All components are linked together with their unique identification numbers on an online database (Launois, 2008).

9.4.3

New technologies

9.4.3.1

Voice-recognition systems

Voice-recognition technology allows users to enter data on the status and location of an item, i.e. packages, pallets, containers, railcars, or vehicles, directly into a computer simply by speaking into a microphone (Mousavi et al., 2002). In food chains, voice-recognition systems are used in warehouses and distribution centres where order-picking is one of the most labour-intensive functions. Voice-recognition systems let users concentrate on the selection process, freeing them from having to focus on the tool that they are using. This simplifies the function and streamlines physical movements by eliminating the necessity of picking up or putting down an instrument, or shifting the gaze of the employee from the instrument’s display to the material being collected. All this translates into more efficient physical movement

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and reduced opportunities for error. For grocery distributors in particular, voice solutions seem to do better than scanning technology in cold storage areas (Kevan, 2004). 9.4.3.2

Feature identification systems

Feature identification systems rely on collecting intrinsic data about a product’s natural features or properties, which can then be used to provide a unique form of identification. Biometric data can be used as a method of indentifying an individual animal. The advantages of biometric identification are that it is tamper-proof, and the biometric identifier does not change over the animal’s lifetime (Shanahan et al., 2009). For example, the vascular pattern of the retina is unique to each animal. An image of this pattern can be simply and rapidly captured using a specially configured digital camera. Iris scans, which are also unique, can be captured similarly. Retinal imaging with a digital camera linked to an internal GPS receiver enables automatic encryption of the date, time, and location of image capture, making it virtually tamper-proof (Marchant, 2002). Retinal imaging appears to hold the most promise as a bovine biometric identifier (Shanahan et al., 2009). In recent years, increased attention to food safety has stimulated interest in the authenticity of food products. DNA markers are increasingly being used to solve traceability and provenance issues for animals and plants. DNA samples can be collected from animals at any point during their lifecycle, from blood, meat, saliva, etc. (Food Standards Agency, 2002). Although, so far, DNA testing is too slow and costly to be used for routine identification of livestock on a large scale (Stanford et al., 2001), in one European project a collection of 49 olive varieties, randomly selected from among those most commonly cultivated in the Mediterranean basin for production of Protected Designation of Origin and high-quality olive oils, was constituted (see OLIV-TRACK, http: //www.dsa.unipr.it/foodhealth/oliv-track/index.html; Consolandi et al., 2008). The main objective of this project was to apply molecular technologies based on genomic and metabolic information to the problem of the traceability of the origin and authenticity of olive oils produced and sold within the European Union. Optical signatures can nowadays be coded into plastics during manufacture. These can be read using a fluorescent reader. Chemical signatures can also be used in a similar way and electronic noses have been developed that may allow volatile signatures to be used (Food Standards Agency, 2002). One innovative technology utilises microscopic, edible barcodes, which can be applied directly onto foods to make them more secure, safer, and also less expensive, by replacing ‘one step forward, one step back’ traceability protocols with reach-through and real-time documentation of the origin and subsequent history of a product. Compounds such as polylactic acid or celluloses can be used for producing these food markers by extrusion. The size and concentration of these markers must be such that they have no detectable effect on the taste or the texture of the marked product. The information has to be encoded on the surface of fairly rigid microscopic particles and the particle must be attached to food by either electrostatic attraction, use of wetting agents, proteins, or lipids as adhesives, or by mixing the particles into a material that is subsequently mixed into or applied to a food. Generally, binary coded information is scored and embedded onto and within a fibre. When placed on/in food, the markers by definition become food additives and must be safe for the consumer at the maximum level at which a consumer might be exposed. In some cases, it may be useful to use a marker that dissolves after a particular time or after it has been heated to a particular temperature (Nightingale and Christens-Barry, 2005).

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REFERENCES Aarnisalo, K., Heiskanen, S., Jaakkola, K., Lander, E., Raaska, L. (2007) Traceability of food and foodborne hazards. VTT Research Notes 2395. Edita Prima Oy, Helsinki. Brown, D.E. (2007) RFID implementation. New York. McGraw-Hill. Consolandi, C. et al. (2008) A procedure for olive oil traceability and authenticity: DNA extraction, multiplex PCR and LDR-universal array analysis. European Food Research and Technology, 227, 1429–1438. European Commission (2007) Food Traceability (factsheet). Available at: http: //ec.europa.eu/food/food/ foodlaw/traceability/factsheet_trace_2007_en.pdf. Food Standards Agency (2002) Traceability in the Food Chain. A preliminary study. Food Chain Strategy Division, Food Standards Agency, UK. Golan, E., Krissoff, B., Kuchker, F., Nelson, K., Price, G. (2004) Traceability in U.S. Food Supply; Economic Theory and Industry Studies. Agricultural Economic Report No (AER830). USDA/Economic Research Service. GS1 US (2006) An introduction to the Global Trade Item Number (GTIN). Available at: http://www.gs1us. org/library. GS1 (2008) Wine Supply Chain Traceability. GS1 Application Guideline. Brussels. Available at: http: // www.gs1.org/docs/traceability/GS1_wine_traceability.pdf. Hobbs, J.E., Bailey, D., Dickinson, D.L., Haghiri, M. (2005) Traceability in Canadian red meat sector; do consumers care? Canadian Journal of Agricultural Economics, 33, 57–65. Kelepouris, T., Pramatari, K., Doukidis, G. (2007) RFID-enabled traceability in the food supply chain. Industrial Management and Data, 107(2), 183–200. Kevan, T. (2004) Improving warehouse picking operations: voice-recognition systems offer advantages that scanning technology can’t touch. Frontline Solutions. Available at: http: //findarticles.com/p/articles/ mi_m0DIS/is_5_5/ai_n6121010/?tag=content; col1. Krivda, C. (2004) RFID after compliance: integration and payback. Business Week, December. Kumar, P., Reinitz, H.W., Simunovic, J., Sandeep, K.P., Franzon, P.D. (2009) Overview of RFID technology and its applications in the food industry. Journal of Food Science, 74(8). R101–R106. Launois, A. (2008) RFID tacking system stores wine bottle data. Food productiondaily.com, April 2008. Available at: http://www.foodproductiondaily.com/content/view/print/141322. Levinson, D.R. (2009) Traceability in the Food Supply Chain. Office of Inspector General, Department of Health and Human Services, USA. Lihatiedotus (2009) Traceability of beef. Available at: http://www.lihatiedotus.fi/www/fi/laatu/naudanlihan_ jaljitettavyys/index.php. [In Finnish]. Madge, R. (2005) Responding to traceability needs. New Food, 8(3), 78–82. Marchant, J. (2002) Secure Animal Identification and Source Verification. Optibrand, Fort Collins, CO. Morrison, C. (2003) Traceability in food processing: an introduction. In: Food authencity and traceability (ed. Leeds, M.). Woodhead Food Series no. 94. Woodhead, Cambridge. Mousavi, A., Sarhadi, M., Lenk., A., Fawcett, S. (2002) Tracking and traceability in the meat processing industry: a solution. British Food Journal, 104, 1, 7–19. Nightingale, S.D., Christens-Barry, W. (2005) Placing barcodes directly onto foods. Food Technology, 59(2), 36–39. Opara, L.U. (2003) Traceability in agriculture and food chain: a review of basic concepts, technological implications, and future prospects. Food, Agriculture and Environment, 30, 239–247. Regattieri, A., Gamberi, M., Manzini, R. (2007) Traceability of food products: General framework and experimental evidence. Journal of Food Engineering, 81, 347–356. Roberts, C.M. (2006) Radio frequency identification (RFID). Computer Science, 25, 18–26. Schwägele, F. (2005) Traceability from a European perspective. Meat Science, 71, 164–173. Shanahan, C., Kernan, B., Ayalew, G., McDonnell, K., Butler, F., Ward, S. (2009) A framework for beef traceability from farm to slaughter using global standards: An Irish perspective. Computers and Electronics in Agriculture, 66, 62–69. Standford, K., Stitt, J., Keller, J.A., McAllister, T.A. (2001) Traceability in cattle and small ruminants in Canada. Revenue Scientifique et Technique (Office of Epizootics), 20(2), 510–522. TRACE project (2010) Appendix A. Recommendations for Good Traceability Practice in the Food Industry. Tracing Food Commodities in Europe (FP6–2003-FOOD-A). Available at: http://193.156.107.66/ff/po/ TraceFood/guidelines.htm

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van der Vorst, J.G.A.J. (2004) Performance levels in food traceability and the impact on chain design: results of an international benchmark study. In: Proceedings of the Sixth International Conference on Chain and Network Management in Agribusiness and the Food Chain (eds H.J. Bremmers et al.), pp. 175–183. Wageningen, The Netherlands. van Dorp, K.J. (2002). Tracking and tracing: a structure for development and contemporary practices. Logistics Information Management, 15(1), 24–33. Wilson, T.P., Clarke, W.R. (1998) Food safety and traceability in the agricultural supply chain: using the internet to deliver traceability. Supply Chain Management, 3(3), 127–33.

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10

E-business Applications in the European Food and Beverages Industry: Evidence from the Wine Sector

Michael Bourlakis and Ilias Vlachos

10.1

INTRODUCTION

Until recently, companies in the food and beverages industry have used e-business mainly to improve their internal processes and procedures. Applications most commonly used both by small and large enterprises are e-mail, websites and online banking. These basic tools are followed, with a considerable distance in terms of adoption rates, by the introduction of electronic data interchange (EDI) and enterprise resource planning (ERP) systems. However, the growing complexity of the industry is driving companies to adopt more effective solutions in response to new strategic challenges. The most important issues that are likely to have a big influence on information communication technology (ICT) investment decisions in the future are food safety and the full digital integration of the value chain. Investments in supply-chain integration (both internally and in business-to-business (B2B) processes), including radio frequency identification (RFID) technologies, are a focus of ICT adoption in the industry. Integration of internal processes, customer relationship management (CRM) and supply-chain management (SCM) are also likely to gain momentum. The main opportunities companies hope to exploit through e-business are improvements in customer service, increased efficiency of internal processes, and sharing investments and risks. The main risks and barriers for e-business adoption in small and medium-sized enterprises (SMEs) at present are the inadequacy of existing ICT infrastructure, the fragmentation of supply chains (especially in Southern Europe) and cultural barriers. This chapter reports and synthesises findings and reports of the European e-Business Market Watch (E-business Watch, 2003) and reports on a case study (oenoview) of an advanced application that combines geographical information technologies and image processing to safeguard wine quality in the field and across the supply chain.

10.2

E-BUSINESS APPLICATIONS: A TYPOLOGY

E-business can be defined as any business transaction that takes place using information and communication technologies. This broad definition includes three mainstream e-business applications: Intelligent Agrifood Chains and Networks, First Edition. Edited by Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis. © 2011 by Blackwell Publishing Ltd. Published 2011 by Blackwell Publishing Ltd.

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(i) commercial activities such as buying and selling products and services electronically; (ii) business activities such as enterprise resource planning, customer relationship management as well as collaboration in new product development; (iii) social activities such as supporting social interaction and cultural enforcement, i.e. by the use of discussion groups, e-mail, chat, and so forth. According to the type of trading partner, e-business applications are classified into several categories such as B2B, business-to-consumer (B2C), business-to-government (B2G), and government-to-citizen (G2C). The dominant characteristic of these categories is the conduct of a business transaction electronically by using a communication network. The basic components of an e-business application can be described as follows. Firstly, there is the infrastructure, which consists of hardware and a communications network in the form of the electronic medium. The most popular electronic medium is the internet. Then there are the internal software applications that manage the e-business transactions, i.e. to present information, store and retrieve data in databases, or exchange information. Web-based applications, such as a corporate website, an electronic marketplace and a webbased data interchange are increasingly being used by corporations of any size. The web gives businesses a global presence: the corporate site becomes a company’s shop front in a worldwide downtown. As a result, internal software applications have to integrate with the web applications seamlessly, a task that is more easily said than done. Finally, there are the e-business applications themselves, which can be classified into three categories according to the purpose (Table 10.1): (i) Informative applications. The purpose of informative e-business application is to provide technical, professional or business information, as in the case of a corporate website. In this case, the content is typically unstructured and dynamic. Typical informative transactions include the corporate website, business communication transactions and e-promotions using e-newsletters and e-mail. Recent developments in web technologies such as the extensible markup language (XML) aim to develop a unified framework for unstructured informative transactions. XML is a language that defines a document format that is very similar to semi-structured data and can support the integration of multiple data sources (Deutsch et al., 1999). (ii) Transaction applications. The purpose of e-business transactions is to facilitate current or future transactions with business partners and customers. In this case, electronic transactions should be codified in advance. Instead of using the post office to exchange invoices, receipts and other sorts of business documentation, companies can exchange EDI messages, which are structured according to predefined standards, e.g. the UN/EDIFACT standard. The majority of e-marketplaces are also characterised by codified business transactions. Humphrey (2002) found it useful to classify e-business marketplaces according to the extent to which transactions are either transaction- or information-oriented. In the transaction-oriented type, Humphrey includes online auctions, which take place in real time and also facilitate on-line payment. (iii) Growth applications. Chandler, in his seminal work, pointed out that the purpose of a firm, particularly a large and/or innovative one, is more than to reduce transaction costs: firms actually define new markets and resource uses (Chandler, 1990). E-business can be used as an instrument to open up new markets, leverage new product development and engineer innovative business processes. E-tailing is an example of how technology

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E-business Applications in the European Food and Beverages Industry Table 10.1

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A taxonomy of e-business applications.

Type and scale of users

Objective of e-business application Informative

Operations

Growth

Individuals (customers)

Discussion groups Mailing Portals Vortals

Internet access Retail Auctions Build-to-order Banking Brokerage Travel

P2P Mobile commerce G2C

SMEs (including SBC)

E-procurement Search engines Electronic agents

ASPs Hosting E-Banking B2G Auctions and marketplaces

ASPs Mobile commerce

LSEs

B2E Electronic agents

ERP CRM Enterprise application integration Salesforce automation

Mobile commerce Virtual chain

P2P, peer-to-peer; G2C, government-to-consumer; SME, small and medium-sized enterprises; SBC, small business customers; ASP, application service providers; B2G, business-to-government; LSE, large-scale enterprises; B2E: business-to-employee: services provided to employees, e.g. corporate/industry news and key contacts, ERP, enterprise resource planning; CRM, customer relationship management.

has created a new market of online shoppers, who, instead of paying a visit to the local retail store, prefer to do their shopping electronically from home or work. Although the initial target group of e-tailers consisted of busy people, reports, i.e. by Andersen Consulting, indicate that as many as 42% of shoppers in the USA and Europe are willing to order groceries from home (Narayanan, 1997; Verhoef and Langerak, 2001).

10.3

E-BUSINESS APPLICATIONS FOR AGRICULTURE AND THE FOOD INDUSTRY

The advent of advanced ICT has created a multitude of challenges and opportunities in the food sectors in developed economies. E-business applications have received particular favour, given the fact that food industries depend on effective distribution systems in order to meet diversified consumer demands and need to be able to deal with short delivery times as well as maintaining effective reverse logistics (Iijima et al., 1996; Vlachos, 2004). During the last two decades, large companies, especially retailers and manufactures, have used e-business applications to increase their power in agrifood supply chains by enhancing customer service, creating economies of scale, reducing logistics costs and facilitating the

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Table 10.2

Applications of e-business tools to food and agribusiness management.

Business functions

E-business tools

Applications

Marketing

B2B e-commerce, internet ordering, corporate websites, mobile commerce

Product promotion, new sales channels, direct savings, reduced cycle time, customer services

Purchasing

EDI, Internet-purchasing, EFT

Ordering, fund transfer, supplier selection

Production

B2B e-commerce, MRP, ERP, GIS

Production planning and control, scheduling, inventory management, quality control

Sales and distribution

Electronic funds transfer, online TPS, bar-coding system, ERP, WWW integrated inventory management, internet delivery of products and services, RFID

Internet sales, selection of distribution channels, transportation, scheduling, third party logistics

Warehousing

EDI, EFT, web-based integrated inventory management

Inventory management, forecasting, scheduling of work force

Supplier development

Web-assisted supplier selection, communication using internet (e-mails), research on suppliers and products with web and intelligent agents

Partnership, supplier development

Source: Adopted from Gunasekaran et al. (2002). B2B, business-to-business; EDI, electronic data interchange; EFT, electronic funds transfer; MRP, material requirements planning; ERP, enterprise resource planning; GIS, geographical information system; TPS, transport management systems; WWW, world-wide-web; RFID, radio frequency identification.

efficient flow of food and information. Such an achievement has been strategically leveraged by ICT that enhances the performance of food chains, i.e. in terms of cost, time and accuracy of deliveries, and at the same time assures food quality and safety. Small and medium-sized food companies can use web-based e-business solutions to exploit niche markets and create new market segments by gaining sporadic, low-volume suppliers and customers at low marginal cost. Table 10.2 shows the e-business applications for various agribusiness functions. A multitude of e-business solutions can be applied to each business function, e.g. EDI and webbased integrated inventory management for warehousing and automated replenishment. There is consensus that e-business applications have a profound impact on the food supply chain. E-business adds flexibility to operations management, allowing for smaller lots of orders and shipments, real-time inventory replenishment, and shorter order cycle time and, subsequently, shorter lead times. Van der Vorst et al. (1998) argue that SCM should be concerned with the reduction or even elimination of uncertainties to improve the performance of the chain and suggest that reduction of uncertainties could improve service levels significantly. Myoung et al. (2001) pointed out that the successful implementation of SCM in agriculture means that all parties involved in production, distribution and consumption must trust each other if they are to gain from information sharing. However, a substantial body of evidence suggests that the competitive advantages from the implementation of e-business in the food chain may be distributed unevenly among the parties involved (Loebbecke and Powell, 1998).

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E-business Applications in the European Food and Beverages Industry

10.4

171

THE ROLE AND USE OF ICT IN THE EUROPEAN FOOD AND BEVERAGES SECTOR

The role and use of ICT technologies mirrors the structure of the industry: dominance by large multinationals, where the creation of industrial groups (tied to mergers and subsidiaries) has encouraged the installation of interconnected local networks. In the large multinationals, the role of ICT is evolving from mere instrumentation for reducing production costs and is becoming a growing support for strategic decisions and greater e-business interaction/ models. Sophisticated technologies and applications are less pervasive than in other manufacturing sectors, focusing mainly on intra-organisational processes and procedures. The core business areas are supply, production, logistics, services, and marketing and sales. Other critical areas now being targeted for improvement are packaging processes, the control of quality in hazard analysis and control critical points, the quality of the product, and the reverse SCM of returned products. In the production sector, verifying the quality of the raw materials is becoming increasingly important. The data used in this study are derived from the European e-Business Survey 2003. In total, 3515 telephone interviews with decision-makers in European enterprises in five EU member states (Germany, Spain, France, Italy and the UK) were conducted between 24 February and 20 March 2003. A follow-up study is on-going and involves 5000 enterprises (2005) from ten different sectors across seven EU member states. The field work was carried using computer-aided telephone interview technology. The decision-maker in the enterprise targeted by the survey was normally the person responsible for ICT within the company, typically the IT manager. Alternatively, particularly in small enterprises, which may not have a separate IT unit, the managing director or owner was interviewed. The role of ICT in the sector is still rather controversial. Despite the fact that, based on the results of the survey, 71% of the interviewed enterprises feel that e-business does not yet play a significant role for the company, it must be noted that for approximately 50% of larger enterprises and over 20% of small enterprises, e-business already represents a rather significant factor.

10.4.1

Online selling

Only 5% of companies use online selling. This percentage is slightly higher in the case of medium-sized enterprises (9%) and large enterprises (8%). Nevertheless, it must be emphasised that in the food industry online selling is less developed in comparison to other sectors, in which the average is a 16% rate of online selling. Spain and the UK are the countries that use this sales method the most, with 10% and 9% of companies selling online, respectively. France is the least oriented to online selling (only 2% of companies). The countries revealing the highest percentage of companies that are planning to introduce online selling within the next 12 months are Spain (11%) and the UK (13%).

10.4.2

Impact of online selling on companies

Online selling has proven to have a positive impact, above all in terms of the number of customers (an aspect cited by 64% of the companies that sell online). Moreover, although with a slightly lower percentage, its impact on the quality of customer service (58%) and on

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the efficiency of internal processes (57%) has been indicated as positive. There is also a significant percentage of companies that state a positive opinion about the impact of online selling on their sales turnover, a factor that 12% of the companies considered a ‘very positive impact’. The impact that online selling has on logistics costs and stock management is less positive. For this factor, over 65% of the companies stated that online selling has neither a positive nor a negative impact.

10.4.3

E-procurement

In contrast to online selling, which is used by 5% of the interviewed companies, online procuring (as in other sectors) has been developed more rapidly, playing a more important role in the sector. In fact, 19% of the sample companies use online procuring, although this percentage is lower than the average for other sectors, where the use of online procuring amounts to 33%. Large companies are the ones that mainly adopt online procuring (54% of the sample), but there is also a rather significant percentage of small companies that handle their purchasing online (19%). At a geographic level, online procuring is more widespread on average in countries like Germany (40%) and the UK (30%). Conversely, French companies are the least oriented towards e-procurement (only 6%). For 70% of companies (out of the total number of companies that use e-procurement), online purchases represent less than 5% of total purchases. This leaves a wide window for future online purchases.

10.5 10.5.1

PRECISION VINE GROWING WITH SATELLITE IMAGERY World wine production and consumption

At the beginning of the twenty-first century, estimates of the size of the global wine industry ranged from US$130 to US$180 billion in retail sales. Vineyards produced and sold three categories of wine: table (less than 14% alcohol by volume), dessert or fortified (greater than 14% alcohol), and sparkling (champagne). World wine production is highly fragmented. There are over one million wine producers worldwide, but no firm accounted for more than 1% of global retail sales. In sharp contrast, the wine market is highly concentrated in western countries. For example, the top 20 firms controlled 75% of the US wine industry. In the European Union, the wine market is dominated by retailing, although Europe is traditionally the place to produce and consume wine. Three EU countries, France, Italy and Spain, account for one-half of the world’s supply of wine, and the EU for 75% of worldwide supply. The ‘New World’ wineries, in countries such as Australia, Chile, South Africa and the USA, have increased their share of the global market in the past two decades, while wine production declined dramatically in ‘Old World’ countries, particularly in Europe. The New World producers have invested a lot in promising technologies and innovations in order to compete with old players in the world market. For example, New World producers introduced machined-harvesting of their grapes, while hand-picking is more common in Europe. Another technology that has been explored in New World countries is satellite imaginary, used to create efficiencies in production and quality control across the wine supply chain.

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10.5.2

173

World wine marketing and distribution

The number of companies involved in the supply of still wine remains very large. Branded wines are important for new entrants to the market but, as consumers become more experienced, they have become more interested in experimenting. The grocery sector continues to win an increasing share of sales, with the multiples dominant. These can offer a very comprehensive range, keen pricing and adequate information and guidance for most consumers. Multiple grocers are also becoming increasingly proactive in sourcing wines directly from producers and in specifying which types of wine will appeal to their customers. Grocery multiples, and to a lesser extent the larger multiple specialists, continue to dominate sales. As interest in wine has grown and the choice available has expanded, so the retailers have allocated more shelf space to it, and it is only the larger outlets that can stock a comprehensive range. It is not just the consumers who have become more knowledgeable and discerning. The major retailers have also become much more sophisticated, knowing what the wine drinker wants and dealing directly with producers.

10.5.3

Use of satellite imagery in winemaking

As noted in Wine Spectator (2008): In the 1990s, the Robert Mondavi Winery explored the benefits of imaging in response to an outbreak of phylloxera, and the results were effective. Scientists at the NASA Ames Research Center got a close-up view of the aphid infestation. In 2003, Mondavi, along with Dehlinger Vineyard, took part in a USDA [US Department of Agriculture] study of the vineyard that used ground-penetrable radar to determine soil moisture […]. The findings showed where and when to irrigate and harvest. Mondavi continues to use high resolution imaging to help with vineyard management. Once a year, staffers receive a detailed report and photo for each vineyard showing Normalized Differential Vigor Index, a measurement based on high-resolution imaging that color-codes the vineyard based on moisture, fruit and leaf growth, and other factors. In 2003, the European Space Agency (ESA), headquartered in Paris, and the European Commission formed their own vineyard satellite imagery program, called Bacchus, that captures images at extremely high resolutions to assess different vineyard parameters, including slope, altitude, sun exposure, soil conditions, and even acidity and Brix levels [Brix is a term used to measure the sugar content of grapes, grape juice or wine]. The ESA is currently testing Bacchus in Italy’s Frascati region, just south of Rome, with the help of various Italian partners. The project incorporates high-resolution images from space and air using a network of sensors, both orbital and on the ground, that track environmental activity in the vineyards and show the results in real time via Internet-based software.

10.5.4

The application – oenoview

Faced with declining sales in recent years, French vintners – particularly smaller producers – hope to gain a competitive edge over their New World rivals and immediate neighbours Italy and Spain. Disease prevention and treatment directly affect vine quality and vigour, and therefore there is a need for improved disease management. In 2009 a study by the Credoc French research centre showed that Spain could permanently overtake France as the world’s biggest wine producer as early as 2015 because

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Spanish wine growers were improving the yield of their vines while the French were cutting back (Credoc, 2009). As a result, wine producers turned to new technologies to gain a competitive advantage. The primary aim of oenoview was to help wine growers manage their work effectively – in terms of pruning, fertilising, stripping, etc. – and to reduce their production costs. Oenoview targeted the following two groups. The first was growers looking to make their vineyards more profitable. The value-added feature of oenoview is its provision of detailed maps for each field, thus allowing growers to adjust pruning and fertiliser inputs as well as to organise maturity checking and harvesting to obtain the required grape quality. Oenoview also helps to make irrigation more efficient, thereby reducing annual water costs. Secondly, the system assists winemaking organisations who obtain grapes from a large number of fields: precise characterisation of the estimated vine vigour and in-field variability for each field over large regions enables winemakers to better manage grape harvesting, that is, to harvest the best grapes at the same time and put them in the same vat to improve wine quality. Oenoview has already received recognition from Q@LIMEDiterranée (http://qalimediterranee. b2bmatchmaking.com/p_index.php), a competitiveness cluster in the Languedoc-Roussillon region focusing on sustainable agro-food systems and quality of life in the Mediterranean.

10.5.5

The profile of the companies involved

10.5.5.1

Infoterra

Infoterra is a leading provider of geo-information products and services for managing the development, environment and security of our changing world. Infoterra provides operational products and services across the entire geo-information spectrum – data acquisition and processing, imagery analysis and interpretation, hosting and delivery of large datasets – as well as offering GIS development and consultancy. The company: ● ●

●

●

● ●

●

has 550+ staff in France, Germany, Hungary, Spain, the UK and China; operates across a comprehensive range of markets, including environment, utilities, oil and gas exploration, telecommunications and defence and security; holds the exclusive commercial exploitation rights for the high-resolution radar satellite TerraSAR-X; has global customers, including international companies, national, regional and local governments, as well as authorities such as the European Commission and the European Space Agency; is complemented by a global partner network, ensuring a local presence; is a wholly-owned subsidiary of Astrium, Europe’s leading satellite systems and services specialist; together with Spot Image forms the Spot Infoterra Group, the Earth Observation division of Astrium Services.

10.5.5.2

Institut Coopératif du Vin

Institut Coopératif du Vin (ICV) is a cooperative structure providing technical, organisational and strategic support for all stakeholders in the wine and grape-growing sector. The ICV is a cooperative company founded in 1946 and based in Montpellier, which has a

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mission to ensure the analytical control of wines. Over the decades, this mission has considerably widened. Together with winegrowers, the ICV has actively participated in many developments, such as changes in grape variety planting, wine-making techniques, winery equipment and the style of wines. Its core competencies cover three areas: (i) wine expertise through a team of 60 consultants; (ii) wine and grape analysis in its 10 certified laboratories; (iii) selection and distribution of products adapted to Mediterranean wines. With 70 technicians and 60 oenologists, the ICV is dedicated to research into the improvement of wine quality along the Mediterranean basin and the Rhône Valley. It produces over 800 000 analyses per year and has more than 1200 clients. The ICV is a member of the OIV experts’ board (technology and analysis groups), the EC oenological practices expert group and the AFAQ-AFNOR food industry expert committee. It participates in regional research and development groups (Languedoc-Roussillon, Institut Rhodanien, Centre du Rosé) and has created a research network with 10 leading cooperative wineries in order to assess new techniques and new tools. It is in the process of creating a ‘good diagnosis practice’ guide for dissolved oxygen management. To remain at the cutting edge, ICV is engaged in research, development and innovation, and is continuously tracking new technologies.

10.5.6

Operations management

Oenoview is based on image-processing technology. Using innovative technology, Infoterra uses high-resolution satellite imagery to generate geographical data on vineyards – the number of leaves per square metre, the density of vegetation cover, etc. The information is displayed on maps, and is then analysed and discussed by wine-growing specialists at the ICV. Oenoview allows the wine grower to see the differences in grape quality and ripeness from one plot of land to the next (or even within the same plot of land) so they can harvest the grapes separately when different varieties are ripe. This results in high-quality wines. ‘We compare what we see from up in the sky to an ideal growth model of the plant based on various biophysical parameters, such as the number of leaves per square metre or the fraction of canopy per surface unit,’ says Henri Douche, head of development for oenoview. Satellite imagery allows winemakers to quickly access information that it would normally take 20 or 30 years to acquire in an empirical way. Furthermore, wine makers receive not only maps, but recommendations as well, all delivered on data-storage media. Therefore, decision-making is accelerated and wine makers can make informed decisions, in comparison to the estimates or empirical guesses that were used in the past. Jointly developed and operated by the ICV and Infoterra, and in collaboration with the Institut National de Recherche Agronomique, oenoview is an innovative service designed to answer these needs, assist cooperatives and vineyards with grape selection, and boost vineyards’ profitability. Oenoview is an extremely specialist service, based on the analysis of satellite imagery, which carefully monitors vine growth and identifies differences in grape quality from one plot of land to the next – or even on the same plot. Oenoview is therefore tailor-made for wine growers looking to offer customers the best quality wine. Using innovative technology, Infoterra uses high-resolution satellite imagery to generate geographical data on

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vineyards – the number of leaves per square metre, the density of vegetation cover, etc. The information is displayed on maps and is then analysed and discussed by wine growing specialists at the ICV. The primary aim is to help wine growers manage their work effectively – in terms of pruning, fertilising, stripping, etc. – and to reduce their production costs. Based on aerial and satellite imagery analysis that gives a spatial view and helps in characterising in-field variations, oenoview precisely maps vineyard vigour and provides indications of bunch and grape weight, soil water-retention and grape composition at different points within a field. The technology, which combines satellite imaging and aerial photographs, can show detailed, near-infrared images of the water level of the soil, the amount of leaf canopy surface area, the size of grape clusters and the presence of certain minerals. It can also track the spread of disease and help pinpoint vine vigour. The service is relatively expensive, but oenoview has promised to cap the price at €30 per hectare, with rates destined to fall as more producers sign up. There is also competition. In 2003, the European Space Agency (ESA), headquartered in Paris, and the European Commission formed their own vineyard satellite imagery programme, called Bacchus. This system captures images at extremely high resolutions to assess different vineyard parameters, including slope, altitude, sun exposure, soil conditions, and even acidity and Brix levels. The ESA is currently testing Bacchus in Italy’s Frascati region, just south of Rome, with the help of various Italian partners. The slopes of Frascati overlooking Rome boast rich, volcanic soils: wine has been produced there since time immemorial. However, the latest vine crop should go down in history as the best-documented harvest ever. Part of Frascati’s controlled denomination of origin – the Denominazione d’Origine Controllata (DOC), a wine’s legally demarcated home region – was surveyed in ultra-fine detail using an airborne radar sensor both before then after October’s harvest. This twostage ESA campaign was called BACCHUS-DOC, and was intended to complement a number of radar and optical satellite acquisitions by ERS-2, SPOT, Landsat, IKONOS and QuickBird. Following processing of the raw data, the results were studied by a team from ESRIN, ESA’s European Centre for Earth Observation, located within the area of study, and the nearby Tor Vergata University. In particular, they investigated to what extent the BACCHUSDOC airborne and satellite radar imagery is sensitive to vineyard surfaces and the change in biomass following the grape harvest. ‘We have been demonstrating the potential use of satellite radar imagery from ERS and Envisat for correlating the radar signal with the vineyard biomass, and in particular the “grape biomass” ’, said Luigi Fusco of ESRIN. ‘The early results – applying detailed geographical information gathered on the area during previous projects – have shown that this correlation exists, and this detailed analysis is proving worthwhile.’ BACCHUS-DOC was overseen by ESA’s dedicated campaigns unit, with the participation of the German Aerospace Centre (DLR) and Rome’s Tor Vergata University, whose personnel carried out the accompanying ground measurements. The campaigns unit and the Bacchus team selected a 24.5 km2 area of study, with the orientation fitting the orbit and the orientation of the ERS-2 radar at that time. For their part in the campaign, DLR operated their Experimental Synthetic Aperture Radar (E-SAR), flown on a customised Dornier-228 flown out of nearby Ciampino Airport. The E-SAR has a maximum spatial resolution of 4 metres and operates at five different radar

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wavelengths, with selectable polarisation – a means of increasing signal sensitivity to different environmental variables. Such performance is superior to the current generation of radar satellite sensors but presents a way to simulate the results available from future space-based instruments. According to the terradaily reports (http://www.terradaily.com), the initial E-SAR flight took place on 5 October 2004, with a follow-up on 25 October. In the meantime the harvest took place. Highly radar-visible corner reflectors were placed at various places within the area of interest to act as reference points. The precise aircraft route was tracked using GPS, backed up by an onboard inertial navigation system (INS). ‘The SAR image acquisitions were accompanied by contemporary ground measurements on the vineyards,’ explained Professor Domenico Solimini of the Tor Vergata University. ‘An extensive survey identified the general conditions of vegetation and of the terrain in a wide area of the Frascati wine production zone. For the second overflight, when the grapes had been harvested, only the parameters of stable structures were the same, so only the variable elements were monitored, such as leaf height, distribution and dimensions, number of leaves per unit area, roughness and moisture of the terrain, plus weed height.’ The main scientific objective of BACCHUS-DOC was to investigate the sensitivity of polarimetic radar in measuring grape biomass, as well as additional useful parameters for inventorying and characterising vineyards, such as vine row spacing and orientation, and vineyard borders. The potential to estimate local soil roughness and moisture is also being assessed. Frascati was selected for the BACCHUS-DOC campaign because a dedicated geographic information system (GIS) has been constructed for this DOC area as part of a European Commission-funded project called Bacchus, aimed at applying Earth observation and GIS technology to improve European wine quality. Bacchus is now complete, but a follow-on project called DiVino is extending the capabilities of the Frascati GIS.

10.6

CONCLUSIONS

A key challenge from the perspective of the food and beverages industry is to improve the production process and product innovation. SMEs should be encouraged to use innovation to produce higher margins and higher-value products. More participation in global value chains and marketplaces will assist commercialisation. Access to new markets and business partners should also be supported. Working with key players will help SMEs to access distribution chains and new markets. Fragmentation, which is typical in Southern Europe, creates both supply inefficiencies derived from dynamics (the Forester Effect) and – perhaps more critically – ineffectiveness in safeguarding food quality and safety. Food tracking and tracing requires, to a large extent, supply-chain integration. Food traceability is hard to implement without the help of modern technology and e-business applications. E-business technologies can create market transparency, allowing consumers to track all the relevant information about the food they eat. This raises consumer confidence and trust in the integrated supply chain. Until recently, companies in the food and beverages industry have used e-business mainly to improve their internal processes and procedures. For centuries Europe has been one of the world’s great wine-producing regions, although cultivation practices are often inconsistent and expensive. With global competition growing,

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the hope is to develop information tools that combine aerial and satellite imagery with GIS technology in support of vineyard management and improving wine quality. Satellite imaging has an impact on wine producers. Although it is a slow process it can create benefits. Even for small vineyards, there could be differences, i.e. one area may be poorer than another. GIS technologies, such as oenoview, can pinpoint these differences and let wine producers manage their fields better, i.e. give a vine more water, different pruning, a little more or less fertiliser. Such advanced technologies certainly raise a question of cost for small companies, yet wine cooperatives can often afford such costs, as in the case of ICV. Furthermore, oenoview technology is the start of traceability of quality in the winemaking process. The quality wine produced can be traced back to its source: its vine.

REFERENCES Chandler, A.D. (1990) Scale and Scope. Belknap Press, Cambridge, MA. Credoc (2009) Available at: http://www.credoc.fr/. Deutsch, A., Fernandez, M., Florescu, D., Levyd, A. and Suciu, D. (1999) A query language for XML, Computer Networks, 31, 1155–1169. E-business Watch (2003) ICT & e-Business in the Food, Beverages & Tobacco Industry, Sector Report No.1 III, The European e-Business Market Watch, July. Available at http://www.e-business-watch.org/. Gunasekaran, A., Marri, H.B., McGaughey, R.E. and Nebhwani, M.D. (2002) E-commerce and its impact on operations management, International Journal of Production Economics, 75, 185–197. http://www.infoterra-global.com/oenoview.php. http://www.telegraph.co.uk/news/worldnews/europe/france/3103054/French-wine-growers-use-satellitesto-harvest-grapes.html. Humphrey, J. (2002) Business-to-business e-commerce and access to global markets: exclusive or inclusive outcomes? Institute of Development Studies, Globalisation and Poverty Working Paper, Brighton. Iijima, M., Komatsu, S. and Katoh, S. (1996) Hybrid just-in-time logistics systems and information networks for effective management in perishable food industries, International Journal of Production Economics, 44, 97–103. Loebbecke, C. and Powell, P. (1998) Competitive advantage from IT in logistics: the integrated transport tracking system, International Journal of Information Management, 18(1), 17–27. Myoung, K., Park, S., Yang, K., Kang, D. and Chung, H. (2001) A supply chain management process modelling for agricultural marketing information system, EFITA, 3rd Conference of the European Federation for Information Technology in Agriculture, Food and the Environment, Montpellier, France, June 18–20, 409–414. Narayanan, S. (1997) Home shopping: the way of the future is here, Retail World, 50(20), 6. Van der Vorst, J.G.A.J., Beulens, A.J.M., De Wit, W. and Van Beek, P. (1998) Supply chain management in food chains: improving performance by reducing uncertainty, International Transactions Operational Research, 5(6), 487–499. Verhoef, P.C. and Langerak, F. (2001) Possible determinants of consumers’ adoption of electronic grocery shopping in the Netherlands, Journal of Retailing and Consumer Services, 8, 275–285. Vlachos, I.P. (2004) Investigating the adoption of electronic data interchange by agribusiness organizations, Journal of International Food & Agribusiness Marketing, 16(1), 19–42. Wine Spectator (2008) Winemakers need space to make good wines: Advancements in satellite imagery may help some vignerons grow the perfect crop, September 2008. Available at: www.winespectator.com.

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The Impact of Information and Communication Technologies on the Organisational Performance of Microenterprises: Evidence from Greece

Ilias Vlachos and Panayiotis Chondros

11.1

INTRODUCTION

The contribution of small and medium-sized enterprises (SMEs) to global entrepreneurship and prosperity is colossal. It has been widely recognised that the survival and success of SMEs is crucial to any nation’s economic stability. To this end, governmental incentives around the world provide increasing resources and support, financing programmes to motivate and maintain SME performance. According to the national body for SMEs in Greece, it is estimated that in the EU, more than 99% of 20 million businesses are SMEs. In Greece, the percentage of SMEs is estimated to be 87.7%, sixth highest of the EU-15 (EOMMEX, 2007). Additionally, in the geographical area of Peloponnese in Greece, where the data for this survey were collected, it is estimated that the number of SMEs is almost 5% of the total number of businesses, while SME revenue is estimated at around 2.2% of annual revenue of Greek entrepreneurs (http://www.eommex.gr). SMEs are not very different from larger businesses in terms of business objectives: SMEs aim to produce quality products and services by implementing cost-benefit policies (Iansiti and Levien, 2004). Information and communication technology (ICT) can potentially alter industry structures and the rules of competition by creating competitive advantage and new business opportunities. ICT adoption is a key strategy in supporting a firm’s operation, creating strategic advantages in both micro and macro environments. During the last three decades, there has been no conclusive evidence that the adoption of ICTs has had a direct effect on productivity and profitability. However, a number of recent studies have produced valid and reliable evidence for this. In particular, Auramo et al. (2005) have stated that the contribution of ICT to productivity is significant, providing increased profitability, quality improvement and time-lag benefits. Markides and Anderson (2006), meanwhile, highlighted the relation between ICT and the micro business environment on how ICT can identify challenges on customer demand and new segmentation marketplaces. In doing so, researchers has showed that productivity paradox is not valid any more and ICT do have an effect on firm performance, including SMEs. Intelligent Agrifood Chains and Networks, First Edition. Edited by Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis. © 2011 by Blackwell Publishing Ltd. Published 2011 by Blackwell Publishing Ltd.

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The implementation of ICT in SME operational processes has varied greatly and has led many researchers to make criticisms (Matlay and Addis, 2003; Oliver and Porta, 2006; Lasch et al., 2007). For example, Saarenketo et al. (2004) measured the influence of ICT on business performance as related to the knowledge management process, while Boonstra and De Vries (2005) went a step further, measuring the influence of ICT on inter-organisational procedures such as alliances and economic and political barriers. Moreover, Kohn and Husig (2006) urged that integration of ICT can provide innovation, while Spanos et al. (2002) tried to evaluate the relationship between ICT adoption and management theory, finding out that SMEs, particularly those in Greece, have great resistance to external threats due to the lack of suitable ICT systems. This chapter is organised as follows. Section 11.2 presents the main aspects that characterise the effects of ICT adoption on business performance among 62 SMEs in the geographical area of South Greece, the Peloponnese. The results are primarily compared with the adoption of the governmental programme ‘Go-Online’ in the whole geographical area of Greece for the same period (July 2006). Section 11.3 discusses the methodology followed, providing notes for the governmental programme ‘Go-Online’. Section 11.4 presents the data analysis, which is divided into two parts. First, the demographic and ICT application variables are revealed and then the factorial analysis is presented. Finally, sections 11.5, 11.6 and 11.7 conclude the paper by summarising the most critical findings and suggesting areas for further research.

11.2 LITERATURE We reviewed the literature on ICT factors that affect SME performance.

11.2.1 ICT compatibility with human resources practices, management, education, training, trained personnel and skills SMEs are standardising many of their business processes and building an integrated platform of ICT applications that cover areas such as human resources. Lee and Bai (2003) made a model, trying to investigate the measurement of how ICT can potentially enhance employees’ performance. They found that learning procedure is a continuous process that all members of business unit have to follow if they want to provide innovative solutions. Indeed, this strategic path is more critical nowadays due to the changing external and internal environments of companies (Dietz et al., 2006). Executive ICT models providing training and learning capabilities for SME employees can be critical paths for overcoming traditional barriers such as lack of financial resources, time, expertise and facilities (Sambrook, 2003). The need for ICT integration supporting human capital investments is recognised in the model of Martin and Matlay (2001), who suggested the importance of ICT implementation during the initial stages of business operation (Lloyd-Reason et al., 2002). Additionally, Lloyd-Reason et al. (2002) suggested that training and learning models can successfully interact in inter-firm cooperation by improving a firm’s capabilities, as could happen to the research and development department, a fact that can lead to innovative attitudes. So, recruitment and learning have to leverage the ICT process by enhancing managerial skills. Both researchers proposed that organisational mechanisms, such as training personnel with ICT skills, are critical to business success.

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Morgan et al. (2006) went one step further by trying to investigate the impact of ICT advisors on business performance. Although they highlighted the significant contribution of ICT to business success, they suggested that business goals can be successfully implemented by appropriate individuals’ efforts. The contribution of ICT training therefore also has a significant effect on employees’ presentation and business performance. Morgan et al. (2006) carried out empirical research by providing knowledge to a number of employees, aiming to familiarise them with ICT. The variables they measured included operation and technological structure, individual efforts and development. They concluded that an ICT training model can be successfully adopted with long-term interactions only if it is modified to the needs of SMEs and continuously repeated on a regular basis. These findings are consistent with the results of Lawless et al. (2000) when they proposed the Learning Support for Small Business (LSSB) online training model. Additionally, Jutla et al. (2002) applied a model of effective ICT adoption to business operations based on governmental incentives, measuring the relation between employees’ education and business performance. They found out that successful ICT applications, such as website construction and usage through e-commerce, are significantly dependent on appropriate knowledge management and effective training, especially in small businesses. SMEs tend to adopt a more informal training model in comparison to larger companies, which can afford a more sophisticated learning procedure (Tanova, 2003). In such cases, government policy should support training programmes offering incentives to SMEs to adopt ICT applications by offering financing help for the continuous practice of innovative technologies. However, an effective training policy oriented to technological infrastructure is a matter for school education. Lloyd-Reason et al. (2002) argued that workers who were familiar with technology through their school education were more motivated and capable of adopting new ICT applications. Hence, governmental policies have to incorporate training and not be restricted to financial incentives. We therefore proposed hypothesis 1: ICT compatibility is positively dependent on human resource (HR) practices.

11.2.2 The impact of ICT on SME performance SMEs aim to benefit from ICT implementation and their ability to build and sustain close relationships with both customers and suppliers. This business objective can be achieved by adopting new ICT resources that can provide a key competitive advantage and facilitate the search for niche marketplaces and profitable promotional channels in both the domestic and global markets (Martin and Matlay, 2001). Galloway and Mochrie (2005) tried to evaluate the impact of ICT on the business performance of rural firms. They found there was a significant effect of the internet and ICTs on the relation between the business inter-organisational process and the business external environment. However, they stated that this dual-band relation is differentiated among business and industrial sectors because of alternative ICT policies adopted in several organisational areas. Differentiated ICT does not encompass a standard set of applications that conform to corporate-wide automation in business processes. Each strategic project can be a unique effort, and the number of unique or custom strategic projects in leading enterprises appears to be growing. Nevertheless, Markides and Anderson (2006) implied that ICT adoption is crucial for strategic innovation only at the beginning of strategic orientation and only if ICT implementation supports business strategies that create ‘who, what, how’ innovations by overcoming

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previous value chain limitations. This means that business performance can be positively modified not only by adopting ICT’s inimitable and sufficient applications, but ICT implementation can potentially provide cost-effective solutions and be the source for quicker scale-up to innovation and modification. In contrast, large corporations can take advantage of their greater capability for technological and asset investments, and successfully integrate standard ICT projects across sales, distribution, HR, manufacturing and finance functions. This alignment increases corporate agility, functionality and financial procedure by leveraging cost. Therefore, we proposed hypothesis 2: SMEs’ performance positively influences overall ICT adoption.

11.2.3 Perceived safety, trust and online transactions Wilson (1997), trying to measure the relation between safety and business performance to electronic transactions, pointed out four factors that are vital for safety on the internet: authenticity, integrity, non-repudiation and confidentiality. These are crucial issues for building business-to-business (B2B) and business-to-consumers (B2C) safety, which in turn is a fundamental factor for a good long-term relationship between company, customers and suppliers. Associated with the trust that is generated from safety, Ratnasigham (1998) urged that online applications such as transactions and communication demand trust in order to appropriately operate the online model. Ballantine (2005) suggested that the greater the interactivity of an effective website, the more trustworthy it is perceived to be. Helpful and quick navigation can increase trust and increase the potential for online transactions. Similarly to Wilson, Madu and Madu (2003) pointed out the importance of security and trust in online transactions. Cho and Park (2003) highlighted the significance of a safe transactions on ICT systems in order for this application to be widely accepted, especially in the retail sector. Safety in turn creates confidence in B2C and B2B relationships, an issue that Tamini et al. (2000) supported in their studies of the privacy policies of transactions among large businesses. Ribbink et al. (2004) suggested a model measuring online loyalty based on the role of trust in business operations. They found that trust is not affiliated only with willingness for customers’ transactions but lack of trust can be a negative consequence for a firm’s reputation with suppliers, customers and the public sector. However, the implication of safe electronic transactions has a significant impact on the supply chain by positively leveraging the value chain, reducing costs and allowing the most appropriate suppliers and intermediaries with the lowest prices to be found (Houghton and Winklhofer, 2004; McIvor and Humphreys, 2004). In addition, an electronic transaction is an online procedure that has implications for internal and external business operations. Mullane et al. (2001) pointed out the trust of online applications for effective cost-benefit gains associated with low-price products from foreign markets. Indeed, trust has a great impact on a firm’s reputation, providing opportunities for global collaboration with wellknown suppliers, which will have a positive effect on a firm’s products. This means that online ordering is geographically limitless, which gives to business an important advantage. We therefore proposed hypothesis 3: Perceived safety, trust, and online transactions are positively influenced by ICT adoption. Figure 11.1 depicts the hypotheses between the ICT measure and the performance variables. There are three ICT variables (ICT compatibility with Human Resources, the perceived impact of ICT on business performance, and perceived safety, trust) that hypothetically relate to SMEs’ performance via four performance measures: perceived competitiveness, perceived sales, perceived profitability and perceived sustainability.

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The Impact of Information and Communication Technologies Performance variables Perceived competitiveness

ICT measurements ICT compatibility with HR

H1

Perceived increased sales

The impact of ICT on business H2 performance Perceived safety, trust and online transactions

183

Perceived profitability

SMEs’ performance

H3 Perceived sustainability

Figure 11.1 Our empirically valid model. HR, human resources; SME, small and medium-sized enterprises.

11.3 METHODOLOGY 11.3.1 ‘Go-Online’ programme This study was based on the Greek Ministry of Development’s programme ‘Go-Online’ (http://www.go-online.gr), with participation from public organisations (universities), which aimed to present information about ICT adoption by Greek SMEs. The programme employed into two phases: financial support for renewing or purchasing appropriate hardware/software and internet access, and financial support for website construction and employee training. The purpose of the programme was to motivate SMEs to adopt ICT applications providing financing and training to allow SMEs to take advantage of new technologies. Only SMEs (0–10 employees) were allowed to participate in the programme, because its purpose was to reduce the gap in ICT adoption between large companies and SMEs. In aggregate, in total, 585 206 SMEs participated, 25 828 of them situated in the geographical area of Peloponnese.

11.3.2 The sampling procedure and sample The study was carried out in July 2006 in the Peloponnese, in South Greece. It is estimated that 1147 SMEs met size requirements, but only 65 of them were situated in the Peloponnese. Sixty-two (N = 62) structured questionnaires, from all the districts of the Peloponnesus area (Argolida, Messinia. Arcadia, Corinthia and Laconia), were collected, and a very high response rate of 95.4% was achieved. The questionnaire was pre-tested on randomly selected SMEs. Based on the results of the pre-test procedure, the final questions were refined. A random sample was selected from the SMEs that met the sampling criteria. The questionnaire was directly distributed to the respondents by our external co-operators. Table 11.1 shows the design of the survey questionnaire.

11.4 RESULTS Table 11.2 presents the demographics of the participating companies.

11.4.1 Demographic variables Number of employees: The survey sample of the research revealed that the majority of enterprises do not have a permanent number of employees (51.6%) while only 22.6% have one

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Table 11.2

Questionnaire design.

Section

Content

1 2 3 4

Demographic variables Information about internet Reasons for ICT adoption through ‘Go-Online’ Personal positions

Demographics.

Demographic variables

N (N = 62)

%

Number of employees 0 1 2–5 5–10 10+

32 14 9 5 1

51.6 22.6 14.5 8.1 1.6

Revenue (2005) (€) 0–50 000 50 001–100 000 100 001–200 000 200 001–400 000 400 001+

24 14 6 8 8

38.7 22.6 9.7 12.9 12.9

Sector Construction Food and beverage Service Commerce Other sectors

7 6 25 23 1

11.3 9.7 40.3 37.1 1.6

Expenditure (percentage of revenue) Business application Commercial Hardware Software Web construction

0%

1–5%

5–10%

10–15%

15+

37.1% 14.5% 27.4% 77.4%

54.8% 59.7% 51.6% 16.1%

3.2% 17.7% 14.5% 4.8%

3.2% 6.5% 3.2% −

− 1.6% 1.6% 1.6%

Note: Figures may not add up to 100% as some companies did not answer the relevant question.

permanent employee. This negative relationship grows as the number of employees increases, with the result that only 1.6% of enterprises have 10 or more permanent employees. Revenue (2005): Most enterprises (38.7%) had a turnover of €50 000, while 22.6% of enterprises had a turnover of €50 001–100 000. Sector: Regarding the sectors of micro-medium enterprises (MMEs), 40.3% are in services followed by 37.1% in the commercial area while only 11.3% are in construction and 9.7% in the area of food and beverage. Business application: This presents the percentage of expenses for enterprising activities associated with the turnover (in 2005) for the MMEs. It is obvious that only a small percentage of expenses, 1–5% of turnover, is invested in activities such as commercials, web construction, hardware and software.

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11.4.2 ICT influence on business performance variables Table 11.3A presents the ICT applications usage, the reasons for ‘Go-Online’ programme participation and the most widely used internet applications.

11.4.3 The effect of ICT applications on business performance The investigation of the factors that influence business performance has resulted in the following findings. IT infrastructure: The overwhelming majority of SMEs have elementary technological equipment, meaning personal computers (98.9%) and printers (98.4%). Regarding internet access, 80.6% of SMEs use the internet while services like email, online applications and online sales are used by 98.4%, 40.3% and 14.5%, respectively. Reasons for ‘Go-Online’ participation: The reasons for the SMEs’ participation in the educational programme ‘Go-Online’ were investigated. A fundamental reason for joining the programme was to learn to use office automation with software, such as Microsoft Office (74.2%). Technologies that concern production integration (9.7%), warehouse management (25.8%) and accounting software (12.9%) did not appear to constitute an important motive for using ‘Go-Online’ compared to the growth of commercial applications, which was shown to be a more important reason (37.1%). Internet applications: Regarding the use of the internet and the reasons for its application and use, companies often had more than one reason for using it. The most common reason for using the internet was browsing for information (77.4%). Other internet services, such as online banking (41.9%), e-commerce (procurement) (33.9%), online shopping (30.6%) and transactions with state-organisations of social security (27.4%) have an important impact on SMEs, while online recruitment (3.2%), e-commerce sales (14.5%) and legislation and sector news (16.1%) are less important. Reasons for ICT applications: Looking at what SMEs want when they use new information technologies and communications, particularly high in their preferences are service enhancement (72.6%), the online market place (56.5%) and an increase in competitive advantage (53.2%). E-mail usage: The reasons why SMEs use e-mail include because it is suitable for enterprising use (71%), direct communication (66.1%), communication with customers and suppliers (54.3% and 51.6%) as well as using it for communication with foreign customers or partners (16.2%).

11.4.4 Barriers to ICT adoption Table 11.3B presents the main barriers that are faced during the import and use of new technologies in MMEs. The most significant barriers are safety of data transactions (53.2%), the high cost of applications (45.2%) and hardware and software barriers (45.2%).

11.4.5 Factor analysis Principal component analysis with varimax rotation was conducted in order to assess the 26 ICT practices of the questionnaire (Table 11.4), measured on the Likert five-point scale (1 = very significant, 5 = not significant). The analysis reveals three ICT factors: (1) human resources compatibility with ICT, (2) ICT impact on SME performance, and (3) perceived

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ICT applications. N (N = 62)

%

IT infrastructure E-mail Printer Personal computers Internet access Laptop Online applications Online sales

59 61 57 50 26 25 9

95.2 98.4 91.9 80.6 41.9 40.3 14.5

Reasons for ‘Go-Online’ participation Office automation Commercial applications Warehouse management Accounting software Production integration MIS Internet access

46 23 16 8 6 5 2

74.2 37.1 25.8 12.9 9.7 8.1 3.2

Internet applications General reasons Voice mail B2G Online banking E-commerce (procurement) Online shopping Competitors’ news E-learning-HRM Promotion through website Legislation and sector news E-commerce (sales) Online recruitment

48 47 37 26 21 19 16 14 11 10 9 2

77.4 75.8 59.6 41.9 33.9 30.6 25.8 22.6 17.7 16.1 14.5 3.2

Reasons for ICT applications* Cost benefit Profitability Competitive advantage Online marketplace Service enhancement E-mail usage* Feedback conduct Language reasons Safety Online orders CRM SCM Direct communication

50.0 50.0 53.2 56.5 72.6 2 10 11 24 33 32 41

3.2 16.2 17.8 38.8 54.3 51.6 66.1

HRM, human resource management; MIS, management information system; B2G, Business-to-Government; CRM, customer relationship management; SCM, supply-chain management. *Respondents could select more than one factor, so figures do not add up to 100%.

safety/trust and online transactions. Furthermore, Table 11.4 shows that factor 1 accounts for 17.4% of the variance, factor 2 accounts for 14% of the variance and factor 3 accounts for 2.3% of the variance. We used the Anderson–Rubin method, which ensures the orthogonality of the estimated factor scores.

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Table 11.3B

Barriers to ICT adoption.

Barriers to ICT adoption*

N (N = 62)

% (N = 62)

18 25 26 27 28 28 33

29.1 40.3 41.9 43.5 45.2 45.2 53.2

Long-term procedure Language barriers Knowledge management Executive personnel Cost Hardware and software barriers Safety reasons

* Very significant or significant. Table 11.4

Rotated factor loadings for three performance practices*. Factors 1 Compatibility ICT–HR

Executive recruitment is significant for ICT adoption Current employees need to enhance their education with seminars for ICT usage Ad hoc education is crucial for ICT adoption Government support of employee training helps adoption of ICT Employees need continuously to enhance their education The governmental trainee programmes for ‘Go-Online’ were useful Our competitors’ online CRM applications are greater than ours Our customers demand enhancement of our online applications Our competitors have already adopted ICT Our suppliers demand enhancement of our online applications Our company has the appropriate infrastructure for ICT adoption The current expenditure for ICT adoption is great Internet improves our exports Our competitors’ profitability is greater than ours due to ICT adoption We feel unsecure when using the internet Online transactions are not safe Safety is a significant part of internet transactions Internet cost is great ICT cost too high Eigen values Initial percentage of variance explained Rotation sum of squared loadings (total) Percentage of variance explained Cronbach a (sample N = 62)

2 SME performance

3 Safety

0.868 0.755 0.721 0.685 0.647 0.604 0.791 0.658 0.648 0.638 0.581 0.519 0.518 0.473 0.869 0.785 0.712 0.487 0.428 6.836 25 319 4 693 17 380 0.862

3.919 14 513 3 770 13 965 0.825

2.509 9 293 3 325 12 313 0.797

* Extraction method: principal axis factoring; rotation method: varimax with Kaiser normalisation. Rotation converged in four iterations.

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Table 11.5

Means, standard deviations and correlation matrix. Mean

SD

1

2

3

4

5

Control variable 1. Revenue

2.50

1.515 1

0.057**

0.083**

0.120**

0.151**

Firm performance 2. Perceived competitiveness 3. Perceived increased sales 4. Perceived profitability 5. Perceived sustainability

2.22 2.60 2.16 1.92

1.093 1.278 1.167 1.140

1

0.552 1

0.373 0.477 1

0.247* 0.286* 0.606 1

0.365* 0.458 0.220**

0.347* 0.577 0.108**

0.687 0.311* 0.010**

0.538 0.379* 0.129**

ICT variables 6. HR compatibility 7. SME performance 8. Perceived safety, trust

−0.078** 0.160** −0.079**

* Correlation is significant at the 0.01 level (two-tailed); ** correlation is significant at the 0.05 level (two-tailed).

The reliability of the factor loadings was measured using the Cronbach alpha (a) test. Factor 1 (seven items) was measured to be Cronbach a = 0.862, factor 2 (eight items) was Cronbach a = 0.825 and factor 3 (five items) was Cronbach a = 0.797.

11.4.6 Univariate analysis Table 11.5 presents the Pearson correlations analysis. Control variables (revenue) showed low correlation with performance variables (perceived competitiveness, perceived increased sales, perceived profitability and perceived sustainability) as well as with every ICT variable. In contrast, SME performance variables showed significant correlation only with factor 2. In particular, HR compatibility has significant association with perceived profitability (R2 = 0.687) and sustainability (R = 0.538), but has low correlation with the control variable (R2 = 0.078). ICT impacts on SME performance have significant correlation with perceived increased sales (R2 = 0.577) and perceived competitiveness (R2 = 0.458), and has credible correlation with control variable revenue (R2 = 0.160). Finally, perceived safety, trust and online transactions have significant correlation with perceived competitiveness (R2 = 0.220), while they have no significant correlation with the control variable (R2 = –0.079).

11.4.7 Hierarchical regression We conducted hierarchical multiple regression in order to assess the association between dependent (firm performance) and independent (ICT) variables. First, we entered the control variable (firm size) in step 1 of the regression equation. Firm size is the control variable measured by number of employees. Step 2 included the four performance variables (perceived competitiveness, perceived increased sales, perceived profitability and perceived sustainability) in the regression equation. Finally, step 3 included interactions along with the control variable (firm size) and ICT variables. Table 11.6 presents the results of hierarchical multiple regressions. In particular, the ICT variables are significantly predicted by perceived profitability. (F = 16.453), while all the other independent variables significantly contribute to the dependent variable. The beta weights indicate that HR compatibility with ICTs and ICT impact on SME performance

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contribute most to predicting perceived profitability and perceived sustainability. The change at adjusted R square (0.564) indicated that 56.4% of R square can be corrected in order to closely reflect the goodness of fit of our model. The other performance variables also showed a significant effect on ICT variables, especially perceived increased sales (F = 10.886, change in adjusted R square = 0.469), perceived sustainability (F = 9.999, change in adjusted R square = 0.437) and perceived competitiveness (F = 7.552, change in adjusted R square = 0.383). The ICT variables HR compatibility and ICT impact on SME performance were significant predictors for all the dependent variables, thus supporting hypotheses 1 and 2. Furthermore, Table 11.6 shows the correlation between performance variables and interactions of factor analysis findings. Our model indicates low correlation (low change in adjusted R square) for the measurements variables and also F significance. However, the perceived sustainability has the greater F significance. Additionally, the factors’ interactions have greater beta and t significance values supporting hypothesis 3.

11.5 DISCUSSION We investigated the impact of ICT on Greek SMEs participating in the government programme ‘Go-Online’ in the geographical area of Peloponnesus, in Greece. The demographic analysis indicated that programme was mostly adopted by SMEs managed only by a director, with no permanent employees. This did not surprise researchers as they knew the aim of this programme was to support micro-SMEs with low revenue and to provide the appropriate financial support for technological innovation. Regarding the high rate of e-mail adoption, we believe that this is because SME owners focused quickly on taking advantage of e-mail communication for promotion and commercial issues (Arbore and Ordarini, 2006). The results also indicated that the main reason for ICT application was hardware innovation. This could be because SMEs attempted to improve their customer and supplier facilities using e-mail applications to enhance their internal/external operation through improvement in the handling of received/sent information. Office automation contributes positively to this aim. Additionally, the analysis indicated that the great majority of SMEs used the internet for general reasons, general navigation, market investigation, e-mail communication and contact with public and bank services. This means that SMEs wanted to take advantage of digital facilities to avoid the usual bureaucratic costly and time-consuming procedures that are barriers to the daily operation of SMEs. Indeed, this could be verified from the fact that cost-benefit is the main reason for ICT application, an approach supported by Lohrke et al. (2006). Conducting factor analysis, we identified that respondents correlate ICT adoption with HR compatibility, performance and safety. In addition, univariate analysis indicated high correlation of HR with perceived profitability and sustainability, SME performance with perceived sales, and perceived trust/safety with perceived competitiveness. As the theoretical section of this research supported, the ICT acceptance for early ICT adopters is mostly related to HR and training issues. The more familiar employees are with new technologies, the better the results the SMEs have in their operation (Bengtsson et al., 2007). We suggest that suitable training models could allow SMEs to integrate individuals to business scope through ICT usage by improving the SME’s competitiveness. Barriers such as safety, hardware and software could be overcome through suitable training facilities (Motwani et al., 2006), showing employees how they can effectively use ICT capabilities and teaching them

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3.074* 4.023 1.704**

0.349 0.461 0.193

0.353 −0.013 0.007

0.863**

0.744 −0.005 0.014

0.120 7.366 2.947 0.015**

0.693 0.280 0.001

16.453 0.543 0.564

1.348**

0.129

0.490** 1.278** −0.179** 0.977 −0.002 0.061

0.072 0.197 −0.027

0.151

1.160 0.003 0.023

1.077**

3.105 5.602 0.698**

1.380**

0.543 0.344 0.122

0.143

9.999 0.414 0.437

5.046 3.164 1.130**

1.312**

Step 2 (ICT practices)

10.886 0.432 0.469

0.326 0.594 0.073

−0.147

Step 1 (Control variables)

Step 2 (ICT practices)

Step 3 (Interactions)

−0.617** 1.239** −0.324** −0.265** 0.684 −0.025 0.051

−0.594**

Step 1 (Control variables)

−0.092 0.193 −0.050 −0.044

−0.083

Perceived sustainability

7.552 0.335 0.383

0.769**

−0.089

Perceived profitability

*Significant at P < 0.01; **significant at P < 0.05.

F Adjusted R square Change in adjusted R square

Control variable 1. Firm size ICT practices 2. HR compatibility 3. SME performance 4. Perceived safety, trust Interactions Firm size 5. HR * Per of SME 6. HR * P safety/trust 7. Perf* P safety/trust

0.408**

0.167 −0.016 0.003

−0.057

Step 2 (ICT practices)

Step 1 (Control variables)

Step 3 (Interactions)

Step 1 (Control variables)

Step 2 (ICT practices)

Perceived increased sales

Perceived competitiveness

Hierarchical regression results of ICT variables on four performance measures and their interactions.

Control variable 1. Firm size ICT practices 2. HR compatibility 3. SME performance 4. Perceived safety, trust Interactions Firm size 5. HR × Perf 6. HR × P safety/trust 7. Perf × P safety/trust F Adjusted R square Change in adjusted R square

Table 11.6

−0.910** 0.547** 0.536** −0.727** 0.419 −0.047 0.027

0.104 0.233 0.113 0.118

1.066 0.005 0.060

0.695** 1.507** 0.732** 0.712**

Step 3 (Interactions)

−0.137 0.086 0.084 −0.122

Step 3 (Interactions)

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191

not to be afraid to use them. Hence, we accepted all the hypotheses we proposed showing the significant influence of ICT on SME operational processes.

11.6 MANAGERIAL IMPLICATIONS We investigated and present the status of Greek SMEs in Peloponnesus related to their participation to the governmental programme ‘Go-Online’. We identified the ICT infrastructure and main reasons for ICT applications, which can benefit owners of SMEs in exercising their entrepreneur power. Additionally, the results can help ICT advisors to propose more sophisticated ICT models for effective enhancement of SME operation. Training should be a priority to familiarise employees with the new ICT models (Macdonald et al., 2007). Furthermore, we suggest that continuous training is necessary to reduce the barriers to ICT adoption. The owners of SMEs can benefit from the results of this study to evaluate new trends in digital economy and apply new e-business models that could revolutionise the way they do business. E-business could be the managerial tool for SME differentiation, providing highquality products and services, and this should be exploited by SMEs (Iansiti, 2005).

11.7 LIMITATIONS/FUTURE RESEARCH The relatively small sample size was thought to be the most critical limitation of this study, an issue that was potentially overcome by the high questionnaire response rate. Data collection was bounded within the Peloponnese region and this could be also be a limitation, but this is unavoidable because of the adoption of ‘Go-Online’ in the specific geographical area of Peloponnesus. Future research could reveal useful information for the relationship between ICT practices and business operation accordingly to ‘Go-Online’ adoption. However, this future research should cover the whole geographical area of Greece in order to increase the effectiveness of the results. Additionally, the timeline of data collection should cover the whole adoption of the government programme, not just one part as this research does.

11.8 CONCLUSION The purpose of this study was to evaluate the impact of ICT practices on business performance in the Greek entrepreneurship accordingly to the government programme ‘Go-Online’. Related to the aim of this study, we made three hypotheses: (1) ICT compatibility with HR, (2) the impact of ICT on SME performance, and (3) perceived safety, trust and online transactions. As expected, the results indicated that ICT compatibility with HR and ICT impacts on firm performance are significant predictors for all the performance variables. However, all the ICT practices showed significant correlation with overall business performance. Additionally, we measured business performance with four variables: competitiveness, increased sales, profitability and sustainability. In particular, the results indicated that ICT compatibility with HR and ICT impacts on firm performance significantly improved perceived competitiveness, perceived increased sales, perceived profitability and perceived sustainability, while perceived safety, trust and

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online transactions have low correlation with perceived increased sales and profitability. Results strongly suggest that ICT adoption can be a success only when SMEs train their personnel appropriately. The combination of ICT and skill personnel has a direct effect on the scope and performance of SMEs.

ACKNOWLEDGEMENTS This research was conducted in collaboration with the Greek online project in the Peloponnese region, a part of the European GoDigital initiative (http://www.goonline.gr).

REFERENCES Arbore, A. and Ordarini, A. (2006) Broadband divide among SMEs. International Small Business Journal, 24(1), 83–99. Auramo, J., Kauremaa, J. and Tanskanen, K. (2005) Benefits of IT in supply chain management: an explorative study of progressive companies. International Journal of Physical Distribution & Logistics Management, 35(2), 82–100. Ballantine, P. (2005) Effects of interactivity and product information on consumer satisfaction in an online retail setting. International Journal of Retail & Distribution Management, 33(6), 461–471. Bengtsson, M., Boter, H. and Vanyushyn, V. (2007) Integrating the internet and marketing operations. International Small Business Journal, 25(1), 27–48. Boonstra, A. and De Vries, J. (2005) Analyzing inter-organizational systems from a power and interest perspective. International Journal of Information Management, 25, 485–501. Cho, S.E. and Park, K. (2003) Characteristics of product/service process and customer needs of geographical accessibility in electronic commerce. Industrial Management & Data Systems, 14(5), 520–538. Dietz, G., Wiele, T., Iwaarden, J. and Brosseau, J. (2006) HRM inside UK e-commerce firms. International Small Business Journal, 24(5), 443–470. EOMMEX (2007) EOMMEX – National Statistic Organization for SMEs in Greece. Report on usage of ICTs in Greece. Available at: http://observatory.eommex.gr/eommex/ (accessed 19 October 2010). Galloway, L. and Mochrie, R. (2005) The use of ICT in rural firms: a policy-oriented literature review. Info, 7(3), 33–46. Houghton, K. and Winklhofer, H. (2004) The effect of website and e-commerce adoption on the relationship between SMEs and their export intermediaries. International Small Business Journal, 22(4), 369–488. Iansiti, M. and Levien, R. (2004) The Keystone Advantage: What the New Dynamics of Business Ecosystems Mean for Strategy, Innovation, and Sustainability. Boston: Harvard Business School Press. Jutla, D., Bodorik, P. and Dhaliwal, J. (2002) Supporting the e-business readiness of small and mediumsized enterprises: approaches and metrics. Internet Research, 12(2), 139–164. Kohn, S. and Husig, S. (2006) Potential benefits, current supply, utilization and barriers to adoption: an exploratory study on German SMEs and innovation software. Technovation, 26, 988–998. Lasch, F., Le Roy, F. and Yami, S. (2007) Critical growth factors of ICT start-ups. Management Decision, 45(1), 62–75. Lawless, N., Allan, J. and O’Dwyer, M. (2000) Face-to-face or distance training: two different approaches to motivate SMEs to learn. Education & Training, 42(4/5), 308–316. Lee, G.C. and Bai, R.J. (2003) Organizational factors influencing the quality of the IS/IT strategic planning in digital era. Management Decision, 41(1), 32–44. Lloyd-Reason, L., Muller, K. and Wall, S. (2002) Innovation and education policy in SMEs. Education & Training, 44(8/9), 378–387. Lohrke, F., Franklin, G. and Frownfelter-Lohrke, C. (2006) The internet as an information conduit. International Small Business Journal, 24(2), 159–178. Macdonald, S., Assimakopoulos, D. and Anderson, P. (2007) Education and training for innovation in SMEs. International Small Business Journal, 25(1), 77–95.

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Madu, C.N. and Madu, A.A. (2003) E-quality is an integrated enterprise. International Journal of Quality & Reliability Management, 15(3), 127–136. Markides, C. and Anderson, J. (2006) Creativity is not enough: ICT-enabled strategic innovation. European Journal of Innovation Management, 9(2), 129–148. Martin, L. and Matley, H. (2001) “Blankets” approaches to promoting ICT in small firms: some lessons from DTI ladder adoption model in the UK. Internet Research: Electronic Networking Applications and Policy, 11(5), 399–410. Matlay, H. and Addis, M. (2003) Adoption of ICT and e-commerce in small businesses: an HEI-based consultancy perspective. Journal of Small Business and Enterprise Development, 10(3), 321–335. McIvor, R. and Humphreys, P. (2004) The implications of electronic B2B intermediaries for the buyer– supplier interface. International Journal of Operations & Production Management, 24(3), 241–269. Morgan, A., Colebourne, D. and Thomas, B. (2006) The development of ICT advisors for SME businesses: an innovative approach. Technovation, 26, 980–987. Motwani, J., Motwani, N., Schwarz, T. and Blankson, C. (2006) Succession planning in SMEs. International Small Business Journal, 24(5), 471–495. Mullane, J.V., Peters, M.H. and Bullington, K.E. (2001) Entrepreneurial firms as suppliers in business-tobusiness e-commerce. Management Decision, 39(5), 388–393. Oliver, J. and Porta, J. (2006) How to measure IC in clusters: empirical research. Journal of Intellectual Capital, 7(3), 354–380. Ratnasigham, P. (1998) Trust in web-based electronic commerce security. Information Management & Computer Security, 6(4), 162–166. Ribbink, D., Van Riel, A., Liljander, V. and Streukens, S. (2004) Comfort your online customer: quality, trust and loyalty on the internet. Managing Service Quality, 14(6), 446–456. Saarenketo, S., Puumalainen, K., Kuivalainen, O. and Kylaheiko, K. (2004) On dynamic knowledge-related learning processes in internationalizing high-tech SMEs. International Journal of Production Economics, 89, 363–378. Sambrook, S. (2003) E-learning in small organisations. Education & Training, 45(8/9), 506–516. Spanos, Y., Prastacos, G. and Poulymenakou, A. (2002) The relation between information and communication technologies adoption and management. Information & Management, 39, 659–675. Tamini, N., Rajan, M. and Sebastianelli, R. (2000) Benchmarking the homepages of Fortune 500 companies. Quality Progress, 33(7), 47–51. Tanova, C. (2003) Firm size and recruitment: staffing practices in small and large organizations in North Cyprus. Career Development, 8(2), 107–114. Wilson, S. (1997) Certificates and trust in electronic commerce. Information Management, 5(5), 175–181.

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12

Warehouse Technologies in Retail Operations: the Case of Voice Picking

Aristides Matopoulos

12.1

INTRODUCTION

The retailing sector has a long record in the adoption and implementation of both technologybased applications and innovative managerial practices. Starting with barcode technology in the early 1980s, moving next to cross-docking and vendor-managed inventory practices in the 1990s and radio frequency identification (RFID) applications in the 2000s, the retailing sector has demonstrated its capacity for continuous performance and efficiency improvements in response to increased competition, increased transportation costs and therefore threatened net profit margins. There is no doubt that the retail industry relies heavily on technology, having being transformed into an extremely information-intensive sector, with hundreds of thousands of orders, deliveries, shipping notices or receipt documentations exchanged on an annual basis. Within this context, it is no surprise that, alongside the transport sector, retail is a leader in Europe in the use of technology-based applications (IDC, 2008). Furthermore, according to same report, the highest percentage of pilot projects and ongoing implementations is currently reported in the manufacturing sector because of increased pressure from retail customers and with the objective of improving production efficiency while safeguarding product safety and authenticity. The objective of this chapter is to present the importance of information and communication technologies (ICT) in retail warehouse operations. The chapter has the following structure: first, an overview of the characteristics of warehousing operations is presented. Then, the order-picking process is analysed, along with the most important methods currently employed, putting emphasis on voice picking. Then a case study of a Greek retailer is provided. The case study emphasises the way a warehouse for fruit and vegetables operates, drawing from a real project, and presenting insights from the implementation of radio frequency (RF) picking and voice-picking technology.

12.2 12.2.1

RETAIL WAREHOUSE OPERATIONS An overview of warehouse operations

Warehouses lie, by definition, in the centre of retail operations, playing a vital role in their daily life and contributing significantly to their final success. Despite their undisputed importance, operating a warehouse often turns into a nightmare for many companies Intelligent Agrifood Chains and Networks, First Edition. Edited by Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis. © 2011 by Blackwell Publishing Ltd. Published 2011 by Blackwell Publishing Ltd.

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since, in addition to their traditional inventory holding roles, warehouses nowadays have been transformed into distribution centres where adding value activities (e.g. assembly, packaging, quality control) are also performed (Maltz and De Horatius, 2004; Baker and Canessa, 2009). According to Gu et al. (2007), the basic requirements in warehouse operations are: ● ● ● ● ● ●

to receive stock keeping units (SKUs) from suppliers; to store SKUs; to receive orders from customers; to pick orders (retrieve SKUs and prepare the order); to assemble orders for shipment; to ship the completed orders to customers.

In this chapter, emphasis is given to order picking, which has been recognised in the literature as one of the most crucial operations in the warehouse. This is due to the fact that it tends to be either very labour intensive or very capital intensive (de Koster et al., 2007; Baker and Canessa, 2009). Indeed, according to some researchers order picking is the single most expensive element of warehousing, accounting for about 50% of all warehousing expenditure (Caputo and Pelagagge, 2006; de Koster et al., 2007). In addition to cost-related issues, problematic order picking can lead to unsatisfactory service and could cause serious delays to the entire supply chain. In retailing, order picking was traditionally a difficult task as in comparison to other sectors, it presents the following characteristics: ●

● ●

Retailers have an extended network of stores that need to be served (which is also geographically dispersed). A large number of SKUs are stored in the warehouse. Orders from retail stores are very complex in terms of product quantity and variation.

Recent trends in retailing have further increased the complexity of the order-picking process as well as its importance. Centralisation of logistics operations, for example, has dramatically increased the number of SKUs stored in a warehouse or distribution centre to tens of thousands. Similarly, competition has forced retailers to further increase the number of SKUs they hold in an effort to increase variety and service for consumers. Particularly in the case of fresh produce, retailers have had to further increase the frequency of deliveries to stores, often in smaller lot sizes, so as to meet ‘freshness’ criteria and to satisfy consumers’ demand. Within this context, the need for accuracy, multi- or single-piece picking capability, sorting ability and response time, in a cost-efficient and productive way, is brought to the top of the agenda of retail logistics managers.

12.2.2

Warehouse order picking and the emergence of voice picking

As Gu et al. (2007) argue, the increased availability of new ICT, such as barcoding, RF communications and warehouse management systems (WMS), provides new opportunities to improve warehouse operations, and not only in terms of the financial benefits. In the following paragraphs, a brief analysis of the available picking methods is provided, with the emphasis being placed on voice picking.

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Four major types of order picking can be distinguished: (i) (ii) (iii) (iv)

paper-based picking; RF picking; picking-to-light; voice picking.

In paper-based picking, companies use a printed list to prepare their orders for shipping. The order-picking instructions are sent to the warehouse on paper. Paper-based picking, with low capital invested, is inefficient in several ways. When a picker uses a paper-based system he has to take in the orders, print them, prioritise operations, read them line by line, locate each order in the warehouse – with much time spent searching and walking around – and then pick the correct amounts. Next, on order completion the worker has to note down deviations in stock, subtract the units picked from each location and then enter all this new information into the computer. Not surprisingly, it is very easy for errors to occur during this process, which often results in client complaints, causing a negative impact on the quality of the service. Moreover, detecting picking errors before the order is sent to the client is a costly process. Radio frequency picking, in contrast, is a paperless way to execute order picking. It is based on RF technology, which allows mobile devices, as well as computers and printers, to communicate with each other wirelessly within a local area network. The RF picking system allows stock retrieval and replenishment to be combined, and reduces the number of movements involved in the internal transport of material and also the number of empty runs. RF picking supports order-picking principles, such as individual selection, batch selection or splits between items and packaging. Picking information is received by the terminal, and inquiries or transaction/activity data are sent from the RF terminal to the host in real time. Once the order is picked, a forklift truck operator is given delivery instructions from the WMS through an RF terminal. The RF picking system provides real-time updates of picking activity and order status. It also enables the WMS to continually recalculate the most efficient pick/putaway routes and order assignments. Picking-to-light is a system that provides an effective way to collect parts, components and other material with the minimum number of operator errors. It comprises two parts: the picking control software, which knows which components must be collected, and the picking panels, which guide the picker to collect the right amount of each necessary component. The system uses light displays to direct operators to specific stock locations. Each product location can have an individual numeric or alphanumeric display, with a light, an acknowledgement button and a digital readout for indicating quantity. Other configurations allow for fewer or more simple displays to reduce the total cost. Voice picking is a human-based method of performing order selection in a warehouse or distribution centre using verbal commands, which are given to and received from the picker. The method works in a similar fashion to RF devices, but instead of picking tasks being displayed on an RF screen, warehouse operators listen to task information on their headsets through a voice system. The picker normally wears a headset/microphone combination, which is attached to a small control unit worn around the waist, and moves through the warehouse to locations as directed by the headset. The control unit is responsible for communicating voice commands to the picker and then receiving spoken responses from the picker. Communication is transmitted to and from a server or host computer via radio waves or RF signals. Two types of voice units exist: speaker-independent units, which can be used by any operator, and speaker-dependent units, which retain large vocabularies, can be

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language specific and can create unique speech profiles or templates for each operator. In practice, voice picking is not a ‘one-size-fits-all’ application. The use of voice technology, for example in the warehouse, is starting to take off, particularly for order picking, and particularly in the foodservice industry and among grocery retailers, who are leading the way in adopting the technology (Kator, 2008). A 2009 benchmarking survey, conducted by the Supply Chain Consortium and based on returns from 270 participating retail, manufacturing and wholesale/distribution companies, revealed the prevalence of ‘traditional’ picking. It seems that paper-based, label-directed and handheld (RF gun) picking technologies are still more commonly used than voice picking. Picking-to-light is mostly used for full pallets or full cases, although full case, pick-to-pallet operation is actually a very good fit for voice picking (Napolitano, 2009). Several benefits of voice picking have been suggested (Warehouse Management Consultants, 2002; Kevan, 2004; Napolitano, 2007; Connolly, 2008). The most important categories of benefits are presented and briefly analysed below: (i) Increased accuracy: The reduction in picking errors is one of the most important benefits of voice picking. Despite the fact that errors in picking in conventional systems amount to only 0.5% of orders, nonetheless they lead to significant costs for a business. This is because of the complexity of correcting them. In addition, out-of-stock situations and undelivered products negatively impact on customer service. (ii) Increased productivity: Picking is made easier and more productive, since the picker can focus his eyes on his movement around the warehouse, on stock locations and on product movement tasks, rather than on a display or keyboard. Because the picker does not have to constantly shift focus from a display to a product and back, there is less visual fatigue. In addition, order pickers in foodservice or grocery retail warehouses often work in chillers and freezers, where protective gloves make handling RF devices or paper lists difficult and time-consuming. (iii) Cost reduction (e.g. cost of printing and distributing picking documents): In voice picking the need for printing and distributing pick lists is eliminated. The cost of the paper and printer supplies, as well as the labour needed to distribute the paper each day, is eliminated. In addition, exceptions are communicated using voice at the time of the pick, eliminating clerical data entry. (iv) Reduced training: In voice picking, training needs can be reduced since verbal prompts are easier to understand. This is of particular importance for an environment in which foreign workers are employed.

12.3 12.3.1

THE AB VASSILOPOULOS CASE STUDY Grocery retailing in Greece

Grocery retailing in Greece is a large and dynamic sector and sales increased by 10% in 2007 to a level that is above the European sector average (EXPRESS, 2008a). Traditional food convenience stores contribute only 8% of sales, while multiple retailers hold 16% of stores but enjoy 92% of sales (IRI, 2006). A number of mergers, acquisitions and new entrants to the market have been seen in the last few years. The entrance of multinational players has increased the level of competition, causing domestic retailers to accelerate their growth through acquisition of smaller players and entering new markets (Doukidis,

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Warehouse Technologies in Retail Operations Table 12.1

199

The top 10 food retailers in Greece.

Rank

Company

1 2 3 4 5 6 7 8 9 10

Carrefour-Marinopoulos SA Alfa Beta Vassilopoulos SA Sklavenitis, I. and S., SA Veropoulos Bros SA Metro SA Atlantic SA Masoutis, D., Supermarket SA Makro (Greek branch of the German metro)* Pente SA Dia Hellas SA Top 10 (total turnover and market share between these multiples)

Turnover 2007 €m 1899 1175 961 848 601 596 544 457 413 381 7875

Market share 2007 % 24.11 14.92 12.20 10.77 7.63 7.57 6.91 5.80 5.24 4.84 100%

Source: Express, 2007a. *Involved both in wholesaling and retailing.

2004). Despite this trend, the Greek food retailing sector is less concentrated than other European countries. It is estimated that the top three grocery retailers in Greece account for approximately 40% of the market, while the European average is nearly 50%. Total turnover of the sector is calculated at €8.5 billion, 81% of which is achieved by the top 10 retailers (EXPRESS, 2008b). Domestic and multinational retailers have nowadays become the most powerful players in the food sector. The entrance of multinational retailers into the market initiated changes and improvements in the structure of the logistics systems of companies. Prior to the entrance of the multinational companies, the development of warehousing and the use of third-party companies was limited. The implementation of efficient and effective logistics practices by domestic retailers was also very weak (Bourlakis and Bourlakis, 2001). However, the establishment of a vast network of stores across the country encouraged domestic retailers to re-evaluate their logistics strategies. Many retailers moved towards centralisation of their logistics processes, with the establishment of new distribution centres or investments in ICT in an effort to increase efficiency and coordination, and in order to compete and catch up with multinational players (Bourlakis and Bourlakis, 2006). In many cases domestic retailers developed new strategic partnerships or outsourced logistics activities to third parties. Table 12.1 lists the top 10 grocery retailers in Greece.

12.3.2

Company background

In the competitive business environment of the Greek grocery retail market, where two overseas (AB Vassilopoulos and Carrefour International) and two national (Skalvenitis and Veropoulos) retail chains account for more than 60% of the total organised retail market of €12.9bn, Alfa-Beta Vassilopoulos S.A (ΑΒ) is ranked in second place, with about 10.4% market share. Recently the company acquired the discount retail chain Plus Hellas, enlarging its network by 29 stores after the closure of several of those it had acquired. Its presence in northern Greece was strengthened by the addition of seven new prefectures into AB’s geographical network through the acquisition of Plus Hellas. With its current operation of

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Table 12.2

AB in numbers.

(Consolidated)

2008

Financial results Amounts in thousand EUR Turnover (Sales) 1.337.074 Net profit margin 2.4% Outlets Number of stores Sales area (in sq.m.) Franchising network stores Personnel (31.12) Total of employees Full-time/Part-time Male/Female

2007

2006

2005

2004

1.174.883 3.1%

1.030.249 1.9%

908.001 1.4%

873.114 2.0%

160 186,971 41

123 156,320 36

118 150,675 30

111 142,090 24

110 145,745 19

8,821 4,027/4,794 2,934/5,887

7,545 3,596/3,949 2,521/5,024

7,209 3,521/3,688 2,455/4,754

6,744 3,419/3,325 2,364/4,380

6,517 3,419/3,098 2,322/4,195

Source: AB’s 2009 financial report.

201 stores around Greece, ΑΒ is close to becoming a national player, with full geographical coverage and group consolidated sales for 2008 of €1.34bn. AB was established in December 1969 by the brothers Gerasimos and Charalambos Vassilopoulos. In November 1990 it was listed on the main market of the Athens Stock Exchange. In July 1992 it became a member of the Delhaize Group, which owns 65.27% of AB. The acquisition of Trofo in 2000 played a very important role in the rapid expansion of AB. With a workforce of approximately 9000 people (both full-time and part-time employees), AB ranks among the most important employers in Greece. In Table 12.2, a brief presentation of the most important financial characteristics of AB is provided. The company has an organisational structure with eight main divisions: (i) Store Operations, which organises, staffs and supervises all the supermarket stores of the group, including the supervision of franchise stores. (ii) Purchasing, with responsibilities that include the choice of suppliers and products, setting product ranges, the development of AB-label products, setting pricing policy, purchases of non-tradable goods and responsibility for quality assurance. (iii) Supply Chain, with duties that include the overall supervision of logistics, the operation of the Informatics Department, which plans, develops and operates the most modern systems and information networks, and the development of new company warehouses. (iv) Finance, which is responsible for general and shop accounting, acquisition and management of funds, compiling, monitoring and implementing the budget and cashflow programme, and monitoring shareholder relations. (v) Human Resources, which is responsible for organisational procedures, new hires, training and development of staff, salaries and security for protection against losses. (vi) Business Development, Strategy and Marketing, which is chiefly responsible for real-estate selection, design, construction and maintenance and management of the real estate portfolio. (vii) Strategic Marketing, which is chiefly responsible for collecting and processing data through research, the customer relationship management, management of AB Visa and merchandising and company communications, both internal and external. (viii) Internal Auditing and the Legal Service, which support the management of the company.

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Table 12.3 General information on the AB fruit and vegetable warehouse (based on interviews with AB’s Managers). AB Fruits & Vegetable Warehouse Product category

Temperature (°C) Area (sq. m) Rack type Warehouse vehicle equipment

Reception workstations Shipment ramps Picking method Stores SKUs Daily average number of cases (output) Picking shifts Reception shift Loading shift Headcount

Fresh fruits (4 categories) Vegetables (13 categories) Bio f&v (1 category) 12 4 4500 No racks 25 order picker (1 pallet) 2 stacker 5 hand pallet trucks 7 19 By Line (or Item) (FIFO) 152 (110 AB stores, 10 ENA C&C stores, 32 affiliated stores) 500 (daily), 1000 (yearly) 25000 I (10:00–18:00) II (18:00–02:00) 07:00–20:00 15:00–06:00 60

12.3.3 A view of the company’s warehousing and distribution operations In terms of distribution and warehouse operations, the company currently has divided its distribution into two major geographical areas: south-central Greece and northern Greece. South-central Greece stores, 163 in number, are supplied with dry grocery and fruit and vegetables through the central warehouse located in Mandra Attika. A private fleet of 59 trucks is used to deliver to the 104 Attika stores, while a third-party (3PL) fleet serves the remaining 29 provincial stores. Additionally, two 3PL warehouses supply the same stores with cold, chilled and frozen SKUs, with a 3PL fleet serving the Attika stores and crossdocking at the central warehouse to another 3PL fleet serving provincial stores. Stores in northern Greece, 40 in number, are supplied with 80% of their total volume of dry groceries, 100% of fruit and vegetables and cold, chilled and frozen SKUs through a distribution centre (DC) located in Sindos. The remaining 20% of dry groceries come through the central warehouse in Mandra via a 3PL fleet. Another 5% of the total volume is supplied to northern Greece stores through the Sindos DC, which is replenished through the central warehouse in Mandra Attika. It is estimated that total centralisation reaches 83% for dry groceries, 97% for fruit and vegetables, and 46% for cold, chilled and frozen foods. Currently, a new warehouse is being constructed in Inofyta Viotia, which will hold fruit and vegetables and cold, chilled and frozen foods. The goal is to further increase centralisation levels. This case study examines warehousing operations for fruit and vegetables (FV). The categories of products handled are FV, which is 100% centralised and some specific items, handled through cross-docking, such as fresh milk, sandwiches and packed cheese. In Table 12.3 the basic characteristics of the warehouse in terms of its design, equipment and operations are presented.

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12.3.4

Analysis of AB’s warehouse operations

Three of the most important processes in the FV warehouse from an operational perspective are: (i) goods receiving; (ii) order preparation; (iii) pallet preparation (per store). 12.3.4.1

Goods receipt

Goods receipt is a critical task for ensuring the smooth operation of every warehouse because goods receiving are the first people to confirm that all parameters – both legal and operational – are met, before accepting the pallets of incoming goods. The effectiveness of the task will ensure the proper performance of the warehouse in terms of picking, shipping to stores and inventory shrinkage. The planning of goods receiving is very difficult to achieve, since the market for FV is variable on a daily basis and the stock level of the warehouse is close to zero. The reception process involves three phases: (i) document control; (ii) physical product reception; (iii) administrative reception. Document control must be performed with caution since it is AB’s formal acceptance of the purchase of the items and quantities delivered by the supplier. In all cases the details of the receiver (AB) must be checked as correct (name of company, address of company, address of delivery and taxation number). The receipt is then executed according to the data printed on the delivery note. The reception starts with the arrival of the supplier’s truck at the warehouse doors. Before unloading the truck and after the receipt of the shipping documents, the receiver must retrieve from AB’s WMS the order created by the Commercial Department regarding the specific supplier. The receptionist must now compare the items and quantities ordered with those listed in the order. If the receptionist spots differences they must inform the shift supervisor or/and the buyer and proceed accordingly. The next phase is physical product receipt, where items are received in pieces or in kilos or pallets, depending on the product. Lastly, administrative receipt takes place. Here, the receptionist fills in a blank receipt form indicating the reusable means of product transportation received by the supplier. 12.3.4.2

Order preparation and picking

Order preparation and picking start after a last selection conducted by the Commercial Department, which filters the items and quantities of the orders to best match them with what is available in the warehouse. The FV warehouse uses picking by line to prepare orders. As soon as an item is received, fully or partially, the shift supervisor selects items to pick manually, using criteria such as productivity, sensitivity, total reception quantity vs. order quantity etc.). A paper-picking list is then printed, describing a full or partial fulfillment of a store’s orders. The shift supervisor then performs the allocation of the tasks to the pickers manually. The principal goal is to achieve optimised use of space and labour and meet certain strict time limits.

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After the above parameters are set, the list of the items to be picked is displayed and the items to be distributed are chosen. The paper-picking list provides the picker with all the necessary details for the physical distribution of the selected item, which has already been distributed by the system, considering the available quantity and its allocation to pallets and cases, the quantity requested by the orders and the parameters set during the task creation. The picker who has received a picking task has to login to the system through a terminal, and inform the system who has started working on the task and when by scanning a personal login number and the task number. Following the instructions on the picking list, the picker realises the distribution of quantities by item and by store, at the end of each line counting the remaining cases on each pallet used. The sequence of events involves the retrieval of each pallet indicated on the picking list with the specific number of cases and quantity per pallet. Then, the picker goes to each store lane in the list and puts the listed number of cases on the pallets for the store, in a way that reinsures the integrity of the quality of the product and the optimisation of the exporting volume. When leaving the store lane, the picker indicates on the picking list the number of the lane (i.e. a check digit), which is used for verification of the allocation of the cases for a specific store. When the picker concludes the assigned tasks, he has to inform the system by inputting per task the remaining cases per pallet he has counted at the end of each individual task. The picker is responsible for informing the shift supervisor of any deviation he notices between the picking list and the physical picking, so that mistakes can be traced and correction be performed so that transactions are performed correctly.

12.3.4.3 Preparation of pallets The preparation of pallets, per store, ensures the safe distribution of products and also the optimisation of the truck volume. The parameters estimated for good performance in this task are the weight and material of each case and its compatibility for stacking with other cases so that the quality of products is not reduced during transportation. The pallets or roll cages built must be aligned with the geometry of the trucks and the distribution of weight must be such as to create a stable unit for transportation, to and from the trucks and in the stores, etc. Consequently, it is obvious that the quality and the total time used for preparing pallets is influenced by the sequence of the item picking in the store lanes, the placement of the cases on the pallets/roll cages by the pickers, the cases used by suppliers, etc. Figure 12.1 shows a general process flowchart for the AB FV warehouse.

12.3.5 Insights from the implementation of RF picking and voice picking At the end of the 1990s (1997–98) the AB IT and Logistics Department started working, through business analysis, towards the development of a fully in-house integrated WMS, aiming to upgrade operations by introducing new, value-added technologies, and giving the opportunity of reconfiguring a picking process that was low-tech and riddled with inefficiencies. The goal was to implement the new WMS in the group’s new dry-grocery distribution centre in Mandra, Attica, gradually substituting the off-line, manual procedures with RF technology.

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Stores

Customer orders

Order filtering

Commercial Dpt.

Procurement orders

Yes

Item reception

Continue reception?

No

Yes

Reception complete?

Item picking list

Distribution Centre

Manual task assignment to picker

Proportional picking

Item picking

Allocation of cases to lanes

Pallet retrieve

Formation of pallet / store

Yes

End of picking?

Remaining cases on last pallet

Stores / truck

Loading / truck

Exporting pallets/ store

Cross docking items

Document printing

Figure 12.1 General process flowchart of the AB fruit and vegetable warehouse.

The first implementation was concerned with the reception process and went live in 1999, followed by the introduction of forklift RF guidance. Full integration was completed with the replacement of the picking and loading processes in 2005 and the distribution centre reached 100% RF thereafter. With a significant percentage of volume picked every day, the company had for years also been picking multiple orders using paper pick lists and grocery shopping carts. Picking several orders at a time, each picker had to manually track which product went with which order. As if that was not enough, paper pick lists had the tendency to simply disappear and error rates were very high. In addition, on some occasions, because of quality issues (the picker spotted a quality issue or a damaged product) the quantities had

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to be excluded for picking. The picking list then had to be cancelled, new quantities had to be reserved, and consequently the picking list had to be reprinted taking into account the new total quantity available. In an effort to overcome all these inefficiencies, in the late 1990s the company decided to look at the different technologies available at that time, such as: picking-to-light, voice picking and RF picking. Picking-to-light was rejected from the beginning because the number of SKUs was very high. Voice picking was in its infancy at that time and not many installations were in place. Consequently, the company decided to install RF picking and this resulted in significant improvements. Mispicks, for example, reduced from 1% to 0.1%. However, in the following years the company sought to increase accuracy in reception, stocking and picking as well as productivity, compared to its traditional operations. A pilot demonstration involving a voice-enabled WMS convinced the team that all these inefficiencies could be removed by implementing a voice-picking solution, which would not only be the best fit but it would also be the most cost-efficient system. The interest turned to voice-enabled applications, and especially voice picking, around 2005, when the company was ready to convert from conventional paper operations for FV to RF. The project aim to increase accuracy by at least 50%, a 10–15% increase in overall productivity, minimisation of the training period for new employees, increased traceability as dictated by local law, and the availability of online, live, warehouse management information. Moreover, compared with RF guns, voice picking enables hands-free interaction with the computer system while work is performed by hand. The main difference between dry-grocery and FV operations is that for the latter picking is performed by line, since no full stock of all items is available when picking starts. This peculiarity led to extensive analysis in cooperation with the voice application provider since picking by line is unusual and, where it is used, it usually involves relatively small volumes. In the voice-directed picking system the picker is verbally directed to a location where they provide the pallet’s four-digit identification. They are then guided to the preparation areas, where picked items are matched with orders to be prepared. Each time, the picker indicates the two-digit check-number of each location he visited and verifies the quantity picked. At the end of each split pallet he counts, if any, the remaining quantity as a last quantity check. Meanwhile, as picking places receive cases from different picks the system calculates the volume on the pallet and, when the pallet is full, a task is created for replacing the pallet in the place with an empty one. The full pallets are stocked in the shipping lane for each order. Using new picking carts, pickers work on multiple orders at a time, placing products directly into the shipping carton.

12.4

CONCLUSIONS

In this chapter the use of a specific warehouse technology to support operational improvements was presented. The case study demonstrates on the one hand the complexity of warehouse operations, particularly the order-picking process, and on the other hand it shows how new technologies can offer companies new alternatives for achieving operational improvements. Despite the fact that the company already had in place an RF-based picking system, it decided to proceed with the voice-picking project to further improve the picking processes and the efficiency of the FV warehouse in general. After the rollout of the new system in 2009, AB Vassilopoulos has been using it continuously to support the picking process in the central warehouse for FV. The case study reveals that voice-picking applications are highly

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relevant for warehouse areas with high-volume or pallet picks and is most effective for repetitive tasks. Alternatively, RF picking can be equally effective. However, if the warehouse operators perform a large number of different transactions, voice picking may not be very effective. The decision to implement such a solution is not risk-free, given that the company still has to invest a considerable amount of money and to overcome technical as well as organisational challenges, such as the alignment of technology with the business processes and proper training of end-users. In any case, a careful cost-benefit analysis is needed to determine what areas of the warehouse can benefit from voice picking.

ACKNOWLEDGEMENTS The author would like to thank AB Vassilopoulos for their permission to use company data and information. In particular, the author would like to thank Mr Nikos Iossipou (Supply Chain Executive Director), Mr Spyros Kyrousis (Executive Logistics Director) and Mr Michalis Sotiriou (KAM Warehouse Manager), who generously assisted in providing the detailed information and data used to prepare this chapter.

REFERENCES Baker, P. and Canessa, M. (2009) Warehouse design: A structured approach, European Journal of Operational Research, 193, 425–436. Bourlakis, M.A. and Bourlakis, C.A. (2001) Deliberate and emergent logistics strategies in food retailing: a case study of the Greek multiple food retail sector. Supply Chain Management: An International Journal, 6, 189–200. Bourlakis, M.A. and Bourlakis, C.A. (2006) Integrating logistics and information technology strategies for sustainable competitive advantage. Journal of Enterprise Information Management, 19(4), 389–402. Caputo, A.C. and Pelagagge, P.M. (2006) Management criteria of automated order picking systems in highrotation high-volume distribution centers. Industrial Management & Data Systems, 106(9), 1359–1383. Connolly, C. (2008) Warehouse management technologies. Sensor Review, 28(2), 108–114. De Koster, R., Le-Duc, T. and Roodbergen K.J. (2007) Design and control of warehouse order picking: A literature review. European Journal of Operational Research, 182, 481–501. Doukidis, G. (2004) The contribution and competitiveness of food retailing, ELTRUN Working Paper Series, WP 2004–005, Athens University of Economics and Business (in Greek). EXPRESS (2008a) Retailer’s sales in 2007, 4th February 2008. Available at: http://news.pathfinder.gr/ finance/business/454915.html (accessed 20 January 2008). EXPRESS (2008b) Turbulence in the Greek retail sector, 1st January 2008. Available at: http://news.pathfinder.gr/finance/business/449306.html (accessed 20 January 2008). Gu, J., Goetschalckx, M. and McGinnis, L.F. (2007) Research on warehouse operation: A comprehensive review. European Journal of Operational Research, 177, 1–21. IDC (2008) Various Reports from Sector. IT Services, New York. IRI (2006) The food retailing in Greece, IRI Report, Athens. Kator, C. (2008) Foodservice distributors turn to voice-directed picking. Logistics Management, June, Framingham, USA. Kevan, T (2004) Improving warehouse picking operations: voice-recognition systems offer advantages that scanning technology can’t touch. Frontline Solutions, 5(1), 16–21. Maltz, A. and DeHoratius, N. (2004) Warehousing: The Evolution Continues. Warehousing Education and Research Council, Oak Brook.

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Napolitano, M. (2007) Voices in the warehouse: Should you listen? Logistics Management, January, Framingham, USA. Napolitano, M. (2009) Warehouse & DC: voice broadens its horizons. Logistics Management, January, Framingham, USA. Warehouse Management Consultants (2002) Voice directed picking: a technology that is ready for prime time! Document # WP-8378, February 26, 2002.

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13

Leveraging RFID-enabled Traceability for the Food Industry: a Case Study

Angeliki Karagiannaki and Katerina Pramatari

13.1 INTRODUCTION Public and industry concerns over food safety have grown considerably over the last decade. Food safety has traditionally been viewed as a ‘cost of business’ (Littlefield, 2006) and, as a result, perceived and positioned as the voluntary responsibility of companies. However, this perception is changing as stricter legislation and industry standards have come into force and require that companies not only adopt a strategy of minimal compliance, but also treat such a strategy as a catalyst for better business practices. Despite all the legal requirements and industry standards deployed to ensure optimum quality, serious outbreaks of food diseases (e.g. BSE or mad cow disease, dioxin contamination of animal feeds, listeria) have occurred where contaminated products had already reached consumers. To cope with such situations, the withdrawal/recall of inappropriate products from the market and the notification of the authorities have become top priorities for food companies. Furthermore, such food deficiencies have raised doubts in the consumer’s mind and created a lack of trust and confidence in products put on the market. Consumers are getting more and more worried about what they eat – whether the food comes from a sustainable source and is produced through eco-friendly methods, and whether production, transport and storage conditions can guarantee food safety. Betraying the consumers’ confidence may, in the long term and the worst case, damage a company and its brand image, and lead it to economic collapse (ECR Europe, 2004). Under the pressures of legal compliance, safety and quality assurance, risk prevention, efficient recalls/withdrawals and the consumer’s right to know, the introduction of a traceability system is not only high priority but, in some food chains, a mandatory initiative. Hence, deploying a traceability system can bring about significant improvements in three main areas (Golan et al., 2003): (i) capturing efficiency gains through improved supply-side management; (ii) achieving marketing/competitive advantage by differentiating foods with credence attributes; (iii) improving food safety and quality control by helping firms to identify and resolve food safety or quality problems.

Intelligent Agrifood Chains and Networks, First Edition. Edited by Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis. © 2011 by Blackwell Publishing Ltd. Published 2011 by Blackwell Publishing Ltd.

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Empowered by the possibility of automatically identifying unique product instances through new technologies such as radio frquency identification (RFID), a traceability system promises to meet the above requirements even more effectively. However, as with all novel technologies, it takes time to make things work. As a result, in view of the premature level of RFID implementation, it is imperative to understand the significance of justifying the investment in an RFID-enabled traceability system and its implications for organisational performance. This chapter describes work undertaken for a company that deals with frozen food regarding the requirements’ analysis, development and pilot implementation of a RFID-enabled traceability system. Based on the experience gained, several considerations are presented that could provide valuable feedback to other organisations interested in moving to a RFID-enabled traceability scheme. The chapter is organised as follows. Section 11.2 offers a justification for the relevance of the work regarding RFID technology in supply-chain management and traceability. Section 11.3 provides the context of the work. Section 11.4 gives the alternative RFID implementations that were proposed to the company. Section 11.5 describes the RFID scenario chosen for implementation. Section 11.6 presents the evaluation of the developed RFID-enabled traceability system that was conducted during the pilot implementation. Finally, section 11.7 provides a number of conclusions.

13.2 BACKGROUND 13.2.1 RFID in supply-chain management Radio frequency identification is a technology that uses radio waves to automatically identify objects. The identification is done by storing a serial number, and perhaps other information, on a microchip that is attached to an antenna. This bundle is called an RFID tag. The antenna enables the chip to transmit the identification information to a reader. The reader converts the radio waves reflected back from the RFID tag into digital information that can be passed on to an enterprise information system (Kelepouris et al., 2007). RFID has been extensively used for diverse applications ranging from access control systems to airport baggage handling, livestock management systems, automated toll collection systems, theftprevention systems, electronic payment systems and automated production systems (Agarwal, 2001; Smith and Konsynski, 2003; Kelly and Erickson, 2005; Hou and Huang, 2006). Nevertheless, what has made this technology extremely popular is the application of RFID for the identification of consumer products and supply-chain management. The advanced data capture capabilities of RFID technology coupled with unique product identification and real-time information coming from different data sources, such as environmental sensors, define a new and rich information environment that opens up new horizons for the efficient management of supply-chain processes and decision support. As such, RFID can potentially empower a broad spectrum of applications, ranging from upstream warehouse and distribution management down to retail-outlet operations, including shelf management, promotions management and innovative consumer services, as well as applications spanning the whole supply chain, such as product traceability (Pramatari et al. 2005). Despite the broad spectrum of applications, RFID implementations currently take place internally within a company, mainly with the primary objective of automating warehouse management processes or store operations. As an outlook to the future, a recent industry report (GCI, 2005) identified certain application areas (specifically store operations,

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distribution operations, direct store delivery, promotion/event execution, total inventory management and shrink management) as the major opportunities for the deployment of RFID technology in the short and mid-term. These application areas have been selected based on their performance versus the ratio of expected benefits over associated costs, including process transformation difficulties. The same report identifies further opportunities in several ‘track and trace’ activities (such as anti-counterfeiting, product diversion, recalls/reverse logistics, fresh/code-dated product management, cold-chain monitoring and legal compliance), although it is noted that ‘more work is required to understand its potential applications and benefits in these areas’ (GCI, 2005). Leading companies in the global market have already made moves towards the application of RFID technology for monitoring product flow in their supply chains. Wal-Mart, the biggest retail chain in the USA, has mandated its biggest 100 suppliers to apply RFID tags to each pallet arriving in its central warehouse in Texas by January 2006. The US Department of Defense has already issued a mandate requesting its suppliers to apply RFID tags to all parts delivered to the US Army by January 2007 (Shutzberg, 2004). Metro, a big retail chain in Europe, has implemented a store (called ‘the future store’) that operates using RFID tags applied to each product. Metro has optimised many internal processes of the store using RFID technology and provides its customers with innovative services such as semiautomatic checkout and smart trollies, which carry a TFT display and provide the customer with information about the products on the shelves and the trolley. Furthermore, the future store gives Metro the opportunity to assess the benefits of RFID in a real case, measuring the impact of RFID deployment on stock reduction, increased availability and other issues of supply-chain management (Hamner, 2005). RFID technology has already been adopted by some suppliers at a product level. Gillette is the most striking example, having already applied RFID tags in some razor products.

13.2.2 Traceability A generic definition for traceability is given by ISO (1995): traceability is the ability to trace the history, application or location of an entity, by means of recorded identifications. The EU Commission (EU, 2002) narrows down the definition for the food industry, defining traceability as the ability to trace and follow a food, feed, food-producing animal or substance intended to be, or expected to be, incorporated into a food or feed, through all stages of production, processing and distribution. Van Dorp (2002) provides an extended list of definitions on traceability, pointing out that the differences between them derive from the different types of activities that are included and the organisational context in which they are performed. Deploying a traceability system can bring about significant improvements in three main dimensions proposed by Golan et al. (2003): traceability for improving supply-side management, traceability for achieving marketing/competitive advantage, traceability for food safety and quality control. Each of these dimensions is addressed, in turn, in the following sections. 13.2.2.1 Traceability for improving supply-side management This dimension involves the following benefits: ● ● ●

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supply-chain operations efficiency; improved trading partners; operational advantage within the company.

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Supply-chain operations efficiency This dimension tries to capture the value of a traceability system in terms of supply-chain efficiency, cost reductions throughout the supply chain and reduced cycle time. The ability to reduce costs relating to the physical processing (i.e. movement, storage and control of products) and the information processing (i.e. information exchange) across the supply chain often creates a financial advantage for firms. The greater the decrease in costs, the greater the value of coordination along the supply chain, the synergies and the operational as well as financial benefits. At the same time, the larger the market and the value of the food product, the larger also the benefits of traceability for supply-side management. Improved trading partner relationships This dimension tries to capture the value of a traceability system in terms of supply-chain integration and synchronisation, improved trading partner relationships and interorganisational coordination and synergies. The ability to integrate and synchronise with the supply chain has long been a basis for both behavioral and economic success. Moreover, the ability to work through improved systems and through an effective and efficient exchange will result in behavioural satisfaction between the trading partners and an increased quality of relationship. Satisfaction is expressed through lack of disagreements or conflicts. Signs of a quality relationship include flexibility, solidarity, continuity expectations, goal compatibility and increased commitment of resources to the supply chain members. Operational advantage within the company This dimension tries to capture the value of a traceability system in terms of increased productivity, economies of scale, organisational efficiency and operational excellence. A detailed traceability system can give very precise data about the production process and can therefore provide the basis for process improvement (both planning and control). Another aspect of productivity is the access to information within the company, especially between production and the general office. 13.2.2.2

Traceability for achieving marketing and competitive advantage

This dimension involves the following benefits: ● ●

building consumer trust; increased product differentiation and information provision.

Building consumer trust This dimension tries to capture the value of a traceability system in terms of increased trust in the company’s ability to provide safe products and products that are quickly identifiable in case of problems. A company that provides effective and efficient traceability embodies increased value in its products due to incorporation of increased safety precautions in its operations and business. It thus gives a minimised risk to any buyers who purchase its products. There is therefore a marketing and competitive advantage for the firm that possesses better and increased traceability. Increased product differentiation and information provision This dimension tries to capture the value of a traceability system in terms of ability to supply products to the final user/consumer that possess increased information about the production process and the origin of both the product itself and the ingredients used during its production.

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Food producers differentiate products using a wide variety of attributes. Content attributes affect the physical properties of a product, although they can be difficult for consumers to perceive. The existence of a traceability system allows the provision of products with quality information on their production process (e.g. in the case of chicken, its rearing conditions, the use of antibiotics, the feed used) and the origin (e.g. the country of origin or exact location of the farms). The higher the expected premiums, the larger the benefits of traceability for credence attribute marketing. Moreover, giving information about the content attributes provides brand protection, meaning that the company misleads nobody as everything comes from where it says it comes. 13.2.2.3 Traceability for food safety and quality control This dimension involves the following benefits: ● ●

compliance with regulations; risk management.

Compliance with regulations This dimension tries to capture the value of a traceability system in terms of meeting legislation and easier compliance with regulations. Compliance in itself is a value, inasmuch it saves trouble (e.g. with the public authority), time (e.g. when being inspected) and effort (e.g. in hiding non-compliance). It also has positive effects on the consciences of companies and individuals alike and will have an influence on both the work climate as well as personnel. Risk management This dimension tries to capture the value of a traceability system in terms of effective and efficient risk management. When dealing with food there are a lot of risks to take into account. A conscious management of these risks can make a very big difference, both in the avoidance of error and in swiftly dealing with situations when they happen. Food-safetyrelated risks are probably the most obvious. This includes both recall effectiveness and recall efficiency. The better and more precise the traceability system, the faster a producer can identify and resolve food safety or quality problems. Moreover, the higher the value of the food product, the larger the benefits of traceability for safety and quality control.

13.2.3 RFID-enabled traceability RFID can potentially make a significant contribution to traceability. According to Kelepouris et al. (2007), RFID’s contribution to traceability can be summarised in the following dimensions: ●

●

●

●

●

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Item identification: RFID can provide effective, unique identification of traceable units and potentially provision of extra information about the product. Bill of lots recording: RFID can provide automatic detection and identification of lots that are used in a specific batch production, using wireless identification. Operations recording: RFID can provide automatic detection and identification of batches that are subject to specific operations and hosted in specific capacity units. Item observation/data capture: RFID can provide effective and efficient item observation across the chain, with reduced labour costs. Links management and data retrieval: no data synchronisation is required for supply chain partners.

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13.3 THE CONTEXT 13.3.1 The case study: a frozen food company Vivartia is the leading food company in Greece, with more than 30% market share. It is one of the largest in Europe. Its brands are recognised by millions, reaching consumers in 30 countries whilst expanding across the world. Its success is based first and foremost on its respect for the consumer, and its tireless daily efforts to supply the best possible value in the form of healthy, quality products. The company now comprises four divisions: Dairy and Drinks, Bakery and Confectionery, Foodservices and Entertainment, and Frozen Foods. The Frozen Foods Division – Barba Stathis SA – is involved in the production and processing of frozen vegetables and foods in Greece and abroad. The range of the division’s products is constantly developing. It is active in the production of frozen vegetables, precooked meals, mixtures of frozen vegetables and, more recently, fresh salads. Over its 35 years on the market, it has always been innovative and generated new products. Realising RFID’s potential for improvements in different aspects of a warehouse, the company decided to participate in a project partly funded by the General Secretariat for Research and Technology, Ministry of Development of the Hellenic Republic regarding the requirements’ analysis, development and pilot implementation of a RFID-enabled traceability system within the central warehouse.

13.3.2 The warehouse and its operations The company has a central warehouse that stocks frozen vegetables and comprises a production unit where vegetables are packaged in bags. This section includes the description of the as-is operations within the central warehouse and aims to provide an understanding of the relationships between various activities, identifying those operations that were troublesome and could be improved by the deployment of RFID. This was accomplished by interviewing and visually examining the operations, including analysis of queues, bottlenecks, and human errors, and as a result, gaining insight into the problems that were expected to be improved by the RFID deployment. The raw materials comprise domestic fresh vegetables (e.g. green beans, peas) or imported frozen vegetable. The incoming fresh products are frozen immediately and packaged in large containers with a content of several kilos. Meanwhile, the imported frozen vegetables that arrive in the factory from approved suppliers overseas are packaged directly into large containers. Consequently, the semi-finished products derive either from the freezing and packaging of domestic fresh vegetables in large containers or the packaging in large containers of imported frozen vegetables. The large containers are then stored in a chamber for semi-finished products until there is a need to put them into consumer packaging. Packaging follows a rolling and controlled programme based on the sales target. Then the semi-finished product passes on a belt to mechanical equipment that bags it and puts it in a sachet/pouch. Workers stack the sacks in cases and, finally, palletise the cases. Consequently, the finished product derives from the packaging in sacks, cases and pallets of the semi-finished product. Figure 13.1 depicts all the warehouse operations. 13.3.2.1

Receiving process

A container carrying fresh vegetable arrives and stops at the assigned bays outside the warehouse. The products on the bed of the container are unloaded onto a conveyor, which triggers the production line.

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Receiving process

Manufacturing process (freezing) Storage process (semi-finished product) Packaging Storage process (finished products in pallets) Replenishment

Picking process

Shipping process

Storage process (finished products in cases) Figure 13.1 The most important processes that take place within the central warehouse.

13.3.2.2 Manufacturing process The freezing process is seasonal, based on a harvest that starts in May. By the end of December the last vegetables have been picked, processed and stored as semi-finished products. The actual process of freezing a food item varies somewhat, depending on what is to be frozen. Peas are the most common frozen vegetable. The pea process is typical for many vegetables. A typical process for a frozen entrée involves the following steps: ● ● ● ● ● ●

cultivating the peas; picking and washing; blanching; sorting; inspection; partial cooking in the oven and then freezing.

13.3.2.3 Quality controls Frozen foods must be carefully inspected both before and after freezing to ensure quality. When vegetables arrive at the processing plant, they are given a quick overall inspection for general quality. The peas are inspected visually again in the penultimate step above, to make sure that only appropriate quality peas go on to the packaging and freezing step. Laboratory workers also test the peas for bacteria and foreign matter, pulling random samples from the production line at various points. 13.3.2.4 Packaging process The frozen vegetables pass on a belt to mechanical equipment that bags them and puts them in a case. Then, workers dressed in cold-weather gear for protection palletise the cases. The pallets are stored in a warehouse cooled to between −17.8 and −28.9°C. They remain there until there is demand from the customer.

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13.3.2.5

Storage process

Although there is a warehouse management system (WMS) in place, the process of storage of semi-finished products depends heavily on quality variation and use of the first-in-firstout principle (FIFO). It is impractical to have predetermined fixed positions because of the characteristics of the particular products. As a result, the assignment of the semi-finished products to storage locations is somewhat haphazard – products are not stored in designated fixed locations, so there is a random storage scheme. The system considers only the production and expiration date of the products. The produced goods enter the warehouse, are analysed by quality control and are released automatically by the system a certain number of days after the production date. The finished product is stored in two chambers: one that consists of pallets of finished products and one that consists of cases of finished products.

13.3.2.6

Picking process

Whenever an order is requested, the picking list is generated. An operator of an indoor forklift truck picks up the corresponding products from the designated locations by using the WMS and by perception. This policy of marshalling products for delivery is chosen because it is easily deployed and it is easy for order integrity to be maintained. The multiple orders are picked consecutively and are accumulated by applying a first-come-first-served (FCFS) logic that combines orders as they arrive until the maximum cubic and weight capacity of a container has been reached.

13.3.2.7

Shipping process

Before being transported, the products for one truck are lumped together at a provisional position. At that time, an operator gives them a compliance check. After that, a truck arrives at the designated loading bay and all products are loaded onto the truck. The truck then departs for its destination.

13.4 ALTERNATIVE RFID IMPLEMENTATIONS 13.4.1 RFID decisions RFID can be applied in different ways, each bringing its own benefits as well as requirements in cost and infrastructure. The decisions that define alternative implementations of RFID-enabled traceability involve the following issues: ● ● ● ● ●

●

the number of RFID readers used; the location of the RFID readers; the application level of the RFID tags (pallet, case, item); the RFID tag attachment procedure on the products (in-house or outsource); the level of automation during the RFID tag attachment procedure on the products (manual or not); the attachment method of the RFID tags, i.e. pre-program and then attach the tags or these will happen simultaneously;

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217

Alternative RFID implementations based on cost-benefit parameters.

Deployment characteristics

Base scenario

Medium scenario

Full scenario

Tag reader locations

Readers only at points where product movements occurs

Readers only at points where products movement occurs Readers in means of transport

Readers only at points where products movement occurs Readers in means of transport Readers inside storage locations

Level of tagging

Pallet, case

Pallet, case

Pallet, case and item

Cost

Low

Medium

High

Benefits

Pallet/case traceability requirements are fulfilled

Pallet/cases traceability requirements are fulfilled Visibility of products while being transported Automatic recording of conditions, monitored by tags inside trucks

Items’ traceability requirements are fulfilled, even in stores Visibility of products inside storage locations and ease in locating them

● ●

●

●

the packaging of the RFID-tagged product items in cases to ensure their readability; the movement of RFID-tagged product cases through the RFID readers, i.e. one or multiple cases at a time; the quantity, the quality and the type of information provided to the users during the business process; the method of providing information to the users during the business process, e.g. by report or alert.

The alternative RFID implementations based on cost-benefit parameters are summarised in Table 13.1.

13.4.2 RFID improvement opportunities Possible RFID implementations resulted from the recognition of inefficiencies within the warehouse. The implemented RFID scenario was expected to satisfy and improve most of these inefficiencies. Through the interviews that were conducted, the inefficiencies within the warehouse were identified as: ●

●

●

●

the need for automatic tracing of quality controls, which required electronic data entry of the files of agronomists and food technologists; the need for more efficient picking of the semi-finished product pallets, which were stored without precise recording of their location; the need for automation of the replenishment process between the chamber where the finished products were stored in pallets and the chamber where they were stored in cases; the need for precise tracking at case level within the dispatch locations.

Based on current inefficiencies, the possible RFID implementations were:

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Internal traceability

Tracing

Production

Storage

Agronomists files

Semi-finished products

Tracking for 2 order picking (FIFO)

Distribution Shipments to central warehouses

Replenishment

Quality controls

Electronic data entry for 1 tracing

Finished products’ pallets

Finished products’ cases

Automation of storage and replenishment (in-bound, out-bound)

Tracking

Shipments to stores

3

Tracking at case level 4

Figure 13.2 Alternative RFID implementations based on improvement opportunities.

●

●

●

●

electronic data entry of information regarding quality control (tracing): a lot number is assigned to a particular quantity in order to provide a link with the manufacturing process information (quality tests of agronomists and food technologists); tracking for order picking (internal traceability), leading to efficient picking of pallets of semi-finished products using FIFO; automation of storage and in-bound and out-bound replenishment (internal traceability), leading to automation of the replenishment process between the chamber where the finished products were stored in pallets and the chamber where they were stored in cases; tracking at case level of shipments to central warehouses and stores, where the lot number would relate cases with dispatch locations.

The possible RFID implementations are depicted in Figure 13.2.

13.5 THE SELECTED RFID PROJECT 13.5.1 Description From the alternative RFID options, it was decided to implement the first and fourth, due mainly to cost considerations. The detailed description of the final project incorporating the two chosen implementations is as follows. When the freezing process is finished, the technologist performs sample tests (microbiological, natural and chemical) and according to their results, the product quality is defined. The results of these tests would in future be recorded electronically, in order to be able to automatically link the lot number of the semi-finished products with the files of the technologists. The semi-finished product would then be stored in the chamber for semi-finished products until there was a need to put them into consumer packaging. Packaging follows a rolling and controlled programme based on sales targets. The semi-finished product passes onto a belt, which delivers it to mechanical equipment that

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Tracing

219

Food technologists files Lot number of semi-finished product

Internal traceability

Tracking

Lot number of semi-finished product Lot number of finished product

Lot number of finished product Dispatch locations

Figure 13.3 The RFID scenario offers full traceability.

Figure 13.4 The implemented RFID scenario.

bags it and puts it in a sachet/pouch. When it is packed in sachets, the change of state from semi-finished to finished product will be recorded. This means that the lot number of the semi-finished product will be related to the lot number of the finished product. At this point RFID tagging will take place at case level. Afterwards, RFID readers will be placed in the shipping areas. During loading, the overall bill of goods, the RFID tags of the boxes and the shipping bay will be recorded. Through the interconnection of the RFID system with the WMS, which maintains all the data related to orders and routes, it would be possible to relate the lot number of the finished product with the dispatch locations. Finally, the system will provide the possibility for two types of reports: (i) (ii)

tracing, which will give the possibility of retrieving quality control data by providing a specific lot number; tracking, which will give the possibility of recovering the current location of products of a specific lot.

The implementation of this scenario provides full traceability, as indicated in Figure 13.3. Figure 13.4 summarises the implementation scenario.

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Figure 13.5 The functionality of the proposed RFID-enabled traceability system.

13.5.2 The functionality of the proposed traceability system The RFID-enabled traceability system functionality can be summarised as follows: ●

●

● ●

electronic data entry of the information regarding the quality tests, enabling cross-correlation of the lot numbers of semi-finished products with product testing data (microbiological, natural, chemical) of the semi-finished product; recording of the change from semi-finished to finished product, enabling cross-correlation of lot number of semi-finished to finished products; recording of product shipments, enabling cross-correlation of lot numbers of finished products with dispatch locations; generation of reports for tracing and tracking.

Figure 13.5 depicts the functionality of the proposed RFID-enabled traceability system.

13.6 THE PILOT IMPLEMENTATION 13.6.1 Evaluating the RFID-enabled traceability system During the pilot implementation, an analysis was conducted in order to evaluate the recently installed RFID-enabled traceability system. Mostly interest was focused on whether the new system produced more profitable results during a recall of a defective batch of a product and

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Distribution of the initial set-up cost per year.

RFID-enabled traceability system

1st year 40% €

2nd year 30% €

3rd year 30% €

10 800

8100

8100

on the 30% of the total market, which represents only the clients with direct distribution from the factory. The analysis was based on two different scenarios. The first scenario assumed that there was no traceability system installed, while the second looked at the situation with the traceability system that had been pilot implemented. The main problem of such an analysis was to define what would be regarded as the recall cost and how it could be measured with regard to the amount of money and time that is needed to recall a suspicious batch of a product. In a product recall, it is significant whether the product has already been placed on the market or not. In each case the measures are completely different. The current analysis considered the worst-case scenario, where the defective products have already been placed on the market at a large number of locations and therefore many additional costs had to be considered. The first and almost significant cost is transportation, where the defective products are returned to the factory for destruction. This cost is considered to be the product of the cost of each route and the number of routes that are required for a product recall, and is directly related to the propagation of the defective products. However, this cost can be greatly reduced if the recollection is performed when a new delivery is made. During the recall procedure another cost is important: the cost of examining all the products that have been distributed to the market to reveal the defective ones. However, this cost may not be relevant if the examination is performed by employees of the customers. The most important cost, however, is lost sales: the company loses sales of the product because during a recall period all further shipments of that particular product are forbidden until it is confirmed as safe for sale. Furthermore, the cost of the RFID tags at case level constitute an important cost. Finally, a cost that is not directly associated with the recall procedure, but is of great importance, is the initial set up cost for the introduction of the new technology in the company. This cost, calculated at €27 000, is distributed over a 3-year period (40%, 30%, 30%) according to Table 13.2. To produce more accurate results the analysis categorised all the frozen products that the company produced into four major classes according to two important characteristics: volume and cost of production. These classes were: (i) (ii) (iii) (iv)

high production volume and low production cost; high production volume and high production cost; low production volume and low production cost; low production volume and high production cost.

Table 13.3 describes the main characteristics of each category. The total annual production of the company was calculated at 2 500 000 cases of products, which requires on average a €375 000 cost for RFID tags. However, due to the fact that only 30% of the market was being examined, this cost was reduced to €111 250. For

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Class characteristics.

Production cost per item ∼ ∼2,50 ∼ ∼5,00 ∼ ∼1,40 ∼ ∼4,90

Cases distributed or produced (per day) ∼ ∼500 ∼ ∼300 ∼ ∼20

€ € € €

Table 13.4

RFID tags cost (per year) ∼ ∼20 000 € ∼ ∼12 000 € ∼ ∼850 € ∼ ∼1000 €

∼ ∼25

Difference.

Difference (per product class) Class 1 € 19 764

Class 2 €

Class 3 €

Class 4 €

10 212

3900

4464

more simplicity in the results, since the production rate in each class of product in an annual period has little variance, it was supposed to be fixed during the 3-year amortisation period of the new system.

13.6.2 Results In order to have a more comprehensive understanding of the impact of the RFID-enabled traceability system, the following metrics have been introduced: ●

●

●

difference, which is measured as the total recall cost for each product before the RFID, less the total recall cost after the installation of the RFID system; benefit, which is calculated as difference multiplied by the number of times a recall procedure was required for a product during a year; profit, calculated by subtracting the cost of the initial set up and the RFID tags’ cost from the total benefit for the year examined. The total benefit corresponded to the aggregation of the benefits of each separate class, which was achieved in the case of a product recall.

This mathematical analysis produced Table 13.4, which indicates the difference for each product class. A vector was produced, representing the total benefit: 19764 x1 + 10212 x2 + 3900 x3 + 4464 x 4 x1 , x2 , x3 , x 4 ∈ Ζ where x1 stands for the number of times a recall procedure was required for Class 1 products, x2 stands for the number of times a recall procedure was required for Class 2 products, etc. Finally, with the help of the above vector the profit can be calculated, and determination made of the minimum range of times a product recall must take place in any year in order for the recently installed IT to have a positive effect on profit.

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Table 13.5 Recall cost reduction rates due to new systems. Product class Class Class Class Class

Reduction rate %

1 2 3 4

90.3 89.0 92.0 92.2

Product recall cost 25,000

21,887

20,000 15,000

11,472

10,000 4,842

4,240 5,000

2,123

1,260

340

378

0 Class 1

Class 2 Old information system

Class 3

Class 4

New information system

Figure 13.6 Total recall cost for each product class.

After mathematical analysis, the RFID-enabled traceability system indicated a spectacular reduction in recall cost for all product classes: about 90% below the initial cost. Analytical measurements are represented in Table 13.5. In order to make these findings clearer, Figure 13.6 indicates the actual recall costs for each class each time a recall of a product is being conducted. This cost reduction is a consequence of the reduction of the number of possible locations in which a defective product can be located, that also being due to the visibility that the RFID system provides. As indicated in Figure 13.7, when no information exists the company is obliged to check all of its clients, whether they have any of the defective product or not. However, after the installation of the new system, the number of possible locations is greatly reduced. The reduction is extremely high, particularly for products with low production volume. Reading Table 13.3 again, a very interesting assumption can be made: if the company was interested in applying the RFID technology to only specific products, then it would be more profitable to install it on products with high rather than low volume production because the recall cost of a product with high production volume is many times higher than the recall cost of a product with low production volume.

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Intelligent Agrifood Chains and Networks Product visibility - 30% of total market 386

386

386

386

Number of possible locations

400 350 300 250 200 150 64

100

64 20

50

20

0 Class 1

Class 2

Class 3

Class 4

Product class Old information system

New information system

Figure 13.7 Possible locations of a defective product.

13.7 CONCLUSIONS This chapter describes work undertaken for a company that deals with frozen food, in respect of the requirements’ analysis, development and pilot implementation of a RFID-enabled traceability system within the central warehouse. The main findings can be categorised into two foci: the specific case implications and the evaluation method implications. Regarding the case study implications, it can be concluded that the RFID-enabled traceability system that the company installed is cost-effective and profitable, especially when a number of product recalls are conducted over a year. However, more research should be carried out into whether it would be even more profitable to use RFID technology, not only in the company’s warehouse, but also in the distribution trucks and even at clients. In respect of the evaluation conducted, it may be considered a method to identify the performance advantages behind investing in an RFID-enabled traceability system (to-be system) compared to a paper-based one (as-is system). As a result, it is a planning guide that any organisation interested in moving to an RFID-enabled traceability scheme can refer to in order to appraise and assess such a deployment. However, further work is required on applying such an evaluation to another case study, in order to measure the value of a RFID-enabled traceability system.

ACKNOWLEDGEMENT This work was partly funded by the General Secretariat for Research and Technology, Ministry of Development of the Hellenic Republic. The authors would like to thank all the partners that participated in the project for their support.

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REFERENCES Agarwal, V. (2001) Assessing the Benefits of Auto-ID Technology in the Consumer Goods Industry. Cambridge University Auto-ID Centre, Cambridge. ECR Europe (2004) Using Traceability in the Supply Chain to Meet Consumer Safety Expectations. ECR Europe Publications, Brussels. Available at: http://www.gs1nz.org/documents/ECR_Bluebook_final.pdf. EU (2002), Regulation (EC) No 178/2002 of the European Parliament and of the Council, Official Journal of the European Communities. Available at: http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ: L:2002:031:0001:0024:EN:PDF GCI (2005) EPC: A Shared Vision for Transforming Business Processes. Global Commerce Initiative (GCI)/IBM. Available at: http://www.gci.org. Golan, E., Krissoff, B., Kuchler, B., Calvin, L., Nelson, K. and Price, G. (2003) Traceability for food safety and quality assurance: mandatory systems miss the mark. Current Agriculture, Food and Resource Issues, 4, 27–35. Available at: http://cafri.usask.ca/j_pdfs/golan4–1.pdf. Hamner, S. (2005) The grocery store of the future. Business 2.0 Magazine, March, pp. 23–28. Hou, J.L. and Huang, C.H. (2006) Quantitative performance evaluation of RFID applications in the supply chain of the printing industry. Industrial Management and Data Systems, 106(1), 96–120. ISO, E.S. (1995), EN ISO 8492.1995, European Committee for Standardization, Point 3.16. Kelepouris, T., Pramatari, K. and Doukidis, G. (2007), RFID-enabled traceability in the food supply chain. Industrial Management and Data Systems, 107(2), 183–200. Kelly, E.P. and Erickson, G.S. (2005), RFID tags: commercial applications v. privacy rights. Industrial Management and Data Systems, 105(6), 703–13. Littlefield, M. (2006) Compliance and Traceability in Regulated Industries, Benchmark Report. Aberdeen Group, Boston, MA. Pramatari, K.C., Doukidis, G.I. and Kourouthanassis, P. (2005) Towards ‘smarter’ supply and demand-chain collaboration practices enabled by RFID technology. In: Vervest, P., Van Heck, E., Preiss, K. and Pau, L.F. (eds) Smart Business Networks. Springer Verlag, New York. Shutzberg, L. (2004) RFID in the Consumer Goods Supply Chain: Mandated Compliance of Remarkable Innovation? Rock-Tenn Company, Norcross, GA. Smith, H. and Konsynski, B. (2003) Developments in practice X: radio frequency identification (RFID) – an internet for physical objects. Communications of the AIS, 12, 301–11. Van Dorp, K.J. (2002), Tracking and tracing: a structure for development and contemporary practices. Logistics Information Management, 15(1), 24–33.

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14

Intelligent Agrifood Chains and Networks: Current Status, Future Trends and Real-life Cases from Japan

Mihály Vörös and Masahiko Gemma

14.1

INTRODUCTION

Food markets are becoming increasingly international and global in developed and developing countries all over the world. At the same time, urbanisation has increased the physical and psychological distance between urban and rural residents and it has separated city people from knowing where, how and by whom the materials for their food are produced, grown and processed. As a consequence of rapid urbanisation, the proportion of agricultural production has been diminished in the national economy in developed countries. There exist secure food supply systems, but usually less than 5% of the population produce food. Under such circumstances, where consumers are distant from the scene of food production, many lose appreciation of existing food systems, become indifferent to agricultural landscapes and are unaware of the multiple ecosystem services provided by rural areas and agricultural production. Because of the increased distance from production, consumers are often completely unfamiliar with the impacts of production practices on land, which consequently determine the local ecology and the quality of raw materials for food production. The food manufacturing process is also unknown for urban consumers, which may lead to further risks concerning the nutrition value of food. There is an increasing interest in diet and health, as well as the environment, but at the same time most urban consumers are concerned with only product quantity and prices in supermarkets. Major new trends in global economics, politics and social life all point to a ‘global paradox’. According to John Naisbitt (1994), ‘the bigger the world economy, the more powerful its smallest players’. As the overall system grows in size and complexity, the importance of the individual parts is going to increase. Considering the growing concerns about energy and agricultural security, and the perceptible phenomena of global warming, there is currently a strong political desire at both global and national levels to ‘re-localise’ food and energy production and supply. The re-localisation strategy has been developed in response to the environmental, social, political and economic concerns on the over-reliance on lower cost energy with no regard to whether it is renewable. Re-localisation is a strategy to build societies based on the local production of food, Intelligent Agrifood Chains and Networks, First Edition. Edited by Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis. © 2011 by Blackwell Publishing Ltd. Published 2011 by Blackwell Publishing Ltd.

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energy and goods, and the local development of currency, governance and culture. The main goals of re-localisation are to increase the local community’s energy and food security, to strengthen local economies, and to improve environmental conditions and social equity. Nevertheless, better understanding of the background of good-quality food and active linkages between urban and rural people can be built by promoting local food systems and establishing connections to the rural landscape. Viable examples of positive linkages include on-farm direct sales, community-supported agriculture and direct farmers’ markets, locally grown food in supermarkets and eco-belts that help to link rural and urban areas with activities of common interest. Urban people who are closer to their food supply can become more engaged and informed consumers who will support an ecologically sound food production system, as well as appreciate a healthy multifunctional rural landscape.

14.2

GENERAL CONCEPTS AND ROLES OF THE LOCAL FOOD SYSTEMS FOR IMPROVEMENT OF QUALITY OF LIFE

This study defines ‘sustainable development’ as comprising three interdependent and mutually reinforcing pillars: (i) economic and social development coupled with a regard for the natural environment or the ecological system; (ii) the people who are the main element of the development; (iii) harmonised coexistence, which should be established at local, national, regional and global levels (United Nations, 1992). The new paradigm of sustainable development establishes linkages across poverty alleviation, human rights, peace and security, cultural diversity, biodiversity, food security, clean water and sanitation, renewable energy, preservation of the environment and the sustainable use of natural resources. This view of sustainable development seeks to ensure a better quality of life for everyone, now and for the generations to come (Turchany, 2008). From this wide selection of issues on sustainable development, exploring local food systems, we intend to touch on and emphasise the issues of biodiversity and food security. In this study, a local food system (LFS) is defined as a unique micro-agro-social-ecological system characterised by special natural endowments, soil micro-organisms, climatic conditions, crop varieties and livestock breeds as well as labour and technical resources and infrastructure, which are operated and utilised by food producers and consumers living and communicating in a certain region to produce and supply agricultural and food products according to diversified consumer needs in that region and outside. In order to utilise and sustain the ecosystem as the most important subsystem of a local food system, ‘multifunctional agriculture’ should be organised and operated. Besides the main function of producing high quality food and nutrition as private goods for the population, multifunctional agriculture can also provide wide varieties of public goods: environmental protection, biodiversity and different cultural and rural values (e.g. landscape, health care and recreational capacities, cultural heritage, food culture, etc.). The organisation of multifunctional agricultural production with respect to protecting and sustaining the environment should be based on a good understanding of the basics of the local ecosystem and nutrient cycle, which include biodiversity (Une, 2006, 2009). The food

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supply in the local food system either consists of a large integrated logistic chains or simple, direct and local sales, which have a strong organic relationship with several (human, machinery, etc.) activities, and processes which all influence the quality of the end product and the natural environment. Local ecosystems and the nutrient cycle are complex systems and, as far as agriculture and food industry are concerned, they are inescapably intertwined with the natural environment and the biodiversity on which food systems are based. Supplying good-quality food with healthy nutrients for people in any part of the world means that these systems should be operating in harmony. Following a simplified approach, the food supply chain (FSC) (or food logistics network) is understood as a system of organisations, people, technology, activities, information and resources that is used to move food products or services from suppliers to customers. Supply chain activities transform natural resources, raw materials and their components into a finished product that is delivered to the end customers. A typical supply chain incorporates the human extraction of raw materials and includes several production links, for instance component construction, assembly and merging, before moving onto several layers of storage facilities as well as remote geographical locations, and finally reaching the consumer. The size, level and dimensions of the FSC can be diversified. Many of the exchanges accomplished in the food supply chain take place between different companies, which are seeking to maximise their revenue and profit within their sphere of interests. In several cases, they might have little or no knowledge or interest in the remaining players in the supply chain. There is no direct connection between producers and consumers. During the daily operation and practice of the highly developed, widely spread and successfully managed FSC, the ‘roots’, namely the close relationship with the natural environment, the guarantee of the quality and the nutrient value of the end products, have, in many cases, been neglected, forgotten or not understood properly. Based on cognitive experience, these determinants are often missing from the advanced well-designed marketing communication channels of food. We should emphasise, however, that this information gap might easily threaten the sustainable development of the natural environment, as well as food safety, health, living conditions and quality of life of people. The decisive role of the food industry should be emphasised at this point with regard to the proposed quality and healthy characteristics of the end products and the risks concerning concealed production abuse (e.g. pesticides, contaminants, disinfectants, food additives, etc.). In a fact-finding book on this topic, an American nutrition scientist wrote, ‘I have often wondered what role the food industry might play in creating an environment so conducive to overeating and poor nutritional practices and so confusing about basic principles of diet and health’ (Nestle, 2002). In well-organised food systems, there might be different channels to supply fresh, goodquality and tasty food to the customers. According to our definition and understanding, we distinguish the terms ‘food supply chain’ and ‘local food system’ (LFS). An LFS is quite different and has a much more complex system than the establishment, organisation and management of an FSC, which is a business organisation for supplying (producing, storing, processing, selling, etc.) food for people living in different geographical locations around the world. An LFS, on the other hand, is inescapably inter-twined with the natural environment and biodiversity. It is also involved in the food consumption cycle in the backdrop of not only the local community concerned but the whole of society in general. In this study, a sustainable local food system includes harmonised development and operation of multifunctional agriculture, an advanced food and nutrition policy to promote

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the local consumption of local food products and to preserve or revitalise traditional food culture in a certain region by effectively utilising local natural and human resources, production inputs and infrastructure within that region in order to contribute to its sustainable economic and social development. In such regions, communication between producers and consumers is more intensive and developed. An increasing number of local food consumers prefer to buy and eat great variety of healthy, fresh, local and/or traditional food products. ‘Chi-shoku’ 地食 (area food) and ‘Dentoshoku’ 伝統食 (traditional food) are the Japanese words expressing the existence of local food and its long history. An agricultural and rural economics study by Forsman and Paananen (2004) highlights characteristics of local food very well, stating that in a particular region, ‘… local food production is supported by the fact that regional and local characteristics such as certain raw materials and dishes, tastes, as well as food traditions and food culture might always be closely tied to particular regions creating and maintaining the identity of these regions’ (Forsman and Paananen, 2004). Thus, from a policy standpoint, strengthening the local community in rural regions means to contribute to its sustainable economic and social development. Building links around food is an ideal way to do it. There are different reasons and objectives which necessitate and justify spatial and economic re-composition of food chains, strengthening local food systems. Forsman and Paananen (2004) summarise them as follows (see Table 14.1): ●

● ●

●

●

● ● ●

retaining income locally, with multiplier effects from local purchases, which support local businesses; capturing value added through local processing, distribution and consumption; equilibrating environmental and socio-economic disadvantages associated with intensive farming and increasing sustainability; compensating uneven distribution of industrial forms of agriculture in core agricultural regions; improving relationships between, on the one hand, farming and the rest of the food chain and, on the other hand, farmers and final consumers, spreading risks; strengthening local connections and sense of identity; building local capacities and retaining/developing skills; raising morale, confidence, social competence and awareness of local assets.

In spite of growing awareness of the importance of healthy nutrition and a viable environment, we are continually surprised by the general population’s high level of disinterest in food. One ongoing challenge is finding ways to motivate sceptical and complacent consumers to allocate their budget to local food so that local production becomes financially sustainable. Another is to encourage people’s decisions to invest and improve their houses and surroundings, and to discourage city residents from converting farmland for non-farm use. Advanced information and communication technology (ICT) and improved approaches and tools to be used in education from nursery to university levels can open up new prospects (United Nations Decade of Education for Sustainable Development). It is best for people to learn about ecosystem services and the need to understand where and how healthy food is produced, how this impacts the ecosystem, and how urban and rural people can work together to cross the boundaries that currently divide them. There are examples such as Japan, where policy tools have been developed to revitalise traditional dietary customs, to promote local consumption of local produce, to build ‘cultural bridges’ between urban and rural people, and to generate knowledge of human and technical resources for strengthening local food systems.

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Current Status, Future Trends and Real-life Cases from Japan Table 14.1

231

Summary of the dimensions associated with local food.

Local food processing firms

Retailers

Restaurants and institutional catering units

Rural tourism enterprises

Freshness Knowledge of origin ‘Products have faces’ Covering the whole chain from production to consumption Available only on a local basis

Freshness High quality Home-made type of food Small-scale production

Freshness High quality No additives Seasonal products

Freshness High quality Authentic taste Purity

Local home-grown raw materials

Non-industrial products

Regionality

Handicraft products

Short distances

Not nationally distributed Small-scale production Artisan entrepreneurship

Local taste experiences

Just-in-time deliveries

Natural products (e.g. berries, mushrooms, herbs) Transparency of the food chain Regionality

Short distances Differentiation from mass production

Increased food safety Maintenance of regional food traditions Educational value Employment of ocal people

Regional development Maintenance of regional food traditions

Source: Forsman, S. and Paananen, J. (2004). Reproduced with permission.

14.3

DEVELOPMENT OF LOCAL FOOD SYSTEMS IN JAPAN

The cases observed in Japan can serve as examples of development in local food systems. We study how the development of the local food system was feasible in Japan. Derivation of general policy implications is our final goal. In the last half century, the land, technology and human resources of agriculture, as well as the traditional rural communities and dietary patterns of people have been undergoing a radical transformation in Japan. The 2005 annual Ministry of Agriculture, Forestry and Fisheries (MAFF) report observes that: Rural communities have borne a variety of roles, besides the aspect of agricultural production, such as the preservation of traditional culture and mutual assistance among residents of regional areas. However, they have been greatly transformed due to the decline in farming households and the advance of multi-habitation associated with urbanisation, among other factors. (MAFF, 2005a)

In the period between 1965 and 2005 the share of agricultural production and contribution to overall gross domestic product (GDP) reduced from 9.0% to 1.0%, the agricultural working population from 11.96 million to 2.52 million, the proportion of the total working population employed in the sector from 26.6% to 4%, and the number of farming households from 6.06 million to 2.85 million. This radical transformation was also caused by changing composition of farming households whose members do not work in agriculture. The number of part-time farming households earning most of their income from non-farming sources

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73

60

54

53 43

40

40

40

40

40

40

39 40

2007

2006

2005

2004

2003

2002

2001

2000

1985

1975

0

1965

20

Year Self−sufficiency rate (%) Figure 14.1 The declining tendency of the food self-sufficiency ratio* in Japan (calorie basis, %). Source: Ministry of Agriculture, Forestry, and Fisheries (2008). * The food self-sufficiency ratio (calorie basis) in this diagram is calculated by the following formula: Food Self-Sufficiency Ratio = Domestically Produced Calorie Supply per Total Domestic Calorie Supply multiplied by 100.

increased rapidly. At the same time, self-sufficient farming households producing for their own consumption also increased. This type of farm does not sell their farm produce, except for their surplus production, which is sold in local direct farmers’ markets (‘Chokubaijo’). In some of these households, all people in the family work in non-farming jobs and tend to take part in farming activities only at weekends. The most fundamental macroeconomic impact of this transformation was the gradual decrease in the food self-sufficiency ratio (FSSR), from 79% in 1960 to 43% in 1995, and to 39% in 2006 (see Figure 14.1). Japan’s FSSR is the lowest among developed countries. The key agricultural products have low FSSRs: 14% for wheat, 3% for soybeans, 39% for fruits and nuts and 55% for meat in 2006. The declining trend in FSSR in Japan can be explained not only by the shrinkage of agriculture, but also by the change in food consumption. Dietary habits in Japan have changed considerably, particularly after World War II. The main factors which affected and will continue to influence these dietary changes are: ●

●

● ● ●

● ●

●

decreased domestic agriculture production and increased food import as well as expanded export of manufactured goods; migration of labour from agriculture and rural areas to industrial urban areas where the lifestyle is different; increased income for families to purchase food; rapid economic growth, which made people too busy to prepare food for each meal; changing employment structure, developing status of women in Japanese society, and widening employment of women; changing human desires of Japanese people (i.e. increased leisure for hobbies); radical changes in lifestyle (amenity, beauty, community, convenience) of people in Japan (Food and Agriculture Policy Research Center, 1997) – their current eating patterns might be considered as the future of culture; the growing network of Japanese convenience stores, and the ever-growing range of places to eat in Japan, with a tremendous assortment of dishes – traditional Japanese food, fast food of Japanese and western styles, family restaurants, ramen or noodle shops, ‘sushi’ restaurants, etc.

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Table 14.2 Comparison of the actual and the desired protein:fat:carbohydrate ratios and their deviations in 1985 and 2007 in Japan*.

1985 2007

Ratios based on consumption figures in the food balance sheet

Desired ratios

P

F

C

P

F

C

13.1 12.9

27.3 28.8

59.7 58.3

12.5 13

25 27

62.5 60

Deviation 5.7 3.6

P, protein; F, fat; C, carbohydrate. Sources: Higuchi, T. (1991), p. 90, Table 1; MAFF UPDATE, Overview of the 2007 Food Balance Sheet, 2008.

In the last four decades, per capita rice consumption decreased from 120 kg to 60 kg. This is unfavourable, not only considering its relationship with the declining tendency of FSSR, but also from a nutritional point of view (Ito et al., 2007). According to dietary recommendations, it is very important to maintain a good balance in the cereal-to-protein ratio. Starch as a proportion of the total energy intake represents an important indicator of Japanese dietary habits. However, a high proportion of starch from rice and soybeans can provide more than half of the calorie intake. Exceeding that amount can increase the carbohydrate intake, which might not be favourable for health (Higuchi, 1991). Our small sample household survey in rural or urban-agricultural regions confirmed that ‘traditional’ diets can alter a little from the standard (optimal or desired) protein-fatcarbohydrate (PFC) ratios. In Table 14.2, a comparison is made between the actual and desired PFC ratios between 1985 and 2007. The overall deviations from the desired levels of food intake become smaller over time. However, fat intake increased while carbohydrate intake declined. The decline of rice consumption and the increase in meat consumption have impacts on these structural changes in nutrition intake. Experts have called for policy responses to stop the worsening trend of nutritional intake in Japan. Ito et al. (2007) state that ‘some sort of food education to learn about domestic food culture and nutrition has to be provided at school and the community level, so that young generation should pursue their own traditional food culture and suitable diet.’ (Ito et al., 2007) The latest MAFF report also shows the negative consequences of the heavy reliance on imported foods, stating, ‘reconsider today’s dietary pattern that depends heavily on imports and generates a lot of food waste; and establish a system for the stable supply of safe food on a long-term basis as soon as possible’ (MAFF, 2008a). Japan is the largest agricultural and food product importing country in the world, resulting in a very high level of ‘foodmileage’ in tons-kilometre, a complex environment indicator. Japan’s total volume of food imports in 2001 was 58 million tons. As Nakata puts it: Japan’s food-mileage is estimated to equal approximately 900 billion tons-kilometre as calculated based on a concept according to which food mileage equals the volume of transported food multiplied by the distance transported, a figure that is dramatically higher than any other country’s. Comparing this food-mileage with the USA the US figure is 40% of the level of Japan. The same figures for the United Kingdom and Germany are both at the level of 20%. France is only at 10% of the level of Japan. (Nakata, 2003)

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To ease food production and consumption problems, Japan has been implementing a set of comprehensive policies covering programmes in agricultural and rural development, as well as nutrition education programmes. Like the EU’s Common Agricultural Policy, the multi-functional nature of agriculture is taken into consideration in the policy goals of protecting the natural environment and improving rural development function of agriculture. Besides the improvement of macroeconomic conditions, the local economy and social goals have received priority as ways to improve the quality of life of people in rural areas. This set of agricultural, food and rural development policies is based on improved legislation: the Basic Law on Food, Agriculture and Rural Areas (FARA)1 and the Basic Law on Food and Nutrition Education (FNE) (MAFF, 2008b). These two laws were enacted in 1999 and 2005. Both laws were jointly designed to be consistent and coherent. From the policy perspective, the government of Japan is aiming for a balanced policy for producers and consumers of agricultural products. Another goal of the policy is to build close communication links between rural and urban societies, which we have referred earlier as ‘cultural bridges’. The FNE (MAFF and Cabinet Office, 2006) interrelates with the basic law of FARA and substantiates the complex agriculture and food policy in Japan. The law incorporates several interrelated policy tools and indicators for improving knowledge about healthy nutrition and dietary life nationwide. The main objectives, policy tools and expected impacts of the FNE law are that it: ●

●

●

●

●

promotes people’s health in body and in mind and promotes nutrition in education2 as a base of intellectual ‘Chiiku’, moral ‘Tokuiku’ and physical ‘Taiiku’ education; encourages people to understand their diet better, including knowledge of the various roles and effects of food (natural environment, farmers, producers, etc.); organises voluntary movements nationwide for promoting ‘Shokuiku’, which spreads food-related experiences and activities to improve understanding of proper diet and considering children as the most important target group; aims to improve awareness and appreciation of traditional Japanese food culture, which includes the interaction between food producers and consumers (revitalising rural farming and fishing regions, rising food self-sufficiency); encourages the dissemination of food safety information and practice for a proper diet through collaboration with stakeholders in society.

In accordance with Chapter II, Section 4, Article 36 of the FARA basic law, the government of Japan determines objectives and indicators in the Basic Plan (MAFF, 2005b, p.6) for promoting local consumption of local produce, as well as giving consumers opportunities to purchase local agricultural produce and foods, given a ‘transparent and accessible’ relationship with producers. In order to achieve this policy objective, local agriculture and related industries should also be promoted. ‘Local Consumption of Local Produce’ (LCLP) is promoted in Japan. A short Japanese term for this expression is ‘Chisan Chisho’ 地産地消 (MAFF, 2007), which is used as a

1

A provisional translation of the FARA Basic Law in English is available at http://www.maff.go.jp/e/index.html. Dates back to the Meiji period, the first book on nutrition education was published by Sagen Ishizuka (1850–1909) and the second by Gensai Murai (1864–1927), who stated that nutrition education has first priority.

2

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promotional slogan for the promotion of local products in local markets. Under the framework of FARA and FNE basic laws, the following three activities are undertaken: (i) communication activity, to promote understanding of local agricultural products among consumers;3 (ii) sales and distribution activity, to distribute local agricultural products within the local community; (iii) exchange activity, to promote interaction between producers and consumers. The implementation guide (MAFF, 2005b, p.2), which calls the attention of the different stakeholders to the following strategic actions, introduces a set of programmes to meet these policy objectives: ● ● ● ●

a nationwide strategy for plain and practical food education; ‘Shokuiku’ and ‘local consumption of local produce’ or ‘Chisan Chisho’; promotion of consumption of rice and other domestic agricultural produce; earning consumer confidence in domestically produced food.

There are some potential problems in promoting local production and consumption of agricultural products. The subsidies for local production might result in delays in modernising the agricultural production sector if uncompetitive farms remain in production. Labour productivity in agricultural production is lower than in other sectors of the economy in Japan. Agriculture produced 1.2% of GDP in 2007, using 4.5% of the labour force. The policy goal of improving the self-sufficiency rate in the food sector needs to be achieved without lowering labour productivity for agricultural production. Otherwise, the policy of local production and local consumption will not be sustainable.

14.4 EXAMPLES OF LOCAL FOOD SYSTEMS IN JAPAN We describe and summarise below some basic features of Japanese farmers’ markets using the results of a recent study in Japan (Vörös, 2009) as well as review and reference materials published in the Japanese professional literature and the websites of direct farmers’ markets (DFMs). According to Japanese government statistics (MAFF, 2008a), around 230 million people visit 14 000 DFMs (‘Chokubaijo’) annually in Japan. This can be considered a result of a successful implementation of the ‘Chisan Chisho’ policy. Besides the increase of food shopping in farmers’ markets, an increasing number of people are using guest farmhouses and farmhouse restaurants all over in Japan. The total sales value of DFMs is estimated at around ¥250 billion annually (Kako, 2008), around a 10% share of the total sales of agricultural products nationwide, but in some regions this share increases to 30–40%. Nowadays Japanese farmers’ markets cannot be considered marginal. Locally produced food is very often promoted in Japan using the word ‘Furusato’ ふるさと, the meaning of which is ‘native land,’ ‘hometown’ or ‘homeland.’ This term is a supplementary term to ‘Chisan Chisho’ 地産地 消 (local product for local consumption) to promote local products. This embodies a very simple, shortly written recommendation for consumers to purchase preferentially the traditional, healthier, home tastes ‘furusato’ foods produced locally by traditional recipes, utilising higher quality and fresh raw materials.

3

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DFMs operating in Japan can be distinguished by their different management forms: ●

●

●

privately owned DFMs, organised and managed by farming families or producer groups; local groups of JA, the nationwide agricultural cooperative organisation, which have established and operate several large DFMs; mixed ownership.

DFMs have been established with the financial contributions by local government and sharing by third sector companies and civil organisations. DFMs are open almost every day, usually for an average of 280 days annually. Over 70% of farmers’ markets are open for more than 300 days per year. DFMs also offer collective sales of products brought by local farmers on commission. Several farmers are in charge of selling on behalf of others, but there are some shops where professional sales staff are employed; DFMs are a special business entity in Japan, an institution which can be supported by public or quasi-public sector bodies (Iizaka and Suda, 2008). Around 70% of customers of farmers’ markets are residents in the same region where the markets are situated, while 30% are either travelling from other regions or are tourists. In mountainous areas, half of the customers of DFMs are tourists. In such areas, DFMs also sell special local food products ‘Dentoshoku’ (e.g. wild mushrooms, dried wild fruits, fish products, jams, processed foods, etc.). In suburban areas of larger cities or in lowlands, there are larger farmers’ markets. The largest farmers’ market in Japan is in Wakayoma prefecture (Kako, 2006), located in a village and managed by JA. Its sales turnover in 2006 was ¥2.3 billion. Around two-third of all farmers’ markets are involved in selling mainly vegetables produced by supplier farmers in the same local region. In these areas, there is growing competition between farmers’ markets and supermarkets. This has a positive influence on choice and the quality of products. Supermarkets are encouraged to supply fresh and authentic Japanese vegetables to be competitive with local DFMs; the customers of the farmers’ markets are sensitive to the freshness of the products (vegetables, fruits, processed food with short expiry periods, etc.) and are also price-conscious. Collective sales on commission are a general characteristic of DFMs in Japan, but in some local regions, individual face-to-face sales methods can also be observed. DFMs operate with farmers transporting their products every morning. One evident management problem is the difficulty of settling accounts for shipments after the DFM closes for the day. Advanced ICT provides appropriate solutions to this problem as well as real-time monitoring of the actual inventory of products, which can also help the exchange of information with producers and customers. Like supermarkets, many larger DFMs have introduced point-of-sales (POS) systems using barcodes on each product item sold in the shop. Two main challenges have surfaced with the use of advanced ICT. One is the cost of the equipment, the other is the difficulties older farmers have in learning the new system. There are real-life examples of the successful operation of POS in Japan. A good example (Iizaka and Suda, 2008) is from Sera-county, Hiroshima prefecture. In this DFM, there are around 100 farmers who are over 60 years old, producing locally and selling more than 70 kinds of fruit, vegetable and homemade foods. After the introduction of ICT, sales tripled because farmers were able to receive sales data and information on the amount of inventory on the shelves every few hours by mobile telephone, thus allowing them to restock all day long. The producers can supply their products to the DFM on a justin-time basis.

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Current Status, Future Trends and Real-life Cases from Japan Table 14.3

237

Development of JA-managed DFMs in Fukuoka Prefecture for 2003–2007. 2003

No. of market places No. of customers (thousands) Total sales value 100M ¥

14 2,050 21.6

2004

2005

26 3,660

31 3,270

35.0

35.9

2006

35 4,380 48.1

2007

41 8,570 83.0

Change index (%) 2003 = 100% 341.5 418.0 384.3

Source: Central Committee of JA Fukuoka (2008).

Table 14.4

The number of JA-registered farmer suppliers.

No. of registered farmer suppliers Rate of increase of farmers compared to the previous year

2003

2004

2005

2006

2007

Changes index (%) 2003 = 100%

4,679

5,672

6,892

7,308

10,039

214.6

100%

121%

122%

106%

137%

137%

Source: Central Committee of JA Fukuoka (2008).

Before introducing POS systems, the farmers had to prepare paperwork for every shipment, but now they only have to take care of shipment itself at the proper time. Their workload has been significantly reduced. They also spend less time on record-keeping. All stakeholders are satisfied with the use of POS. Moreover, this system has reduced the number of mistakes at the checkout, so customers are also satisfied with shorter queue times and the opportunity to have more time for a conversation with the producers. With the use of ICT, it is much easier to build producer–customer communications and provide information about farming technology and any details of the product’s origins. Thus, POS makes just-in-time shipping possible and therefore ensures the freshness of the products. It is also a device that promotes communication between farmers and consumers. The conversations between customers and farmers help the farmers to recognise the needs of their consumers and find out what kinds of crops they should grow. The conversations are informative and useful for consumers. Many consumers want to learn as much as they can from farmers about where and how the products were grown, and how to better prepare and serve them. Most supermarkets are not able to provide such detailed product information. In an official document from the Central Committee of JA Fukuoka, a review of the development of DFMs ‘Chokubaijo’ and local production for local consumption ‘Chisan Chisho’ activity between 2003 and 2007 is as follows (JA Group, 2008). There has been a rapid development of the JA-managed DFM in Fukuoka Prefecture as shown in Table 14.3. In 5 years, the number of market places has increased almost 3.5 times. The number of customers has also increased more than 4 times and the sales value almost 4 times. Table 14.4 shows the increase of the number of the registered suppliers (the farmers must submit applications to JA to get a licence to sell at JA-managed DFMs) in Fukuoka Prefecture for the period between 2003 and 2007.

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Table 14.5 Development of direct farmers’ markets ‘Chokubaijo’ in Fukuoka prefecture for 2003–2007.

No. of market places No. of customers, thousands Amount of total sales value (100M ¥)

2003

2004

2005

2006

2007

Changes index (%) 2003 = 100%

259 11,460

243 12,500

235 15,210

230 17,020

223 21,210

86.1 185.1

141

155

175

200

249

176.6

Source: Agricultural White Book of Fukuoka Prefecture.

In this period, there was a gradual increase in farmers selling products in DFMs as suppliers. Table 14.5 indicates increases in the number of all types of (not only JA-managed) DFMs, the number of customers and sales values in Fukuoka Prefecture for 2003–2007. Considering all types of DFMs in Fukuoka Prefecture, the rate of the development has been not so rapid. The number of market places decreased from 259 to 223 for 2003–2007 while the number of customers increased by 85.1% and the total sales value by 76.6%. In 2007, the total number of DFM customers in Fukuoka Prefecture was 21.2 million, while the sales value was ¥24.9 billion. In order to understand the factors affecting the successful implementation of the local market development, three case studies on different types of management are given below.

14.4.1 ‘Budoubatake’ farmers’ market (privately-owned company) ● ●

Location: Fukuoka City, Fukuoka Prefecture Official website: http: //www2.ocn.ne.jp/~budo-b/about_eng.html

This is a 10-year-old privately owned DFM, established by six farming families living in Fukuoka City.4 The mission statement of the DFM is: ● ●

● ● ●

providing fresh and quality produce directly from farmers to consumers; serving as a ‘cultural bridge’ 文化の架け橋 between rural and urban communities and increasing the understanding of agriculture, farming and food; contributing to preservation of traditional culture, foods, and ceremonies; creating a heart-warming atmosphere for customers, farmers and staff; providing appropriate prices for both farmers and consumers.

‘Budoubatake’ means grape field or vineyard in Japanese. Historically, the origin of the name comes from the fact that the leader of the group was a grape farmer located near the store. This name has a symbolic meaning too. They call each producer supplying products ‘Budou-no-ki’ (tree of grape) and the customers buying products in the market ‘Budouno-mi’ (fruit-of-grape). These words are symbolic of the wish of the business: to grow ‘grape trees’, where each tree (supplier farmer member) is able to produce a lot of ‘fruit’ that generates income for the group. 4

The authors would like to express their gratitude to Dr Shoji Shinkai, his parents and students for their help in conducting interviews in ‘Budoubatake’.

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Before establishing ‘Budoubatake’ in 1999, the founding families organised an informal group, ‘Minatsuki-kai’, and started joint activities (selling some products and studying the production of good-quality agricultural products, food marketing, culinary skills, etc.). During the rapid urbanisation of Fukuoka City, they recognised that they could not only work in their farms but could also open a market place for selling fresh, safe and tasty farm produce and other products for satisfying the needs of a variety of customers in a location near to the rapidly developing city. They recognised also that busy women might have a special role in solving agricultural problems in Japan. In 1988, the 2nd National Health Promotion Program was introduced under the title: ‘Active 80 Health Plan’ This national programme encouraged the activities of Budoubatake. They strongly believed that in a direct farmers’ market place, they could not only sell their products but were also able to organise other farmers from different regions of Japan to join the business. At first, they built a small stand but, day by day, the number of customers increased and therefore they increased the area of the shop. Recently, ‘Budoubatake’ has been operating in the form of a limited liability company. The main owner has a majority share (51%), which provides a simple management structure and operation for the farm business. The management board has nine members. The chairman of the board is the lead owner. Recent employment in ‘Budoubatake’ included taking on four people as full-time employees and 18 as part-time workers. As for the partnership, they now have 150 supplier farmers from different prefectures, providing a range of around 500–600 products. The number of types of vegetables and fruits is around 250–300. These figures include foods like pickles, jam, lunch-boxes, milk, bread, etc. Approximately 250 different types of foods originate from local farmers or are ‘Obento’, lunch-boxes, produced in the kitchen of ‘Budoubatake’ by old traditional recipes. The plum wine ‘Umeshu’ and ‘Kashiwa-bento’ (chicken lunch-box) are not only sold in the shop but in restaurants and other markets, too. The owner farm families were able to provide a good knowledge base for old recipes to be used in the kitchen. Around 30 types of traditional style foods, ‘Dentoshoku’, are produced and sold. However, the agricultural products they produced themselves are 4–5% of the total sales. Most sales are from products brought in from a long distance away. The nearest producer of the products sold at the store is the main owner of ‘Budoubatake’. The next nearest is located about 1 km away. The farthest supplier farmer is located around 1000 km away in Hanamaki, Iwate Prefecture – a producer of Chinese yams. Current types of suppliers to this DFM are as follows: family farms, farmers’ groups (Kumamoto-Amakusa, Kumamoto-Hitoyoshi, Fukuoka-Kuroki, Fukuoka-Shima), farmer’s companies (Fukuoka-Ooki, Fukuoka-Kurume) and farmers’ markets (Iwate-Hanamaki, Nagasaki-Goto, Saga-Nanayama, Fukuoka-Asakura). One of the most important advantages for farmers in joining ‘Budoubatake’ is the opportunity to construct close contacts with consumers. There are special festival events set up for meeting and exchanging views with consumers by this DFM. The following summarises the development of the farm market: ● ●

●

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At the beginning there were 70 partners, but this number has grown to 150. As for the regions covered, at the beginning these were Fukuoka, Saga, Kumamoto Yamaguchi, Miyazaki. Recently, Nagasaki, Oita, Ehime Nagano, Hyogo and Iwate were added. Regarding the increase of clients, at the beginning there were 300 clients per day on average, a number that has risen to 700 clients per day.

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Partner farmers are satisfied with the contract and business relationship with ‘Budoubatake’ because they can receive higher prices than in the auction markets. A problem is that farmers cannot sell all their products and the rest can potentially become waste. The leftovers can be cooked as sellable food products in the Budoubatake kitchen if time is available. There have not been any disagreements in the past among the business partners when discussions have been held on price and quality. The most important factor for keeping partners competitive in the local market is the knowledge of products and skills in farming technology. Fruit in particular needs high-level production skills. Based on a high level of product knowledge and skill, farmers can produce high-quality vegetables and fruits. ‘Budoubatake’ never sells rotten or poor-tasting fruit. Sweetness is the most important characteristic of fruit sold at the shop. In order to ensure the quality of the products, special attention is given to sorting, packaging, special cultivation methods, including organic production approaches, and transportation of the farm products. The agricultural products come from diversified regions in Kyushu and the rest of Japan which specialise in these products. Fukuoka and Saga provide several types of vegetables and fruit; Nagasaki offers onions, carrots, beans, burdocks, cucumbers and tomatoes; Oita delivers tomatoes, corn and mushrooms; Kumamoto is a home for burdock, pumpkin, orange, alliums, and okra (‘Lady’s finger,’ a good base for vegetable garnish); Miyazaki specialises in mango, blueberry and tomato; Yamaguchi is for eggs; Ehime gives oranges; Nagano provides apples; Hyogo brings in black beans (this is the most famous prefecture for this product in Japan); and Iwate sends Chinese yam. The best available products are gathered from all over Japan, but most items are from the surrounding prefectures, which are only a few hours away. The business relationship between ‘Budoubatake’ and farmers is that most products are sold with a commission charged by the shop. If the producers are located in a distant place, the products are purchased by the shop. The profit is shared by the producer and ‘Budoubatake’, with the shares of 20% and 80%, respectively. The farmers can also use a stand in the shopping area located outside the shop. Here they can sell their products and only pay rent for space. They can keep what they receive for the products. ‘Budoubatake’ and suppliers, mainly farmers, agree on the quantity, quality and time of shipments, the sale prices of the products as well as the amount of commission. Farmers are responsible for quality control, transportation, sorting, packaging, inventory control, invoicing, etc. The most important promise to its clients and consumers is quality control. ‘Budoubatake’ is committed not to sell poor-quality products. Partner farmers are wholly aware of ‘Shokuiku Law’ (food education law) and the rather complex food and agricultural policies in Japan. They also consider the specific characters of food culture of their cities, towns and villages. Consumers have been more and more interested in learning about food culture and agricultural practices. Several traditional foods have been neglected in the past, but have been revitalised and promoted by the shop in order to diversify the food culture of the local area. ‘Budoubatake’ recognised that it can create a good opportunity to promote ‘Chisan Chisho’. Most farmers are proud of the food culture of their cities, but usually they do not have enough capacity or the opportunity to be involved in transferring knowledge on agriculture and traditional food culture. ‘Budoubatake’ has a key role in educating farmers and customers, as well generating new information and providing opportunities to farmers and consumers for mutually beneficial communication. This example, in which the local food supply system is managed by a private sector business, provides an example of parties all benefiting from production, consumption, sales and shopping activity. The risk around sales is borne by the producers as well as the shop. This seems to create a suitable solution for establishing a sustainable system to make every party, including consumers, satisfied.

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14.4.2 ‘Rokko Blessing’ farmers’ market (JA-managed company) ● ●

Location: Kobe City, Hyogo Prefecture Official website: http: //www.jarokko.or.jp/Sol/Megumi/index.htm

We rely on the findings of a case study to summarise some characteristics of this farmers’ market (Kako, 2008). ‘Rokko Blessing’ DFM was established and opened by the marketing department of the JA Hyogo agricultural cooperative in November 2004. There are altogether 406 markets selling agricultural products in Hyogo prefecture. ‘Rokko Blessing’ is the largest. In 2006, it had a total sales value of ¥1.4 billion and the number of supplier farmers transporting agricultural products to this DFM was 706. Ninety-two items are sold, mainly vegetables. Next to vegetables, the second-largest volume agricultural product in this market is cut flowers. The shop has also started to sell meat, fruit and pot plants. Financial support from the national and local government was provided to start the operation (Naitoh et al., 2005). During the last 5 years, the quantity of shipments, gross sales and the number of visitors has increased. The sales value increased by 23% from 2005 to 2006. The average sales value per supplier was ¥15,405 in 2005, a number which increased 14% to ¥17,500 in 2006. The number of visitors has risen by 25% from 588 000 in 2005 to 736 000 in 2006. The average daily purchase decreased slightly from ¥1,938 to ¥1,902 per customer. The main characteristic of this farmers’ market is direct contact and interchange between producers and consumers. The questionnaire and interview survey, conducted with the cooperation of JA Hyogo Rokko, revealed the activities executed by management and the operation of ‘Rokko Blessing’. There are seven main functions that can be considered principal activities of DFMs: (i) There is a production planning function based on the continuous analyses of customer demand and preparing plans for annual agricultural production (what kind of products, what assortments and quantity/quality) by providing information for producers in the local region about their opportunities to sell agricultural products in the farmers’ market. (ii) The market helps direct sales promotions of fresh products and local food. There is an ICT-based POS established in the DFM. It creates close communications between farmer suppliers and customers. (iii) JA Hyogo Rokko organises training and advisory opportunities for farmers. This is a food and agricultural education function (‘Shoku-no-kyoiku’), education about food, which is beyond the efforts of ‘Shokuiku’. Active information exchange improves customer knowledge. JA organises education opportunities and advisory services for farmers. (iv) The DFM provides a reliable traceability system for local food. The three main goals of DFM marketing are safety, reliability and provision of information. Relevant production information on cultivation methods, quantities of fertiliser applied and agricultural chemical usage is provided. (v) A wide marketing communication network5 has been formed to popularise local products and local agriculture among the customers and inhabitants of the prefecture.

5

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Individual suppliers can be identified by consumers in the Kobe DFM system (product identification).

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(vi) Joint community marketing activities inside the shop are carried out. This makes the business decisions of the producers more effective. It also decreases the cost of sales of the products for the producers. (vii) Customer convenience has to get priority. The consumers order a commodity so they can find the product more easily inside the large store. There is no means of identifying every supplier but POS provides the communication between consumers and farmers. Development of internal rules and policies to meet the needs of both consumers and producers seems to be key to the successful development of local food production and markets.

14.4.3 ‘Michinoeki’ farmers’ market in Ukiha City (mixed-ownership company) ● ●

Location: Ukiha City, Fukuoka Prefecture Official website: http: //www.michinoeki-ukiha.com/

Ukiha (Ukiha-shi) is a city located in Fukuoka Prefecture, Japan. The city was founded on March 20, 2005 as a result of the merger between the towns of Ukiha (Ukiha-machi) and Yoshii in Ukiha District. As of 2003, the former town had an estimated population of 16 359 and a density of 183.27 people per square kilometre. The total area was 89.26 km2. As of April 1, 2005, the new city had an estimated population of 33 177 and a density of 139 people per square kilometre. The total area was 117.55 km2. There are two local farmers’ markets in the area of Ukiha district, which operate under different ownership and organisational forms. The first one is ‘Michinoeki’ farmers market (UMFM) which is located in Ukiha City. The second one is the JA Agricultural Cooperativeowned farmers’ market in Haki (8 km from Ukiha). UMFM was established by the local government as a mixed-ownership stock company in 2000. The main owners are the local city government, owning 70% of the stock, the Niji (rainbow) Agricultural Cooperative (NAC) and the forest cooperatives, each holding 10% of the total stock. The fourth partner is a private commercial company, the association of local merchants, owning the remaining 10%. The building for the shop is owned by the local government, and this creates the basis of outsourcing a government function to the private business sector. The private company leases the building from the city government and operates UMFM. This provides a public service for the local producers, the farming sector and local consumers (healthy local food). The financial support from the national and local government under the Shokuiku law and FARA law are utilised for the establishment and maintenance of this local market. The local farmers can become members of this joint stock cooperative company if they produce agricultural products and/or foods and pay ¥100 (about $1) as a symbolic membership fee per year. There is no specific procedure to review the eligibility of an applicant for membership, but the products and processing environments should satisfy the standards of the local authority for sanitary and food hygiene conditions. Two members of UMFM living in the local area were interviewed during our short visits to Ukiha (Vörös, 2009). Both of them supplied fresh processed foods with a 1-day expiry period to UMFM every morning. They produced different types of healthy ‘bento’ (lunch boxes) containing mainly local produced agricultural products and most of them cooked and

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prepared according to traditional recipes. These food products can be considered special local healthy ‘bento’ of ‘Dentoshoku’ (traditional foods). The first of these active suppliers interviewed was an 80-year-old farmer’s wife old farmer’s wife with expertise in traditional cooking. The main products of their family farm are rice (0.8 ha paddy field), bamboo shoots (0.2 ha) and ‘Shiitake’ mushroom for drying (500 kg sold/year). Using her own produced raw material, she was able to cook and supply tasty, fresh food products to UMFM daily. One of her most saleable fresh food product is ‘Onizuka’ (young bamboo shoots cooked in cooking sake, soy sauce, etc.), which is a popular ‘Dentoshoku’ among consumers visiting UMFM. Others are different rice-based ‘bento’ food products, such as ‘Inari’ and ‘Onigiri’, all of them sold fresh. This senior farmer couple had invested to extend and modernise the kitchen in their traditional farmhouse so as to be able to produce these fresh sellable foods. This farmer’s wife, as a local ‘Dentoshoku’ specialist, represents a living example of traditional culinary knowledge and sustaining of the local food culture. This case also is an example of on-farm integration in food production and distribution. It can be considered a successful application of the ‘Health Japan 21’ programme6, which supports the elderly to be active in rural society. We can also observe that widening the scene of ‘Chisan Chisho’ in Japan has significant impacts on consumers, who are keen on purchasing fresh agricultural and food products (Sakurai, 2006). The other supplier interviewed was also a woman, the wife of a local pottery producer. Since her family is not in farming, the wife learned various recipes and accumulated knowledge on how to prepare healthy fresh ‘bento’ (lunch boxes). Later on, she decided to engage in income-generating activities to supplement her household income. She purchases local farm products from local producers (except fish) or buys them in local supermarkets. Then, this housewife prepares healthy ‘bento’, with a 1-day expiry period, with the purchased materials. Two-thirds of her bento products are sold in UMFM, and one third in the DFM managed by the JA Agricultural Cooperative, which is located near Ukiha in Haki Town. She employs part-time workers for processing and packaging. She is capable of supplying her goods every day, but the daily demand changes. Usually she can sell more at the weekend. She is very satisfied with UMFM because the marketplace is well equipped with advanced information technology tools. During the day she can monitor the actual stocks and daily sales using her mobile telephone. There is an advanced information processing and daily sales POS monitoring system in this farmers’ market available for customers and suppliers. This second example also demonstrates very well that DFMs provide good opportunities for people in rural areas to be economically active. The other remarkable lesson learned from this example is that there might be ‘two-channel suppliers’ who are continually monitoring the actual level of demand and sales prices offered by different local DFMs to try to optimise their income and profit. These decisions of suppliers can be supported by the advanced ICT and POS information systems implemented by the DFM’s management. The examples show that ‘Michinoeki’ or ‘third sector’ farmers’ markets in Japan perform important social and community service functions for small-scale local farmers and food producers as well as for consumers among local residents and tourists from distant areas.

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Udagawa, K., Miyoshi, M. and Yoshiike, N. (2008) Mid-term evaluation of “Health Japan 21”: focus area for nutrition and diet. Asia Pacific Journal of Clinical Nutrition, 17(S2), 445–452.

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54% 39% 1% 0% 2%

Source: Survey results by the authors.

14.5 CONSUMER SUPPORT FOR LOCAL MARKETS A research study has been prepared on the role of UMFM in implementing the ‘Chisan Chisho’ policy tool and ‘Shokuiku’(Higuchi, 2007). It provides further information and details on some special features and characteristics of UMFM, as well as the contribution and operation of the local community in implementing the policy to improve the local food system. Some relevant results were found in our small sample survey (Vörös, 2009), comprising 89 rural and urban-agricultural households in Fukuoka Prefecture. The consumers of local agricultural products and foods indicated that they prefer local products and that they support the promotion of ‘Chisan Chisho’, which means locally produced and locally consumed (FARA Policy, http://www.maff.go.jp). In our questionnaire we asked the following questions: ● ●

What is the role of product origin in your food shopping decisions? Do you usually give preference to traditional, domestic, locally or regionally produced food?

The level of confidence of households to purchase domestically and locally produced foods is fairly high. Table 14.6 indicates that more than half (54%) of the households give preference unconditionally to buying local food without considering prices, and 39% of households would buy local foods if the prices were around the same or less expensive. Consequently, our small sample survey shows that the majority of households – three-quarters of them – are agricultural producers who are supporting the food, agricultural, and rural area policy targets to promote local agricultural products. Comments provided by the surveyed households supplement well the statistical results. There are important messages for policy decision-makers involved in further improving agricultural and rural development policies in Japan. We can summarise these in the following two comments, which were obtained from farmers who signified their hopes for the improvement of agricultural policy and their trust in the future development of Japanese agriculture: ‘We hope that food products in Japan can grow in the future.’ ‘Domestic or local food is more reliable. Food safety is very relevant. I prefer the development of agricultural production in Japan.’

The majority of households in the sample said that they follow ‘Chisan Chisho’ because of freshness, traceability and the safety of the foods they consume.

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‘We prefer ‘Chisan Chisho’ and eating traceable foods; we are convinced of the food production process.’ ‘We can be well informed about the way food production is carried out. Therefore we can be convinced about the safety of food.’ ‘I would like to be aware of producers and how their farms are run.’ ‘We prefer local food products as much as possible; local producers are reliable and we can buy with confidence.’ ‘We can trace foods. We can be also sure about the distribution system.’

More price-conscious households gave the following comments: ‘If we continue to consume expensive food, we will have difficulties in preserving our living standards.’ ‘I would prefer always to buy domestic, but due to the economic situation I cannot afford it.’ ‘I prefer domestic foods as long as they are not that expensive.’

There still exist challenges for the local food market systems to meet the needs of this group of households.

14.6 CONCLUSIONS Recent studies, including this study in Japan of local farmers’ markets (DFMs) and o the promotion of local production and local consumption (‘Chisan Chisho’) have identified that DFMs give not only positive economic impacts to producers and consumers, but also play several multifunctional social roles (Kai, 2006). Local production and local consumption of agricultural products and foods can be economically and socially feasible and become popular in other countries with a promotional policy to meet the goals of food security, food safety and rural development. The benefits are as follows: ●

●

●

●

● ●

●

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strengthening the local economy, creating new jobs, decreasing unemployment and increasing economic activities of people; creating direct interactions between food producers and consumers, improving city– village relationships; increasing food self-sufficiency at different levels (family-farm households, rural regions and national level); improving ‘food mileage’ indicators, decreasing environmental pollution in the country and globally; improving the freshness of local products to appeal to customers to buy local products; making traceability of food much simpler, with a positive impact on healthy diet and improving quality of life; improving the employment of older generations of farmers, which has a positive social impact on widening economic activity in rural areas; decreasing costs for health care and medical services in the regional and national level (elderly people having a job spend less time and energy on medical services); improving the psychological satisfaction and health of older generations of agricultural producers; widening rural or ‘green’ tourism services, entertaining customers and giving opportunities for food education.

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The cases in Japan show that advanced information systems can be of help for the development of local food systems. Financial support from national and local government and technical assistance form the cooperative organisation of JA and local government are the catalysts for local markets. Local consumers in Japan seem to find value in products’ freshness, traceability and safety in the newly established local markets, which typical supermarkets cannot offer. However, challenges still exist. Local producers are still small in term of sales and employment. There exists a group of consumers who are always price conscious. Continuous efforts for product differentiation so as to enjoy a price premium are required by the producers. Consumers’ expectation on the quality of products is high. Without government financial support, probably not too many local markets can survive in the long run with the existence of seasonality in crop production in Japan. During the winter months, DFMs require some additional activities beside the sales of farm products in many local marketplaces. The DFMs will not replace the existing international and domestic food supply chains soon, these having been efficient in connecting agricultural producers and food processors and reaching out to individual consumers throughout the world. However, the DFMs could supplement these with local activities to meet specific needs of consumers. We expect DFMs to be more visible in many parts of the world in the near future.

REFERENCES Food and Agriculture Policy Research Center (1997) Structural Changes in Japan’s Food System. Tokyo, p. 104. Forsman, S. and Paananen, J. (2004) Value creation in local food supply chains: market opportunities and challenges. Available at: https://ifama.org/events/conferences/2004/cmsdocs/Forsman1038.pdf (accessed December 2010). Higuchi, T. (1991) Japanese dietary habits and food consumption. In: Agriculture and Agricultural Policy in Japan. Committee for the Japanese Agriculture Session XXI IAAE Conference, pp. 87–104. Higuchi, Y. (2007) Research on the Function of the Farmer’s Markets of Agricultural Products on ‘Local production – Local consumption’, ‘Chisan Chisho’ and food education. PhD Thesis. Kyushu University, Faculty of Agriculture. Iizaka, T. and Suda, F. (2008) Making devices for sustainable agriculture systems: a case study of the Japanese farmers market. XII World Congress of Rural Sociology, 6–11 July, Goyong, Korea, 2008. Manuscript of paper presented. Ito, S., Kubo,T. and Kuwabara, T. (2007) Weakening demand for rice in Asia and food education law of Japan. Rural Review. Regional Office of Far East. Afro Asian Rural Development Organization, Second Half 2007, Vol. 34, No. 2. JA Group (2008) Development of ‘Chokubaijo’ Direct Farmer’s Market and ‘Chisan Chisho’ activities in Fukuoka Prefecture. JA Group Fukuoka Prefecture 2008, Fukuoka. Kai, S. (2006) Analysis of development factors for farmer’s markets in relation to local revitalization. Agricultural Marketing Journal of Japan, 15(2), 12–20. Kako, T. (2006) Progress of globalisation and changes in local agriculture. Journal of Rural Problems, 41(4), 334–343. Available at: http://rms1.agsearch.agropedia.affrc.go.jp/contents/JASI/society/norinmondai 41–60.html. Kako, T. (2008) Case study research on ‘Rokko Blessing’ direct farmer market ‘Chokubaijo’ in Kobe. MAFF (2005a) Annual Report on Food Agriculture and Rural Areas in Japan FY 2005. Available at: http://www.maff.go.jp/e/annual_report/pdf/fy2005_rep.pdf. MAFF (2005b) Key Points in the Basic Plan for Food, Agriculture and Rural Areas. MAFF. Available at: http://www.maff.go.jp. MAFF (2007) Annual Report on Food, Agriculture and Rural Areas in Japan FY 2006. Policies on Food, Agriculture and Rural Areas in Japan FY2007. Summary. (Provisional Translation.) MAFF, pp. 24–25. Available at: http://www.maff.go.jp/e/index.html.

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MAFF (2008a) Annual Report on Food, Agriculture and Rural Areas in Japan FY 2007. Summary. (Provisional Translation). Endorsed by the Cabinet and published on 16 May 2008. Available at: http:// www.maff.go.jp/e/index.html. MAFF (2008b) What is ‘Shokuiku’ (Food Education)? Ministry of Agriculture, Forestry and Fisheries. Available at: http://www.maff.go.jp/e/index.html. MAFF and Cabinet Office (2006) Basic Program for ‘Shokuiku’ Promotion. Abstract (provisional). March. Naisbitt, J. (1994) Global Paradox. William Morrow, New York. Naitoh, S., Fujita, T and Kajiura, N. (2005) The development of local agri-food system: promotion policy and the role of local government. Agricultural Marketing Journal of Japan, 14(1), 28–37. Nakata, T. (2003) A study on the volume and transportation distance as to food imports, ‘food mileage’ and its influence on the environment. Journal of Agricultural Policy Research, 5, 45–59. Nestle, M. (2002) Food Politics. How the Food Industry Influences Nutrition and Health. University of California Press, Berkeley, p. vii. Sakurai, S. (2006) Development of the ‘locally-produced-locally-consumed’ movement based on the farmer’s market and its impact on rural development. Agricultural Marketing Journal of Japan, 15(2), 21–29. Turchany, G. (2008) We will have to face the evanescence of civilization in 30 years unless we may change. Ma and Holnap (Today and Tomorrow), Vol. 8, No. 5. Une, Y. (2006) ‘Blessing’ of Fukuoka’s Agriculture. Tajiwara Nijoh City, Fukuoka Prefecture. Laboratory of Agriculture and Nature. Une, Y. (2009) How to preserve ecosystem-balance in rice lands. Symposium, 7 March 2009, Fukuoka, Japan. United Nations (1992) Report of the UN Conference on Environment and Development. Rio de Janeiro, 3–14 June 1992. Annex I Rio Declaration on Environment and Development. Available at: http://www. un.org/documents/ga/conf151/aconf15126-1annex1.htm. United Nations Decade of Education for Sustainable Development (DESD) spanning from 2005 to 2014. Available at: www.unesco.org/education/desd/. Vörös, M. (2009) Studies on the development of rural communities in Japan and its policy implications for sustainable rural development in Central and Eastern Europe. Research study conducted with a Japanese scholarship granted by the Japan Foundation for 2008–2009.

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15

The Use of Telematics in the Daily Distribution of Perishable Goods: The Case of NIKAS SA

Vasileios Zeimpekis

15.1

INTRODUCTION

Typically in a food product chain, the raw products are produced in one part of the world and are preprocessed, transported, refined, processed, and repacked along a long chain of food and transport companies, and finally distributed to the end customer in another country or continent. However, certain goods, such as meat products, are difficult to handle along long supply chains as they need special storage and handling procedures after entering the supply chain, and spoil easily with incorrect handling and processing (Myoung et al., 2001). These situations can lead to various problems, especially during distribution of goods in urban environments, which may severely affect product quality and freshness (Salin 1998; Hill and Scudder, 2001). On the other hand, distribution is a major activity of supply-chain-execution operations and contributes significantly to total logistics costs (Ballou, 1999). Consequently, over the last four decades, both professionals and academics have devoted considerable efforts to improving and streamlining key distribution processes. Much of this attention has been focused on city logistics environments and, in particular, on dynamic incident handling through real-time fleet-management systems, especially in cases where delivery delays cannot be accepted. This is due to the fact that the use of an initial distribution plan in an urban environment, although necessary, is by no means sufficient to address unexpected events, which may have adverse effects on the performance of the delivery execution. Table 15.1 presents a typical classification of incidents and their effects on freight delivery. Various systems have been developed for fleet monitoring and incident detection in urban environments (see Powell, 1990; Savelsbergh and Sol, 1997; Slater, 2002; Ichoua, 2003; Kim et al. 2003). However, most of these systems typically focus on handling client orders that arrive during the execution of the delivery plan and need to be assigned to moving vehicles (Gendreau and Potvin, 1998; Yang et al., 1999; Fleischmann et al., 2004a). Dynamic ordering, however, is only a subset of the unexpected events that may affect urban distribution performance. This paper addresses a more generic problem of dynamic fleet management, in which the distribution plan needs to be adjusted in real time to accommodate changes in uncontrollable parameters of the delivery environment (such as traffic congestion, adverse weather conditions, lack of available unloading areas at the customer site). We describe a real-time Intelligent Agrifood Chains and Networks, First Edition. Edited by Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis. © 2011 by Blackwell Publishing Ltd. Published 2011 by Blackwell Publishing Ltd.

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Table 15.1

Dynamic incidents in urban freight distributions.

Source of incident

Incident

Effect in delivery

Road infrastructure and environment

Traffic congestion, adverse weather conditions, road construction, street markets, protests

Increased vehicle travel time

Clients

No available unloading area, problems with the delivered products (e.g. wrong order) New client request (delivery or pickup), amount of request

Longer client service times Vehicle rerouting in real-time/no service

Delivery vehicle

Car accident, mechanical failure

Customer service interception

fleet-management system that continuously monitors the execution of the initial plan, detects significant deviations that require rerouting, solves the related optimization routing problem and transmits the revised plan to the vehicle, all in real time. The system is tested in a traditional distribution setting, in which each vehicle distributes a pre-specified set of orders along a preplanned route. The latter may be the result of a typical routing process, manual or algorithmic. The execution of this plan, however, is usually impeded by various unexpected events, which may result in significant delays. In this case, the vehicle is no longer capable of completing its entire route, and thus rerouting becomes necessary. The mathematical model related to this problem resembles the so-called Orienteering Problem (OP) (see Tsiligirides, 1984), a variation of the Traveling Salesman Problem (TSP). The remainder of the paper is organized as follows. Section 15.2 presents the research to date in the area of real-time fleet-management systems and dynamic travel time prediction, which is a prerequisite for managing unexpected events. Section 15.3 describes the requirements of the proposed system and its architecture. Section 15.4 describes the results provided by the simulation testing of the system, while section 15.5 discusses the results obtained from real cases in a Greek company (NIKAS SA) that produces and delivers meatbased products in city environments. Concluding remarks, future research guidelines, as well as limitations of the proposed system, are discussed in section 15.6.

15.2 15.2.1

BACKGROUND Real-time fleet-management systems

The typical components of a real-time fleet-management system are shown in Figure 15.1. Apart from the fleet-monitoring process, an event-management mechanism handles unexpected events such as traffic congestion, vehicle breakdowns and new customer requests in a dynamic manner. Incident detection occurs usually through dynamic travel time prediction and incident handling is managed via rerouting algorithms. As mentioned above, research in the area of real-time fleet management initially focused on cases where a new customer request appears during delivery execution and must be fulfilled in a specific time period. Goetschalckx (1998), Powell (1990), Savelsbergh and Sol (1997), Slater (2002), as well as Gans and van Ryzing (1999), described systems that can cope with new customer requests, assuming, however, that travel times either remained

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Real-time fleet-management system Initial vehicle routing and scheduling

Fleet monitoring

Event management

Updated vehicle routing

Dynamic incidents Figure 15.1 Main components of a real-time fleet-management system.

constant throughout the day or were manipulated through simple procedures to adjust them, depending on the period of the day. However, these assumptions are weak approximations of real-world conditions. Therefore, the optimal solution to a formulation of an urban freight delivery problem that assumes constant travel times may be suboptimal or even infeasible (Ichoua, 2003). Kim et al. (2003) proposed the use of real-time traffic information in realtime fleet-management systems in order to manage delays caused by traffic problems. They examined its value to optimal vehicle routing in a non-stationary stochastic network by developing a systemic approach for determining driver attendance time, optimal departure times, and optimal routing policies under stochastically changing traffic flow. Ichoua et al. (2003) described a real-time fleet-management model based on time-dependent travel speeds. An experimental evaluation of the proposed model shows that the time-dependent model provides substantial improvements over a model based on fixed travel times. Fleischmann et al. (2004b) described a dynamic routing system that dispatches a fleet of vehicles according to customer orders arriving randomly during the planning period. The system receives online information about travel times from a traffic management center. Taniguchi and Shimamoto (2004) also presented an intelligent transportation system based on dynamic vehicle routing and scheduling with variable travel times. Results indicated that the total cost decreased when implementing the dynamic vehicle routing and scheduling model with real-time information based on variable travel times rather than a forecast model. Finally, Hanghani and Jung (2004) described a systemic approach to address the dynamic vehicle routing problem with time-dependent travel times. In this case, dynamic travel times are obtained by on-board terminals. Although the aforementioned papers tackle a series of unexpected events, they do not propose a systemic approach for handling dynamic incidents, such as traffic congestion, unavailability of unloading space at the customer, as well as vehicle breakdowns. In this paper, we aim at increasing customer service in urban freight distributions of perishable foods by introducing a novel real-time fleet-management system that incorporates an event management mechanism that can handle unexpected events that occur during delivery execution in a systemic manner. The system incorporates two kinds of algorithms we have developed: (i)

(ii)

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those that combine real-time vehicle data (collected through appropriate on-board devices) and data regarding historical travel times to estimate the expected arrival time of a delivery vehicle to all its remaining assigned customers; those that suggest efficient rerouting strategies when non-recoverable deviations from the original distribution plan are detected.

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Surveillance device (data collection)

Travel time prediction techniques (data processing)

Travel time estimation (results)

Figure 15.2 Basic components for travel time estimation.

The system monitors the progress of delivery execution in real time by using the first set of algorithms to continuously estimate the expected delivery times of all vehicles in the distribution fleet under the prevailing road and environmental conditions. When non-recoverable anomalies are detected (in other words, when estimated expected vehicle arrival times are beyond customer-set delivery windows), the second set of algorithms are executed to suggest rerouting strategies that maximize the total delivery gains that can be achieved in terms of predefined customer weights and priorities. It is apparent that an efficient estimate of the expected arrival time to remaining customers through travel time prediction is critical for such a real-time fleet-management system. Therefore, the following section presents a review of the research to date in prediction methods that are used for incident-detection in such systems.

15.2.2

Travel time prediction for fleet-management systems

Travel time can be defined as the total time required for a vehicle to travel from one point to another over a specified route under prevailing conditions. Its calculation depends on vehicle speed, traffic flow and occupancy, which are highly sensitive to weather conditions and traffic incidents. Travel time data can be obtained through various surveillance devices, such as loop detectors, microwave detectors, and radars, although it is not realistic to have the road network completely covered by detectors (Turner, 1996). With the development of mobile and positioning technologies, such data can be more reliably collected and transmitted by devices (i.e. telematic equipment) that can be set up on vehicles. However, travel time estimation is not straightforward because it depends not only on the surveillance devices, but also on prediction techniques that are used for data processing. Figure 15.2 presents the basic components of an on-board travel time estimation system. 15.2.2.1

Surveillance devices

Various surveillance devices have emerged with the incorporation of portable computers and other electronic technology. According to Turner (1996), these emerging techniques include electronic distance-measuring instruments (DMIs), licence plate matching (via portable computer or video), cellular phone tracking, automatic vehicle identification (AVI), automatic vehicle location (AVL) and loop detectors. Electronic DMIs are inexpensive but are limited to congestion monitoring applications. License plate matching is more expensive, and is most applicable for congestion measurement and monitoring. However, neither can provide real-time travel information or incident detection. On the

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other hand, cellular phone tracking, AVI, AVL, and loop detectors provide real-time information and incident detection. However, cellular phone tracking provides moderate accuracy of travel times and a large investment for creating a control center for taking phone calls is needed. In addition, cellular phones must be in use in order to track, thereby limiting sample sizes and coverage (Turner, 1996). AVI technology has a high initial equipment cost and drivers must acquire and display the tag. In addition, travel time estimation is limited to fixed routes and checkpoints (i.e. points where a roadside reading unit is available). As far as loop detectors are concerned, Berka and Lall (1998) claim that loop detection reliability is low and that maintenance and repair of such a pavementbased system creates safety risks for repair crews. They also argue that loop detector systems may suffer from poor reliability, primarily from improper connections made in the pull boxes. In addition, sources of loop malfunction, such as stuck sensors, can produce erroneous data and may lead to inaccurate detection. Turner (1996) notes that inaccurate results can be generated by loops because they do not easily identify the congestion that occurs between loop stations. Finally, AVL systems, although having moderate capital and operating costs, can provide excellent accuracy for travel time estimates by providing real-time information and incident detection. This is due to the ability of AVL systems to continuously monitor the progress of vehicles, therefore providing more accurate estimates. Drawing on the above, it was decided to use an AVL system as a surveillance device for data collection. The following section presents a review of travel time prediction techniques that can be used in the event management module of the proposed system. 15.2.2.2 Travel time prediction techniques and travel time estimation One of the major issues in travel time and traffic forecasting is the selection of the appropriate methodological approach. Current practice involves two separate modeling approaches: parametric and non-parametric techniques (Vlahogianni et al., 2004). In the vast majority of statistical parametric techniques, several forms of algorithms have been applied with greater weight to historical average algorithms (Smith and Demetsky, 1996) and smoothing techniques (Smith and Demetsky, 1997; Williams et al., 1998). In the early 1990s, autoregressive linear processes, such as the auto-regressive integrated moving average (ARIMA) family of models, which were first introduced in traffic forecasting by Ahmed and Cook (1979) and Levin and Tsao (1980), provided an alternative approach based on the stochastic nature of traffic. Davis et al. (1991) applied a single ARIMA model to forecast the bottleneck formation on a freeway. Later, Hamed et al. (1995) applied an ARIMA model to forecast urban traffic volumes. Recent advances in real-time collecting, storing and managing of large databases from several points of an extended transportation network have afforded the opportunity to explore the robustness of non-parametric techniques in traffic and travel time forecasting. Non-parametric techniques do not assume any specific functional form for the dependent and independent variables (Vlahogianni et al., 2004). Two distinct forms of non-parametric techniques, namely non-parametric regression and neural networks, have gained a great portion of the research into short-term traffic forecasting over the last decade. A number of researchers (Clark et al., 1993; Smith and Demetsky, 1997) argue that the use of nonparametric regression techniques in urban networks is more efficient due to their ability to cope with the fluctuating nature of the observed traffic parameters such as flow, occupancy, speed and so on.

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Drawing on the above, it was decided to incorporate the non-parametric regression method for travel time processing. The following section presents in detail the requirements elicitation process as well as the design of the architecture of the proposed system.

15.3 15.3.1

A REAL-TIME FLEET-MANAGEMENT SYSTEM FOR DYNAMIC INCIDENT HANDLING Requirements elicitation process

To identify user requirements for the proposed system, we performed the analysis shown in Figure 15.3. The users targeted by the analysis were companies and manufacturers that distribute their products using private fleets in an urban environment. The starting point of the user requirements elicitation procedure was the identification of the state-of-the-art and the state-of-practice in the area of real-time fleet-management systems and urban freight-distribution processes. To extract all user requirements in a constructive and methodologically sound manner, a series of interviews were held with 15 logistics managers who were responsible for the dispatching process. All companies used fleet-management systems for monitoring their fleets and six of them were also using a vehicle-routing system to construct the daily delivery plan automatically. The interviews were based on predefined questions to collect the same information from each interviewee and were focused on the following issues: ● ● ●

●

current status of executing delivery schedules; inefficiencies in freight delivery; willingness of users to adopt new methods, techniques and technologies for incident handling operations; user expectations and recommendations.

After having performed the analysis from the interviews, the results were presented to the interviewees in order to be assured that the results corresponded to their needs. The final stage of the user-needs analysis methodology was the synthesis of the results and the establishment of the proposed user requirements. Table 15.2 summarizes the major system requirements resulting from the above process, and indicates which of these requirements are addressed by current fleet-management systems. As can be seen, critical requirements not addressed by such systems include: ●

●

the ability to intelligently reroute a delivery vehicle that has been delayed and, as a result, is no longer capable at serving all scheduled clients; the ability to deal with vehicle breakdowns by rerouting nearby vehicles to deliver the load of the immobilized vehicle.

If a backup vehicle is not available at the depot, then a vehicle that has both adequate load capacity and time availability should be identified to unload the items from the immobilized vehicle and continue the delivery tasks of the latter. The aforementioned requirements led to the design of the system architecture presented in the following section.

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State-of-art State-of-practice

Identification of users

Design of interview session

Interviews

Analysis of user response

Synthesis of user needs

System’s specification Figure 15.3 Methodological framework for user requirements elicitation.

Table 15.2

15.3.2

Urban freight distribution requirements.

Requirements for real-time fleet-management systems

Addressed by current fleet-management systems

Real-time vehicle monitoring Vehicle performance reporting Proof of delivery Dealing with vehicle rerouting Adhering to delivery time windows Dealing with vehicle breakdowns

Yes Yes Yes No No No

System architecture

The real-time fleet-management system (Figure 15.4) comprises three components, namely the control center, the telecommunications subsystem, and the vehicle unit. The control center contains several modules. ●

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The geographical information module (GIM), which manipulates and maps spatial data that are necessary to support the decision support module. The cartographic information required is derived from vector maps.

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Vehicle user interface (VUI) Vehicle on-board system (VOS) Microprocessor

GPRS modem

GPS receiver

On-board terminal

GPS

GPRS Decision support module (DSM) Monitor & detection

Delivery trip projection

Data management module (DMM) Customer data

Fleet data

Decision making & rerouting

Geographical information module (GIM)

Delivery plan data

Geo-data

Control center user interface (CCUI) Figure 15.4 Architecture of the real-time fleet-management system.

●

●

●

The decision support module (DSM), which computes and recommends all required realtime adjustments to the ongoing delivery system to meet preset goals taking into account the system’s dynamic state. The data management module (DMM), which contains all static and dynamic information (spatial and non-spatial) related to clients, vehicles, and distribution schedules. The control center user interface (CCUI), which allows the route planner to interact with various functions of the system. Via this interface, information regarding the status of each vehicle is communicated to the planner in order to obtain a holistic view of the fleet status and be able to make appropriate decisions.

The telecommunications subsystem has two components: (i) (ii)

the mobile access terrestrial network, which is responsible for the wireless interconnection of the back-end system with the front-end on-board devices; the positioning system, which is responsible for vehicle tracking. We have used the GPRS network for terrestrial data transmission, which supports efficient real-time transfer of data. GPS has been used for vehicle tracking.

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The vehicle unit includes the following modules: ●

●

The vehicle on-board system (VOS) comprises the telematic equipment, which supports real-time communication and data processing, as well as a portable data terminal for use by the driver. The system collects all data necessary to dynamically monitor a range of operational parameters relating to vehicle performance, location, and load information. The vehicle user interface where the decisions of the route planner are communicated to the vehicle and presented to the driver. This in-vehicle computer system allows the driver to have bi-directional communication with the control center by which he/she receives rerouting decisions, provides proof-of-delivery information, and alerts the control center in case of unforeseen events.

15.4

SIMULATION TESTING

The system has been initially in tested a simulation environment. The main purpose of this process was to examine a number of representative testing scenarios to evaluate the system performance in incident handling. In order to assess system performance, each test case was simulated twice (with and without the directions provided by the real-time fleet-management system). To perform these tests, a seven-step simulation process was followed. This process is depicted schematically in Figure 15.5. For the purpose of the experiment, we developed three tools: (i) a route builder, which was responsible for the generation of the delivery schedule (i.e. building the route that the truck would follow); (ii) the delivery schedule simulator, which was using the information provided by the route builder as input to simulate the delivery schedule of each vehicle; (iii) the real-time fleet-management platform (incident-handling module), which was used when a deviation from the initial plan was detected. During the simulation tests we simulated the entire system with all its functionalities: ● ● ● ●

the monitoring process; the trip projection, which incorporates the travel prediction methods; the decision support module, which incorporates the rerouting algorithms; the user interfaces (both in the control center and at the vehicle).

All were simulated in an integrated manner so as to be as similar as possible to real-life testing of the system. The test case scenarios depicted in Table 15.3 were designed by using the fractional factorial methodology. Factorial experiments (including fractional factorial ones) are systematic ways to perform an experimental investigation that yields all statistically significant effects of all factors and their interactions (Montgomery, 2001). As mentioned above, in the case of a delayed vehicle, the new plan may exclude one or more clients from the route (i.e. a set of customers) if it is not feasible to serve all clients due to the accumulated delay. In order, however, to prioritize the customers to serve such a case, a weight (i.e. customer importance) was given to each client. The weight was quantified by

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Step 1

Route builder

Define customer network

Step 2

Route builder

Generate route for delivery schedule

Step 3

Real-time fleetmanagement platform

Set delivery constraints

Step 4

Delivery schedule simulator

Execute delivery schedule

Step 5

Real-time fleetmanagement platform

Time violation

Step 6

Delivery schedule simulator

Step 7

Real-time fleetmanagement platform

Yes Generate new route for remaining customer

No

Complete the delivery schedule

Figure 15.5 Simulation process.

Table 15.3

Test case scenarios.

Test case

Area

Traffic

Type of time window

Number of time windows

Range of time windows

1 2 3 4

Suburban Suburban Urban Urban

Heavy Light Heavy Heavy

N/A N/A N/A Small

N/A N/A N/A Relaxed

5

Urban

Heavy

Small

Tight

6

Suburban

Light

High

Relaxed

7

Urban

Heavy

High

Tight

8

Suburban

Light

Driver’s shift Driver’s shift Driver’s shift Customer’s restrictions Customer’s restrictions Customer’s restrictions Customer’s restrictions Customer’s restrictions

High

Tight

a factor (from 1, less important to 10, very important) according to the type of the customer and its importance. Based on this, in order to evaluate the customer service achieved by each vehicle in a certain test, we calculated a ratio as the sum of weights of customers visited by each truck divided by the total weight of all customers in the specific delivery plan.

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Variable Without system use With system use

Total performance results 75

71 70 66

67

66

66

65

Performance (%)

65

62 60 60 56 55 54 52

51

Trial_6

Trial_7

51 50

48

49

45 42 40 Trial_1

Trial_2

Trial_3

Trial_4

Trial_5

Trial_8

Figure 15.6 Performance results for the eight trials (simulation testing).

CS j =

∑w

i

i ∈S j

∑w

× 100 j = 1,2,.....n

(1)

i

i ∈ST

where Sj is the set of customers visited by truck j and ST is the entire set of all customers in the route. The route that achieves the highest CSj is the preferred one. In many cases, this route may contain a lower number of high-importance customers. However, a route with a higher CSj score and a higher number of customers served is clearly superior. Figure 15.6 shows the customer service (quantified by CSj) achieved for each test case. As can be seen, in all test cases, when the directions provided by the real-time fleetmanagement system were followed, a higher performance was achieved. Particularly in cases where simulation tests were conducted in urban areas or included a lot of customers with time of delivery restrictions, the proposed system had a superior performance. Thus, it was concluded that the use of a real-time fleet-management system affects the performance of urban freight delivery. The real-life tests to confirm these results are described below.

15.5 15.5.1

REAL-LIFE TESTING Profile of the company

NIKAS SA is one of the leading companies in the processed meat sector in Greece. Its portfolio includes a large variety of products, such as sausages, dairy products, sandwiches, and frozen pizzas. The company is present at over 5000 points of sale and has a 22% market

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Figure 15.7 Initial monitoring of delivery execution.

share. Its main factory operates with 23 000 m2 of useful surface (i.e. areas of production, warehousing, and distribution). Every day more than 40 t of goods must be distributed to an average of 400 clients, located at distances ranging from 5 to 40 km (Attica Prefecture) away from the company’s main depot. The orders placed must be delivered – most of the time – the following day using the company’s own fleet of 13 trucks. Given that many of the company’s clients are hotels, restaurants, and fast-food restaurants a guaranteed delivery time of the products is of great importance. Because of the highly congested urban environment of Athens and Piraeus, the company faces various problems due to unexpected incidents (mainly travel and service time delays) that may adversely affect the delivery process. Currently, when a delay occurs, interventions are performed through voice communication between the driver and the dispatcher. Often the effectiveness of these interventions is limited, since there is no systemic way of taking into consideration the multitude of parameters involved, such as the importance of the remaining clients, time windows restrictions and so on.

15.5.2

System operation and test case scenarios

In a typical operation, the real-time fleet-management system monitors the adherence to the initial delivery plan continuously. Figure 15.7 depicts the user interface of the control center at an initial stage, in which the travel estimation technique has not detected any deviation from the initial plan (the column with the estimated arrival time for each client is highlighted in light gray). After a vehicle has served a number of clients (see Figure 15.8), the system detects several time-window violations for non-served clients (certain cells of the column are highlighted in dark gray) and proposes a rerouting plan (i.e. a different way of visiting the remaining clients). The new delivery plan is transmitted to the driver through the onboard terminal (Figure 15.9). Figure 15.10 shows the customer service (quantified by CSj ) achieved for each test case. For all test cases, the vehicle that followed the new route designed by the real-time fleetmanagement system (Vehicle B), provided higher customer service. As can be seen the results are close to the simulation results presented in Figure 15.6.

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Figure 15.8 Detection of delivery-time violation and rerouting plan.

Figure 15.9 On-board terminal.

Table 15.4 summarizes key data for each test case. It shows the initial number of clients, the number of clients visited by each vehicle, the importance of the visited clients, total customer service, as well as the performance achieved in each test case. For example, for Test Case 1, Truck B visited 18 clients of a total importance of 102 points, which led to an improvement in the CS by 22. An important finding from this test has been the impact of time windows on the system’s performance. Indeed, in the first three cases (Tests 1–3), in which only the restriction of the driver’s shift pattern has been applied, the total number of clients served by vehicles A and B was almost equal. In Tests 4–8, which included client time windows (in addition to the driver’s shift), the system performed better in terms of clients served and succeeded in reducing time-window violations. The number of clients in the initial plan is another important factor. The higher the number of clients served, the better the performance of the system.

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Variable Truck A Truck B

Customer service (All test cases) 100 95

% Customer service

90

87 81

80

80

77

75 72

74

72

70

70

67 65

60 59

Test_1

60

60

56 Test_2

Test_3

Test_4 Test_5 Test cases

Test_6

Test_7

Test_8

Figure 15.10 Customer service for all cases in NIKAS SA.

This is due to the wider choice of customers to serve in the revised plan. Results from Cases 1, 5, and 7 (all of which included a large number of initial clients), show that Truck B visited most of the clients and, in particular, those with higher importance.

15.6

CONCLUSIONS

In this chapter we described a novel system for real-time management of a delayed distribution vehicle. The requirements for dynamic fleet management were elicited through interviews with logistics managers. We presented the architecture of the proposed system, the methodology employed for delay prediction and rerouting, as well as the results from comprehensive tests in a simulated environment for a Greek company. We have shown that it is possible to combine travel time prediction methods with rerouting algorithms into a systemic approach, as exemplified by the real-time fleetmanagement information system we have developed. System testing results, both during simulation testing and through the case study, show that the proposed approach can yield improvements in customer service through the avoidance of time-window violations. In addition, we have shown that the performance of the system is dependent on the size of the customer base (the higher the number of clients served, the better the system performance) due to the wider choice of customers to serve in the rerouting plan. The system has some limitations, however: (i)

The mobile and satellite technology used. If the vehicle does not have a view of the sky, the system is unable to track the vehicle, preventing proper estimation of the expected arrival time for the remaining clients. However, as tracking interruptions are usually of

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Driver’s shift

Client’s restrictions

1 2 3 4 5

6

107

21 5

6

25 9 9 7 25

64

13 3

5

14 5 5 4 15

Truck A

Truck A, B

81

15 4

5

18 6 6 5 22

Truck B

Number of visited clients

Number of scheduled clients

387

70 26

29

84 29 33 29 87

Truck A

478

81 30

37

102 45 41 36 106

Truck B

Importance (weight) of visited clients

326,57

46,67 27,46

39,30

53,32 36,32 32,14 31,56 59,80

Truck A

357,56

43,78 31,76

40,60

55,99 41,99 38,45 37,09 67,90

Truck B

Total distance traveled (km)

64

67 70

74

59 56 60 60 65

Truck A

80

77 81

95

72 72 87 75 80

Truck B

Total customer service (%)

Truck A follows the predefined delivery schedule whereas Truck B follows the directions provided by the real-time fleet-management system.

Total Average

7 8

Type of windows

Results from the pilot testing in NIKAS SA.

Test case

Table 15.4

25

15 15

28

22 28 45 25 23

Performance difference

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(ii)

the order of a few minutes (i.e. interruptions occur very rarely when the vehicle is in motion) there are no significant practical effects on system performance. As far as possible interruptions of the terrestrial communication (GPRS) network are concerned, there is actually no limitation, since information concerning the location of the vehicle as well other collected data are stored in the telematic equipment of the vehicle and are transmitted to the control center as soon as the network connectivity is restored. User acceptance. The issue of acceptance and actual use of the system mainly concerns the truck drivers, who are not typically exposed to such IT-assisted ways of executing deliveries. During the case study, we did not notice significant user-acceptance issues, beyond the expected initial difficulties in using the system and, less expectedly, drivers’ concerns about the perceived ability of the system to “spy” on them, thus providing management with information that could be used at a later stage. However, the issue of user acceptance remains a significant research question inasmuch as the success of such an approach is dependent on user adherence with system principles, further to the capability of the algorithms to yield near-optimal rerouting solutions.

It should be noted that the proposed system may be used for managing other incidents by using appropriate algorithms. We have also developed algorithms and tested the system for the vehicle breakdown case (Zeimpekis, 2007). Finally, the ideas presented here may be extended to emergency services, couriers, rescue and repair services, as well as taxicab services. In each case, the system should address the particular characteristics of the specific environment. Of course, the main concept and architecture of the real-time fleet-management system (i.e. incident handling by using dynamic travel prediction methods and rerouting algorithms) will remain applicable.

ACKNOWLEDGMENTS The author gratefully acknowledges the Hellenic General Secretariat of Research & Development for partially funding this research under the project entitled Mobile Real-Time Supply Chain Execution (MORSE). Acknowledgments go also to the project partners: Planning S.A, the University of the Aegean, the Athens University of Economics and Business, Emphasis Telematics, NIKAS SA, and Diakinisis SA.

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16

RFID-enabled Visibility in a Dairy Distribution Network

Daniel Hellström and Henrik Pålsson

16.1 INTRODUCTION Arla Foods is one of the largest dairy companies in Europe, which exclusively produces milk-based products. It is co-operatively owned by milk producers in Sweden and Denmark. Besides its main markets of Sweden, Denmark and the UK, Arla Foods runs subsidiaries in 19 other market areas all over the world. Its core business activities are the development, production and distribution of dairy products. In contrast to most other retail suppliers in Sweden, Denmark and the UK, where products are distributed by the retailers themselves, Arla Foods distributes fresh products directly to retail outlets. In order to distribute its milk-based products efficiently, Arla Foods uses different types of returnable transport items (RTIs). RTIs have increasingly been introduced in various industries and may offer significant benefits over traditional single-use packaging. RTIs include all the means of assembling goods for transport, storage, handling and product protection in the supply chain, and are returned for further use. They include, for example, returnable pallets, as well as all forms of reusable crates, totes, trays, boxes, roll pallets, roll cages, barrels, trolleys, pallet collars, racks, lids and refillable liquid or gas containers (ISO, 2005). In Sweden, Arla Foods has traditionally used one type of roll container in the distribution of dairy products. This traditional roll container was specifically designed to be used for the distribution of fresh milk, which constitutes the single greatest part of the total volume distributed by the company. This roll container is used for transport, externally and internally at dairies, and to display products in retail outlets. However, the introduction of new products and new primary packaging designs has drastically increased the range of dairy products the company offers. This has affected the production and distribution processes; one example is the picking process, which was previously performed by the lorry driver at the lorry platform and is now performed at a dairy distribution centre (DC). The increased range of products has also resulted in greater volumes of the distributed product being placed and displayed on retail shelves and not in the traditional roll container. To meet requirements regarding efficient picking and distribution of low-volume products, Arla Foods has introduced a new roll container. This is made of metal and has the dimensions 430 × 660 × 1430 mm (see Figure 16.1). The roll container has three compartments, which cross the roll container horizontally. To enable more efficient return Intelligent Agrifood Chains and Networks, First Edition. Edited by Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis. © 2011 by Blackwell Publishing Ltd. Published 2011 by Blackwell Publishing Ltd.

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Figure 16.1 The new roll container.

transport the roll container can be widened at one end so that empty roll containers can be inserted into one another.

16.1.1 Problems with traditional roll containers Arla Foods has experienced difficulties in managing and controlling the rotation of roll containers. A large number of roll containers are lost and misplaced every year and information concerning how many roll containers are in circulation or how many are in stock at dairies is not available. A major problem is theft. It is common knowledge at Arla Foods that firms in other industries, such as removal and catering firms, build up their internal logistics using roll containers stolen from firms such as Arla Foods. Such theft of roll containers is a major reason why Arla Foods loses large numbers of roll containers annually. Based on historical purchases of roll containers, Arla Foods suspects that roughly 10% of its roll containers are lost annually. Arla Foods estimates that the company has approximately 80–100 000 traditional roll containers. The cost of a roll container is approximately €120, meaning that a loss of 10% constitutes a cost of between €1 million and €1.2 million annually. In total, Arla Foods must reinvest more than €2 million annually in RTIs to cover lost assets.

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To decrease its reinvestment costs, Arla Foods has focused on procuring roll containers at a low cost and minimising the roll container fleet. To combat the loss of roll containers, Arla Foods has assigned a group of employees (called ‘returnable goods police’) to collect lost and misplaced roll containers and other RTI assets belonging to the company. However, such action is not a long-term solution to the problem. In spite of this action, Arla Foods is still losing 10% of its roll containers annually.

16.1.2 Introduction of the new roll container Because of its characteristics, with three enclosed shelves compared to the traditional format, which has two shelves with side panels, the new roll container is more useful. It is therefore judged by Arla Foods to be even more liable to be stolen. Based on its experience of the use of traditional roll containers, Arla Foods estimated that twice as many new roll containers would be lost compared to traditional ones, i.e. about 20% each year. Consequently, in order to introduce the new roll container, Arla Foods realised the need to improve visibility of its RTIs. The Council of Supply Chain Management Professionals (2010) defines visibility as ‘the ability to access or view pertinent data or information as it relates to logistics and the supply chain, regardless of the point in the chain where the data exists’. Arka also recognised that they would need to manage and control the rotation of the new roll containers. Furthermore, the new roll container was to be a crucial component in the dairy DC. A shortage of roll containers would cause major distribution disturbances. To improve the situation, Arla Foods decided to implement a tracking system for its new roll container. To enable visibility, Arla Foods realised that the tracking system should include an automatic identification technology supporting unique identification of the roll containers at different locations throughout the supply chain. The tracking system would also contain a database with the recorded locations of individual roll containers, and a data analysis tool, which could be used to generate reports on RTI movements. It should be noted that the tracking system does not contain any data about the goods which the RTIs hold.

16.1.3 The core problem when introducing a new roll container When introducing the new roll container, the core problem was a lack of visibility in the distribution system. For the old roll containers, the lack of visibility had resulted in a vast number being lost or misplaced. Since the new roll containers were judged to be even more appealing for potential thieves, as well as being more costly, there was an imminent risk of high costs for Arla Foods resulting from an increased number of new roll containers being lost or misplaced. Consequently, Arla Foods realised that it needed to improve the visibility of the new roll containers.

16.2 ACHIEVING VISIBILITY Based on the fact that Arla Foods needed to improve the visibility of roll containers, the company decided to implement a tracking system with unique identification of each roll container. The process of designing a tracking system included two steps: (i) (ii)

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system setup – useful data to be collected, and control mechanisms; identification technology solution.

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Linking roll containers to customers/routes

Jönköping dairy distribution centre

Picking

Transport Retail outlets Transport

Shipping

Roll container buffer

Receiving

Repair

Receiving

Replenishing

Shipping

Storage

Linking roll containers to the dairy

Linking roll containers to the repair shop Figure 16.2 A system using three identification locations.

16.2.1 System setup – useful data to be collected, and control mechanisms The initial step in setting up a tracking system was to identify what information regarding the roll container flow could be useful and what data had to be collected from the roll container flow in order to generate that useful information. These issues were discussed in a number of workshops. The first proposal was to manage and control the roll container in a rental system, where Arla Foods customers would pay a daily or weekly rental fee if the roll containers were returned to Arla Foods. A rental system was, however, rejected because the hardware investment and the additional work for the lorry drivers were considered to be too great. In addition, such a system would require additional administration and would not be appreciated by customers. To proceed with the system setup, a modified solution based on the characteristics of a rental system was developed. In this setup, three identification points at the dairy were used: one in the receiving process, another in the picking process and a third one at the repair shop (see Figure 16.2). All roll containers would have to pass through the first two locations, which would enable Arla Foods to use two virtual zones for roll container localisation: one internally in the dairy and another externally, i.e. roll containers in transport to the dairy or at a specific customer. Based on these zones, localisation of each roll container could be uniquely traced. Thus, Arla Foods could receive information about exactly how many and which roll containers were located in the dairy or at a specific customer, including those in transport to and from that customer. The third identification point, i.e. at the repair shop, was suggested in order for the type of damage to and repair needed for individual roll containers to be recorded. The modified setup, with three identification points, was chosen by Arla Foods to manage and control the roll containers.

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The RFID system RFID tag: passive, read-only, 64-bit. Radio frequency: 125 kHz Technical read range: 250 mm Read range in real conditions: 100 mm Maximum speed of tag when read: 20 m/s Number of readers: 3 Middleware developed for data processing Figure 16.3 An RFID tag attached to a wheel housing.

16.2.2 Identification technology solution Having decided on the system setup, the next step for Arla Foods was to choose an identification technology for data gathering. The requirements of the identification technology were that it should support generation of data that were accurate, reliable, timely and efficiently gathered. The old roll containers and plastic crates at Arla Foods were uniquely labelled with barcodes. However, Arla Foods had experienced a number of disadvantages relating to barcodes. One disadvantage was that barcodes require manual scanning, which is a time-consuming activity. According to Arla Foods, barcode scanning was also regarded as laborious by some staff, meaning that they did not always scan the barcodes, which in turn undermined the reliability of the system. Another disadvantage was the fact that barcodes were easily damaged due to rough handling of roll containers and were thus not always readable. Due to these disadvantages, Arla Foods decided to evaluate other possible identification technologies. The conclusion was that RFID technology was the most appealing. The company consequently decided to concretely investigate RFID technology further in a trial. The trial was successful and resulted in Arla Foods deciding to start the roll-out at the dairy in Jönköping. The main purpose of this implementation was to gain visibility of the roll containers in order to improve their management and control. Through RFID technology, accurate and precise data regarding the roll container flow could be automatically captured. In addition to its main goal, Arla Foods also gained experience and insights into RFID technology through the implementation. This was regarded as essential for future information exchange between Arla Foods and its customers, thereby improving the possibility of increasing the level of customer service offered by the company. RFID insights are thus in line with the company’s aim of being a first-rate supplier to retailers and being deemed to have excellent customer service. The technical characteristics of the RFID system chosen by Arla Foods are described in Figure 16.3. A practical consideration of the RFID implementation worth noticing is

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3PL provider

Dairy distribution centre

Retailers

Transport Retail outlets Transport

Picking

Shipping

Receiving

Replenishing

Roll container buffer

Receiving

Shipping

Storage

Repair

Figure 16.4 The rotation of the new roll containers.

the location of the RFID tag on the roll containers. Numerous tests revealed that the most appropriate placement from a read-rate perspective was the wheel housing (Figure 16.3).

16.3 JÖNKÖPING DAIRY IMPLEMENTATION Arla Foods’ dairies are made up of three physically integrated plants: a production plant, a warehouse for the finished products and a dairy DC. Milk, cream and sour milk are produced in the Jönköping dairy. After production, the products are stored in the warehouse for finished products and are distributed from here to Arla Foods’ other dairies. In the dairy DC, low-volume products are picked and distributed to retail outlets. High-volume products are picked directly from the warehouse for finished products. The new roll containers circulate in closed loops between a dairy DC and retail outlets (see Figure 16.4). A loop starts at the roll container station when pickers collect roll containers. First, a picking assignment is initiated by automatically printed destination barcode labels from the warehouse management system (WMS). Then a picker applies the labels to roll containers. The RFID tags on the roll containers are thereafter linked to customers by associating the destination bar code with the RFID tag on the roll container. The scope of the implementation can be summarised in the fact that, in total, the Jönköping dairy DC distributes approximately 500 stock keeping units (SKUs) to 2200 delivery points/ retail outlets using approximately 80 lorries. On average the dairy DC processes 6000 customer orders, representing a weight of 3500 t every week. The customer order lead time varies between 4 and 24 h. Transport activities between the dairy DC and retail outlets are performed by a third-party logistics provider.

16.3.1 Implementation outcome Introducing the roll container involved the risk of losing one in five roll containers annually, but after having the RFID system running for more than a year hardly any roll containers had been lost at the Jönköping dairy. The elimination of the expected loss has mainly been

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due to people’s awareness that the roll containers are tracked using RFID rather than as a result of actual action taken by Arla Foods. This awareness of the system and its visibility capabilities has made the dairy organisation, lorry drivers and customers pay more attention to rules and procedures concerning the control of roll containers.

16.3.2 Expanding the implementation to include four DCs At the beginning of 2009, Arla Foods had completed its full implementation involving approximately 26 000 new roll containers in four dairy DCs. The new roll container is used for approximately 20% of the distributed product volume, while the remaining product volume is distributed using other types of RTI. In total, the four dairy DCs distribute approximately 500 SKUs to 14 000 delivery points/retail outlets. This case study mainly considers on the implementation at the Jönköping dairy DC, but it also provides some insights from the roll-out at the Gothenburg dairy DC. The implementation at Gothenburg mirrors the one in Jönköping, except for the roll container fleet size. Approximately 6000 roll containers were introduced at Jönköping but only 2900 at Gothenburg. However, the implementation outcome at the Gothenburg dairy was very different. As with the Jönköping dairy implementation, Arla Foods put a lot of effort into informing the Gothenburg dairy organisation, lorry drivers and customers about the company’s ability to track roll containers, and it regularly followed up ‘lost’ roll containers. However, after having the system up and running a few months, the follow-up of ‘lost’ roll containers was forgotten, and Arla Foods went back to business as usual. Approximately 1 year after the system’s introduction, an analysis of the number of lost roll containers was prepared. The analysis revealed an interesting pattern. It showed that the number of lost roll containers was close to zero until Arla Food lost interest in following up lost units. Thereafter, it seemed that the number of lost roll containers increased in an exponential manner. The overall shrinkage of roll containers was equivalent to more than 15% of the roll container fleet on an annual basis. In one month the shrinkage was close to 30% on an annual basis. The very high latter figure was likely caused by the ‘market’ for the newly introduced roll container not being saturated. Arla Foods realised that having visibility is not enough; proper action and continuous management attention are needed in order to attain a low shrinkage rate.

16.4 COST-BENEFIT ANALYSIS WITH ROI CALCULATIONS AND SENSITIVITY ANALYSIS Based on implementation at all four DCs, an ROI analysis indicated a payback period of approximately 14 months (see Table 16.1). The total cost of the investment was estimated at approximately €300 000. The investment costs included attaching a tag to 26 000 roll containers and installing three readers at each of the four dairies that were to use the roll container. The development of the middleware, which integrates the RFID system with Arla Foods warehouse management and enterprise resource planning systems, is assumed to suit all four dairies. The total running gain from the investment was estimated at approximately €265 000 annually. Arla Foods expected that up to 20% of its 26 000 roll containers would be lost annually. However, an RFID system would not eliminate the whole loss. Arla Foods

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Table 16.1

Payback analysis for the RFID investment at the four dairy DCs. Amount/dairy

Hardware Tags Plastic plate Reader process units Reader antennas Reader stations Servers System integration Man-hours for tag installation Man-hours for reader installation Software development, installation Trial Training operational staff

3 3 3 1

25

Total amount

Cost €

26 000 26 000 12 12 12 4

1.0 0.8 2 000 1 000 500 3 000

26 000 20 800 24 000 12 000 6 000 12 000

2 200

37.5

82 500

100

40

4 000

1

75 000

75 000 30 000 10 000

Cost of investment

302 300

System maintenance and support

10 000

Running costs Decrease in roll container loss: 7.5% Decrease in tied-up capital: 20% Running profit Payback period (years)

Total cost €

10 000 1 950

120

5 200

5% of 120

234 000 31 200 265 200 1.2

made a moderate estimate that the loss would at least decrease by 7.5%, which equals approximately €234 000 annually in reduced losses of roll containers. In the final analysis, tied-up capital was also embedded in the running profit. The RFID system aimed to increase control of the roll containers, resulting in the possibility of reducing the number of roll containers needed by 20–30%. Assuming 20% fewer roll containers and an interest rate of 5%, the decreased tied-up capital was estimated at approximately €31 000 annually. A benefit that was not included in the analysis was the decrease in costs related to operational disturbances to the dairies. Operational disturbances, due to lack of roll containers, represent an uncommon problem. However, whenever there is disturbance it results in extremely high costs. Arla Foods’ final investment and the running costs of the implemented RFID system at the Jönköping dairy turned out to mirror those of the cost-benefit analysis, except for the additional cost of data analysis software and time spent by Arla Foods employees, all of which was not considered or included in the analysis. Apart from these omissions, the cost of the implementation corresponded to the cost-benefit analysis. The running profit from the system is, however, difficult to verify. The running profit is based on the assumptions that the investment would decrease the annual roll container loss by 7.5% and reduce the number of roll containers needed by 20%. The RFID investment resulted in nearly 0% loss of roll containers at the Jönköping dairy, while a 20% annual loss was expected by Arla Foods to

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Regression sensitivity for payback period

Mean=1.27 Decrease in container loss

–.738

Decrease in tied-up capital

–.059

0 5% 0.56

2

6 –1

4

90%

5% 2.84

–0.75 –0.5 –0.25

0

0.25

0.5

0.75

1

Standard slope coefficients

Figure 16.5 Risk assessment and sensitivity analysis of the payback analysis.

take place without the investment, indicating that the running gain was based on modest assumptions. Moreover, operational benefits of the RFID investment, such as decreases in manual inventory control, sorting, counting, quality control and reporting, are not included in the analysis. As the payback time heavily depends on the running gain it is interesting to see how sensitive the payback period is to the assumptions made in the running gain calculation. To do this, a risk assessment through Monte Carlo simulation was performed. The percentages decreases in annual roll container loss (minimum 0%, most likely 7.5%, maximum 20%) and decrease in number of roll containers required (minimum 0%, most likely 20%, maximum 30%) were modelled using discrete triangular distributions. Triangular distribution was selected since there were no data available. Subject matter experts at Arla Foods were asked for their most optimistic, most likely and most pessimistic estimates in order to obtain data estimates. One hundred thousand iterations were performed and the resulting histogram of the payback period and the sensitivity analysis in the form of a tornado graph are presented in Figure 16.5. The histogram indicates the range of potential payback periods. The tornado graph indicates the correlation between payback period and parameters. This means that the payback period is more sensitive to container loss than to tied-up capital.

16.5 LESSONS LEARNED The implementation of RFID technology to control and manage new roll containers has generally been successful for Arla Foods. The estimated risk of losing one in five roll containers annually was initially overcome by having visibility and taking action on potential shrinkage situations. Arla Foods internal analyses show that the elimination of lost roll containers at the beginning of the implementation is related to the fact that the people involved became aware of the visibility of roll containers in the system, i.e. because Arla Foods was able to track and trace roll containers, the dairy DC organisation, lorry drivers and customers paid more attention to rules and procedures concerning their control. However, a few months after the RFID implementation, Arla Foods’ Gothenburg dairy did not use its track-and-trace capabilities due to the reappearance of old habits. This resulted in an increased shrinkage rate to more than 15% of the roll container fleet on an annual

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basis. This highlighted the need for asset visibility, but showed that visibility alone is not enough; proper actions and continuous management attention are required in order to attain low shrinkage.

16.5.1 Implementation process A number of success factors and shortcomings have been identified in the implementation process. One success factor was to use a systematic and problem-oriented approach, i.e. not having a technology-oriented approach. This means that from a project point of view, the implementation was not an ‘RFID project’. The overall purpose was to ensure visibility of the roll containers in order to manage and control them more efficiently. RFID was the auto-ID technology chosen to do the job of identifying roll containers, resulting in the project becoming an RFID implementation project. However, the focus was on increasing visibility. According to Arla Foods, the company had to bear this goal in mind in order to avoid becoming blinded by the extensive opportunities offered by RFID technology. They had to focus on the technology and not on the problem. Another success factor was to keep the implementation as simple as possible in terms of administration and technology. Not introducing a rental system or using a more advanced RFID system enabled Arla Foods to achieve a reliable and functioning system with relatively low investment costs. As the level of complexity in the implementation was minimised, this approach also meant that the cause of problems could be identified and managed. A third success factor was the fact that the RFID trial was performed in a real environment, i.e. in a dairy. Performing the RFID trial at a dairy and not in a laboratory environment enabled Arla Foods to verify the concept and the technology with real requirements and disturbances, such as electromagnetic interference, shifting temperatures, liquids, metal, etc. Furthermore, it enabled Arla Foods to choose an RFID system specifically based on its own requirements and needs. A fourth success factor was gaining acceptance from the dairy DC organisation, particularly from the pickers and their managers. The dairy DC did not always link roll containers to customers/routes, which ruined the whole idea of the implemented system. To link roll container requires only a few more seconds than just collecting empty roll containers. However, the source of the problem is that the container station is a bottleneck. Arla Foods tackled the lack of acceptance by informing the staff involved about the importance of linking roll containers to customers/routes and by providing them with training. In addition to these success factors, together with Arla Foods two shortcomings were identified in the implementation process, which would be key to success in future implementation processes. One shortcoming was related to the inability to handle the accumulated data. In an implementation process regarding asset visibility, it is easy to forget how to analyse, interpret and display the accumulated data. Arla Foods lacked instruments providing information processing capabilities and a user-friendly interface. The tracking system used had only limited report-generating capabilities, i.e. although tracking data were available, the visibility for employees at Arla Foods was restricted. Another shortcoming of the implementation process was a failure to actively involve the receiving organisation at the Jönköping dairy. The reason for this approach was that the Jönköping dairy went through a major distribution and warehouse restructuring during the implementation process and there was consequently little time to participate. Even though there was a valid reason, this approach led to lack

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Total number of cycles versus cycle time in days 20000

No. of cycles

15000

10000

5000

0 1

2

3

4

5 6 7 Cycle time in days

8

9

10

Figure 16.6 Distribution of roll container cycle time.

of support and acceptance from the receiving organisation, making the full roll-out slightly problematic.

16.5.2 Indirect benefits from having visibility Besides learning from the implementation process, Arla Foods also gained other knowledge and indirect benefits. Based on the accumulated data so far, Arla Foods has been able to learn the fundamentals of the rotation of the roll containers. One example is the distribution of the roll-container cycle time, which indicates that nearly all roll containers are returned back to the dairy within three to four days (see Figure 16.6). This roll-container cycle time data, and data concerning how many roll containers are used in each customer shipment enable Arla Foods to simulate the rotation of the roll containers in order to find out the appropriate fleet size. In the long-term, Arla Foods also aims to have a system that generates alarms when deviations occur, for example when a roll container has been away for more than 10 days. The implemented RFID system enables Arla Foods to handle the uncertainty of roll container demand. The system provides Arla Foods with granular data, which enable decisions based on real historical demand. Figure 16.7 illustrates the kind of data provided by the implemented system, which might be used in managing and controlling the rotation of roll containers. Accumulated data from the repair area are also useful for Arla Foods. When roll containers are repaired, the individual roll container identification number is registered and the type of repair and the damage are recorded. This means that Arla Foods can identify the physical strengths and weaknesses of the roll containers and relate the damage to, for example, who produced the roll container, batch number, the previous customer/route of the roll container or its repair history, etc. Based on this type of analysis, Arla Foods may identify underlying core problems resulting in damaged roll containers.

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Number of cycles versus cycle times in days

No. of cycles

40

30

20

10

0 1

2

3

4

5

6

7

8

9

10

Cycle time in days Figure 16.7 Distribution of cycle time for a retail outlet.

16.5.3 Technology insights As RFID technology was new to Arla Foods, its implementation resulted in technology insights. Arla Foods gained insights into RFID system components, functionalities, performance and influencing factors such as metals and liquids. In the setup used, RFID technology provided Arla Foods with reliable information from automatic data capture. This means that the identification activity does not interrupt the daily working procedures. Another technological insight was how RFID technology and barcode technology could complement each other. For example, barcodes are used for backup, linking roll containers to customers/ routes and for performing checks on customers who may have difficulties in returning roll containers. Arla Foods choose to use 125 kHz RFID in its setup, which was slightly more robust than the 13.56 MHz alternative. In comparison, hardware costs were also slightly lower. Arla Foods is pleased with the performance of the chosen RFID technology. For example, the read rate is almost 100% and almost no RFID tags have been broken, meaning that the RFID tags are even more durable than the roll containers. Even though RFID technology using ultra high frequency (UHF) has gained acceptance in the retail industry, and standards are available from various organisations such as GS1, Arla Foods does not regret its choice to implement a system operating at 125 kHz frequency. The company claims that if there were any benefit or customer demand for UHF, it would be relatively easy to change the current system. RFID technology costs are often mentioned as one of the main barriers to adopting the technology in supply chains. However, for the application of RFID technology to track RTIs, costs are generally not considered a barrier (Hellström, 2009). The cost and benefit estimate provided in this case study shows that the payback for Arla Foods’ investment was approximately 14 months. It should, however, be noted that each case is unique, requiring a separate cost-benefit analysis for each implementation. A lesson learned is that when using

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RFID tags in tracking RTIs, where the tags are continuously reused, the cost of the tags does not seem to be a central issue. System integration, the number of readers and the process of applying the tags are issues that in themselves may involve higher costs than the cost of the tags.

16.6 CONCLUDING DISCUSSION The characteristics of the roll containers in this case study are representative for RTIs in general. Even though RTIs, in general, are expensive, vulnerable to theft or misplacement, and critical for production and distribution, they are often managed with limited visibility or control (McKerrow, 1996; Twede, 1999; Witt, 2000). This may be because RTIs are challenging assets to manage; they require accurate counting, reporting and shared information among organisations (Twede and Clarke, 2004). Another explanation could be that companies implementing RTIs focus on aspects other than visibility, for example: ● ● ● ●

operational benefits, such as improved protection and security of products; improved working environments; more efficient handling and cube utilisation; reduced use of packaging materials and waste (Livingstone and Sparks, 1994; Kroon and Vrijens, 1995; Witt, 1999; Maloney, 2001).

A third explanation could be that costs associated with plans for adopting RTIs rarely include shrinkage, i.e. theft or misplacement of RTIs (Rosenau et al., 1996). The short payback time due to reduced shrinkage by having visibility of roll containers at Arla Foods highlights the potential of having visibility of RTIs. The shrinkage level at Arla Foods is by no means unique. In a survey of 233 enterprises in consumer-oriented industries undertaken by the Aberdeen Group (2004), a quarter of the respondents report that they lost more than 10% of their RTI fleet annually, with 10% of the respondents losing more than 15%. The cost of a single RTI varies between approximately ten and thousands of euros. It is not uncommon that the value of the RTI exceeds the value of the goods it holds, meaning that an RTI fleet often represents a significant capital investment, and shrinkage may represent a considerable operating cost. This case study provides an increased understanding of the effect of visibility on the management of RTI systems. The results imply that significant cost savings can be achieved. However, it must be emphasised that visibility alone is not enough; it requires proper actions and continuous management attention in order to attain the savings. This was highlighted when roll containers at the Gothenburg DC were poorly managed. For a short period of time, shrinkage was almost 30%. Similar conclusions have been presented in other research. For instance, Brewer et al. (1999), as well as Johansson and Pålsson (2009), provide evidence of tracking being valuable to manufacturing as well as to logistics performance. It also, however, highlights that tracking capability needs to be complemented with data-processing and analysis tools. The use of RTIs in the food industry is increasing. In addition to Arla Foods, numerous firms have reported use of RTI tracking systems. Marks & Spencer, for example, has announced that it tracks 3.5 million returnable food produce delivery trays throughout its supply and distribution network, thereby allowing the company to speed up its supply chain and reduce errors. The Dutch retailer Hoogvliet tracks roll containers from DCs to retail

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outlets in order to reduce handling errors (LogicaCMG, 2004). Tesco has announced that it has revised its plan to tag trays of high-value goods, deciding instead to tag its RTIs delivered to retail outlets from DCs (Collins, 2006). Finally, there is one additional benefit to having visibility of RTIs that Arla Foods has not achieved yet. According to Frazelle (2002) the sizing and configuration of an RTI fleet can be minimised by fleet visibility. Furthermore, studies have shown that it is difficult to determine fleet size, especially in the introduction phase (Johnsson and Hellström, 2007). Thus, companies tend to overestimate the fleet size needed since RTIs are often fundamental to both production and distribution. As visibility is gained for all Arla Foods dairy DCs, the company is able to refine fleet configuration and sizing, thereby minimising the risk of RTI shortage or of having surplus RTIs.

REFERENCES Aberdeen Group (2004) RFID-enabled Logistics Asset Management, Benchmark Report. Aberdeen Group, Boston, MA. Brewer, A., Sloan, N. and Landers, T. L. (1999) Intelligent tracking in manufacturing. Journal of Intelligent Manufacturing, 10(3–4), 245–250. Collins, J. (2006) Tesco Revises RFID Plans, RFID Journal, 7 April. Available at: http://www.rfidjournal. com/article/articleview/2243 (accessed October 2010). Council of Supply Chain Management Professionals (2010) Glossary of terms. Available at: http://cscmp. org/digital/glossary/glossary.asp (accessed 8 March 2010). Frazelle, E. H. (2002) Supply Chain Strategy: The Logistics of Supply Chain Management. McGraw-Hill, New York. Hellström, D. (2009) The cost and process of implementing RFID technology to manage and control returnable transport items. International Journal of Logistics Research and Practice, 12(1), 1–21. ISO (2005) Information technology – unique identification. Part 5: unique identification of returnable transport items (RTIs). Working draft, ISO/IEC 15459–5. Johansson, O. and Hellström, D. (2007) The effect of asset visibility on managing returnable transport items. International Journal of Physical Distribution and Logistics Management, 37(10), 799–815. Johansson, O. and Pålsson, H. (2009) The impact of Auto-ID on logistics performance – a benchmarking survey of Swedish manufacturing industries. Benchmarking: An International Journal, 16(4), 504–522. Kroon, L. and Vrijens, G. (1995) Returnable containers: an example of reverse logistics. International Journal of Physical Distribution & Logistics Management, 25(2), 56–68. Livingstone, S. and Sparks, L. (1994) The new German packaging laws: effects on firms exporting to Germany. International Journal of Physical Distribution & Logistics Management, 24(7), 15–25. LogicaCMG (2004) Making waves: RFID adoption in returnable packaging. Available at: http://www. logicacmg.com/page/400003596 (accessed October 2009). Maloney, D. (2001) Returnable savings. Modern Materials Handling, 56(9), 37–38. McKerrow, D. (1996) What makes reusable packaging systems work. Logistics Information Management, 9(4), 39–42. Rosenau, W. V., Twede, D., Mazzeo, M. A. and Singh S. P. (1996) Returnable/reusable logistical packaging: A capital budgeting investment decision framework. Journal of Business Logistics, 17(2), 139–165. Twede, D. (1999) Can you justify returnables? Transportation & Distribution, 40(4), 85–88. Twede, D. and Clarke, R. (2004) Supply chain issues in reusable packaging. Journal of Marketing Channels, 12(1), 7–26. Witt, C. E. (1999) Transport packaging: neat and clean or down and dirty. Material Handling Engineering, 54(9), 71–73. Witt, C. E. (2000) Are reusable containers worth the cost? Transportation & Distribution, 41(9), 105–108.

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17

CONCLUSIONS

Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis

The food sector is one of the most important sectors for most economies and contains some unique characteristics, probably due to the fact that food is the most universal commodity. Competition, varying customer tastes and preferences, and the high perishability of food products makes food chain members, including manufacturers and retailers, develop and implement new technologies and processes in the food supply chain (Boyer and Hult, 2005). Another characteristic of the food sector is its size diversity and global penetration. The sector includes both small and medium-sized firms but there are also some very large firms who have achieved global presence. On top of this, the sector has experienced a plethora of changes over the past few years, including the emergence of global retailers who have become the supply chain captains, the dominance of own brands, the high market sales concentration in the sector at both manufacturing and retail level, and the introduction of tougher laws regarding food safety and quality after recent food crises (Hughes, 1994; Kaufman, 1999; Fearne et al., 2001; Bourlakis and Weightman, 2004). This book has focused on the food sector and has illustrated state-of-the art electronic business applications and intelligent information technologies in the area of food and beverages. This chapter will introduce the reader to the evolution of the food supply chain, where the most intelligent technologies are being applied. It is followed by a section examining some relevant technologies, the key benefits emanating from their use and their implications for managers and food companies. The chapter concludes with some final thoughts from the book’s editorial team.

17.1

EVOLUTION OF THE FOOD CHAIN

Numerous forces have had an evolutionary impact on the food chain. Strak and Morgan (1995) have stressed five major forces: globalisation, market structure and power, consumer tastes and lifestyles, technological change and regulation. These forces are interconnected and interrelated, and have an impact on the structure and dynamics of the chain and its evolution. An example of this interrelationship is when food retailers source fresh fruit and vegetables (and other food products) from different countries. This has been directly linked to consumer demand (Sparks et al., 2006) and the demand is satisfied by using a plethora of advanced logistics systems and information communication technologies (ICTs) in the food chain (Bourlakis and Bourlakis, 2006). As a result, this global sourcing and selection of Intelligent Agrifood Chains and Networks, First Edition. Edited by Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis. © 2011 by Blackwell Publishing Ltd. Published 2011 by Blackwell Publishing Ltd.

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Small to medium sized firms

Rise of large manufacturers via publicly-owned corporations with many small processors and retailers

Mix of publiclyowned manufacturing oligopolies, retail chain concentration and many smaller entrepreneurs

Polarisation of manufacturing and retailer structures via concentration, acquisition and divestment

I. The era of early competition 1900–1920

II. National consolidation 1920–1945

III. Internationalisation 1945–1980

IV. Globalisation 1980–2000

Source: Ramsey, 2000; Cotteril, 2001.

Structure

Evolution of the food system.

Phase

Table 17.1

Manufacturers extend globally and retailers go multinational

Retailer branding increases level of penetration and begins to challenge manufacturer branding. Both now ‘oligopolistic’

Golden age of manufacturer branding and mass marketing

‘Imperfect’ competition and start of acquisition activity Food manufacturing an important factor in national economies

Move to national/ major regional level in one country Limited export

Multinational expansion of major manufacturers with significant increase in turnover

Best example of ‘perfect’ competition after farming entrepreneurial

Competitive environment

Local/regional within one country but for commodity movement

Scope

Supply chain in Europe run by retailers and challenging for dominance in North America

National manufacturers dominate but some retail challenge resulting from concentration

Run by national manufacturers with wholesaler and retail-chain support

Run by regional wholesalers

Control of supply chain?

Major manufacturers identify core categories Superbrands, retailer brands, address vertical coordination issues in a concentrated channel, internet grocers

Brand management at national and international level Increased demand for market data/ information

Rise of national branding, sales, advertising and research and development Private label appears

Limited branding, mainly commodities

Degree of marketing sophistication

Turnover in food service now challenging for leadership as slowdown in food sales at retail

Food expenditure declines as percentage of disposable income Move to larger retail outlets Growth of eating out

Rise in per capita income and demand for wide range of branded convenience foods

Food a major part of disposable income – up to 50% in some countries

Consumer demand

Conclusions

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fresh produce gives these retailers a competitive advantage, especially against their smaller counterparts. In this way, the large multiple retailers have increased their market share and power in the food chain, leading to further enquiries by regulatory bodies, as evidenced in the UK food chain in the work of the Competition Commission (Blythman, 2005). Ramsey (2000) has suggested four phases in relation to food chain evolution. The era of early competition (1900--1920) was the first phase, when regional wholesalers dominated the food supply chain. The consolidation period (1920–1945) was the second phase, when local and national manufacturers enjoyed the most important role in the food chain. During the third phase, the internationalisation period (1945–1980), the vast majority of food manufacturers moved away from their domestic bases and, at local and national level, started facing many challenges from food retailers. Subsequently, in the fourth phase (1980–2000), the globalisation phase, retailers dominated the food supply chain and challenged manufacturers (see Table 17.1). Since 2000, food retailers have completely dominated the food chain by becoming ‘chain captains’. One major initiative during this time has been factory gate pricing (Finegan, 2002), where retailers pick up the products from suppliers and manufacturers from the manufacturing plants (factory gate). Hence retailers are responsible for the product collection (and its logistics cost) and pay a smaller product price to suppliers/manufacturers. Apart from this initiative, other recent developments in the food chain include use of regional warehouses/centralisation, temperature-controlled (composite) distribution and the large use of third party logistics services by retailers (Bourlakis and Bourlakis, 2005). Specifically, food retailers use large regional warehouses to manage their supply chains, which can be quite complex considering that they comprise thousands of products and sometime thousands of stores (Bourlakis and Bourlakis, 2005). Temperature-controlled (composite) distribution (for both warehouses and transportation) implies that a multi-temperature lorry or warehouse deals with products at various temperatures (ambient, chilled, frozen) all together (Bourlakis and Weightman, 2004; Smith and Sparks, 2004). To accommodate all these practices and processes in their supply chains, food retailers employ largely third party logistics firms, and it is expected that these logistics firms will enjoy a more critical role in the near future (Bourlakis and Bourlakis, 2005). This expectation is supported by the fact that there is considerable variation in the use of third party logistics firms between the countries of the European Union (EU). For example, the use of third party logistics firms is a very popular practice in many EU countries, such as the UK, but it is less popular in other EU countries, such as Greece (Marketline International, 1997). The key message from the above discussion, for the purposes of this book, is that various technologies have been applied at different levels of the food chain evolution. ICT started being employed towards the end of the third phase of the food chain evolution (1945–1980), while in the fourth phase (1980–2000), ICT was employed extensively (see Bourlakis and Bourlakis, 2006). From the fourth phase onwards, intelligent technologies were introduced and used extensively in the food chain and some of those are described in the next section.

17.2

TECHNOLOGIES IN THE FOOD CHAIN, KEY BENEFITS AND IMPLICATIONS

It is worth noting that during the last few decades we have seen a dramatic increase in the use of these technological applications and technologies, penetrating every economic sector and having a tremendous impact. The e-transformation of business processes has become

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an unavoidable corporate response to increasing competitive pressures as well as an adaptation to a rapidly emerging digital business environment. Successful companies are those that have integrated their internal processes with those of external suppliers and customers (Frohlich and Westbrook, 2001; Boyer et al., 2004). Towards this objective, information sharing between companies and supply-chain enterprises becomes of paramount importance, and a range of applications have been applied, most of which are discussed in this book. For a start, electronic data interchange (EDI) in recent decades and the internet (or even internet EDI) in the last decade have supported supply chain firms to share information and collaborate (Bourlakis and Bourlakis, 2005, 2006; Christopher, 2005). Numerous other applications have followed, especially those focusing on the use of intelligent technologies, which have been analysed extensively in this book. Despite this, the food and beverage sector has been lagging behind other sectors in terms of the use of electronic business applications and intelligent information technologies. This situation has changed dramatically in the past few decades as food companies have recognised that the use of these applications and technologies provides a competitive advantage. Large companies, especially food retailers and manufacturers, have therefore used e-business applications to increase their power in agrifood supply chains, aiming to improve customer service, create economies of scale, reduce logistics costs and facilitate the efficient flow of food and information. Small and medium-sized food companies followed suit and used, inter alia, web-based e-business solutions to exploit niche markets and create new market segments. Furthermore, the corporate focus has shifted from the food company to the food chain, suggesting a more system-wide approach. The latter change has been supported by many factors, including the recent food crises as well as the need to collaborate at chain level in order to put in place traceability and transparency systems. In addition, there are great general benefits and savings to be gained by the use of intelligent technologies in supply chain management. Some of the main benefits of intelligent technologies in food chains are summarised below: (i) Trust, and mostly the lack of it, has been repeatedly found to be a moderating factor of buyer–seller relationships (Child and Faulkner, 1998; Rademakers, 2000). Typically, the application of ICT alters trading relations. Empirical studies suggest that powerful partners (usually large retailers) take advantage of ICT to gain more power or impose their strategy on smaller partners. However, ICT does not necessarily have to be obstructive in order to be effective. For example, Bakos and Dellarocas (2003) describe online reputation mechanisms as an emerging alternative to more established mechanisms for promoting trust and cooperative behaviour, such as legally enforceable contracts. Das and Malek (2003), who defined supply chain flexibility as the robustness of the buyer–supplier relationship under changing supply conditions, found that order quantities and supply lead times are the two most common factors associated with flexibility. Intelligent agents can manage orders effectively and reduce lead times, thus increasing the flexibility of the chain. Mangina and Vlachos (2005) found that there can be great benefits and savings from the use of intelligent agents for the beverage supply chain. Intelligent technologies can make the supply chain traceable, increase transparency and therefore increase trust among supply chain partners and forge consumer confidence. (ii) Information visibility: The visibility of appropriate information in a distribution network is necessary in order to optimise scheduling and planning costs. Information visibility means having the right data at the right time. As a consequence, the success

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of any technological improvement depends on delivering information visibility to the system as obtained from relevant supply chain partners. Intelligent technology has the advantage of having access to different layers of information, even in cases where information has been processed with different techniques. For example, RFID can substantially increase the information visibility in comparison to barcoding. RFID has been examined extensively in this book, and numerous applications have been described. In the food chain, Karkkainen (2003) identified the key benefits of RFID for short shelf-life product retailers whilst Jones et al. (2004) illustrated the opportunities and the challenges of RFID implementation for UK retailers. (iii) Efficiency: Managing the bullwhip effect carefully eliminates the possibility of many supply problems such as excessive inventory, severe delays, poor product forecasts, unbalanced capacity, poor customer service, uncertain production plans, high backlog costs and lost sales. Efficiency is the cornerstone of competitive advantage and traditional ICT and intelligent technologies have much to offer in this sense. For example, numerous internet-based applications have facilitated integration between food manufacturers and retailers. Retailers have been active in terms of forward integration toward the consumer (e.g. via e-retail sites), but they have not so far engaged in backward integration, with some exceptions (Kaufman, 1999; GMA, 2000; Fearne et al., 2001). In other cases, food manufacturers plan jointly with retailers, making product forecasts and promotions by using relevant technology-based platforms such as the Collaborative Planning Forecasting and Replenishment tool. Overall, in the food sector, electronic integration has been successfully applied (see for example, Harrison and van Hoek, 2008). The above issues create numerous implications for food managers, food companies in general and small and medium-sized enterprises (SMEs) in particular, which are described below.

17.2.1

Implications for food managers

Food companies take the first step into electronic business by creating a website. A corporate website is the cornerstone of market transparency and allows consumers to track all the relevant information about the food they purchase and consume. Market transparency raises consumer confidence and trust in the integrated supply chain. A website is required, but it is not a sufficient condition to achieve full market transparency. Food traceability is also necessary but this requires e-business applications to enhance transactions. In addition, food tracking and tracing require supply chain integration. Food traceability is hard to implement without the help of modern technology and e-business applications. Food traceability is harder to achieve when the supply chain is fragmented, as can be the case in Southern Europe. Another issue is fragmentation, which creates supply chain inefficiencies, inhibits market transparency, creates information asymmetries and endangers food quality and safety. Policy measures should address supply fragmentation by supporting company participation in e-marketplaces, creating clusters of SMEs, virtual chains, etc. Overall, e-business is a new dimension for food companies and at the same time it opens access to new markets and provides opportunities for re-engineering existing business models.

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17.2.2

Implications for large food companies and SMEs

The spread of ICT reflects the structure of the food industry. Large multinational companies (which are usually leaders in their sectors) are the most technologically advanced companies, while smaller companies lag behind in terms of adopting ICT. The main factors that push companies in the food sector to consider ICT solutions include greater efficiency in internal processes (productive, administrative, delivery of orders, etc.) and integration of internal processes with external organisations to improve logistics and reduce costs. A more integrated view is emerging, with leading companies looking for ways to apply technology strategically to improve business and supply-chain-wide activities. E-business tools are more suitable for leading agribusiness corporations, and large European and US agribusiness corporations have already applied e-business solutions. Large retailers and manufacturers take advantage of e-business solutions in order to leverage their power in the supply chain over competing companies and alternative supply channels. However, SMEs lack the operational readiness of large corporations and the necessary resources to invest in expensive e-business applications. SMEs normally use the internet to disseminate information about their products and to a lesser extent to distribute their products and services electronically. The adoption of an e-business model by SMEs depends on external pressure, as when a large retailer inflicts an EDI system on its food suppliers. These SMEs also adopt technology as a competitive necessity rather than a competitive advantage. Small agribusiness managers should also be aware of new advanced ICTs and continuously evaluate their contribution. Intelligent systems are used to automate transactions, which facilitates supply chain management, enhances customer relationships and reduces operation costs. The implementation of intelligent chain systems often implies the creation of direct and indirect costs and benefits. Agribusiness managers and entrepreneurs need to quantify the costs and benefits associated with the adoption of intelligent chain systems in order to arrive at sound decisions. There is still the need to raise awareness among SMEs of the benefits and risks, based on real experience and best cases. For example, web-based systems are cheap for SMEs, but there is still the barrier of complexity that SMEs have to deal with. The inherent complexity of chain systems, such as in the case of traceability, can be eradicated by policy initiatives and interventions. Overall, food supply chain links are diverse in nature and include buyer–seller transactions among producers, traders, agents, wholesalers and retailers. The heterogeneity of food partners restrains the application of a unique technology throughout the supply chain. If successful, this will increase adoption rates and pace, create a critical mass of users and eventually lead to its widespread diffusion across the food supply chain.

17.3

CONCLUDING REMARKS

This book has had contributions from numerous authors based in a range of academic institutions across the world. We would like to thank the authors of the book chapters for their insightful and invaluable contributions and for supporting us in this initiative. Special thanks also go to David McDade from Wiley-Blackwell and his team for the assistance given during the past few years. Lastly, we anticipate that this book will be of great interest to academics teaching and researching in this field but will also attract interest from students, professionals, managers, practitioners and policymakers engaged in the food chain and in the use of intelligent technologies.

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REFERENCES Bakos, Y. and Dellarocas, C. (2003) Cooperation without enforcement? A comparative analysis of litigation and online reputation as quality assurance mechanisms. In: e-Business Research at MIT, March 26, 3(2). MIT, Sloan School of Management Working Papers, Cambridge, MA. Blythman, J. (2005) Shopped: The shocking power of British supermarkets. Harper Perennial, London. Bourlakis, C. and Bourlakis, M. (2005) Information technology safeguards, logistics asset specificity and 4th party logistics network creation in the food retail chain. Journal of Business and Industrial Marketing, 20(2/3), 88–98. Bourlakis, M. and Bourlakis, C. (2006) Integrating logistics and information technology strategies for sustainable competitive advantage. Journal of Enterprise Information Management, 19(2), 389–402. Bourlakis, M. and Weightman, P. (eds) (2004) Food Supply Chain Management. Blackwell Publishing Ltd., Oxford. Boyer, K.K. and Hult, T.G. (2005) Extending the supply chain: integrating operations and marketing in the on-line grocery industry. Journal of Operations Management, 23(6), 642–661. Boyer, K.K., Frohlich, M.T. and Hult, T.G. (2004) Extending the Supply Chain: How Cutting Edge Companies Bridge the Critical Last Mile into Customers’ Homes. American Management Association, New York. Child, J. and Faulkner, D. (1998) Strategies of Cooperation: Managing Alliances, Networks, and Joint Ventures. Oxford University Press, Oxford. Christopher, M. (2005) Logistics and Supply Chain Management: Creating Value – Adding Networks, 3rd edn. Pearson Education, London. Cotterill, R.W. (2001) Dynamic explanations of industry structure and performance. British Food Journal, 103(10), 679–714. Das, S.K. and Malek, L.A. (2003) Modelling the flexibility of order quantities and lead-times in supply chains. International Journal of Production Economics, 85, 171–181. Fearne, A., Hughes, D. and Duffy, R. (2001) Concepts of collaboration-supply chain management in a global food industry. In: J.F. Eastham, L. Sharples and S.D. Ball (eds) Food and Drink Supply Chain Management Issues for the Hospitality and Retail Sectors. Butterworth-Heinemann, Oxford. Finegan, N. (2002) Backhauling and Factory Gate Pricing. Institute of Grocery Distribution, UK. Frohlich, M.T. and Westbrook, R. (2001) Arcs of integration: an international study of supply chain strategies. Journal of Operations Management, 19, 185–200. GMA, (2000) Food manufacturers take first step toward real B2B e-commerce for the grocery industry. Available at: http://www.gmabrands.com/news/docs/NewsRelease.cfm?DocID=615. Harrison, A. and van Hoek, R. (2008), Logistics Management and Strategy, 3rd edn. Pearson Education, Harlow. Hughes, D. (1994) Breaking with Tradition: Building Partnerships and Alliances in the European Food Industry. Wye College Press, Wye. Jones, P., Clarke-Hill, C., Shears, P., Comfort, D. and Hillier, D. (2004) Radio frequency identification in the UK: opportunities and challenges. International Journal of Retail & Distribution Management, 32, 164–171. Kärkkäinen, M. (2003) Increasing efficiency in the supply chain for short shelf life goods using RFID tagging. International Journal of Retail & Distribution Management, 31(10), 529–536. Kaufman, P. (1999) Food retailing consolidation: Implications for supply chain management practices. Journal of Food Distribution Research, 30(1), 6–11. Mangina, E. and Vlachos, I.P. (2005) The changing role of information technology in food logistics management: Re-engineering food chain using intelligent agents technology. Journal of Food Engineering, 70(3), 403–420. Marketline International (1997) EU Logistics. Market International, London. Rademakers, M.F.L. (2000) Agents of trust: Business associations in agri-food supply systems. International Food & Agribusiness Management Review, 3, 139–153. Ramsey, B. (ed.) (2000) The Global Food Industry: Strategic Directions. Financial Times Retail and Consumer Publishing, London. Smith, D. and Sparks, L. Temperature-controlled supply chains. In: M. Bourlakis and P. Weightman (eds) Food Supply Chain Management. Blackwell Publishing Ltd., Oxford, 179–198. Sparks, L., Gustafsson, K., Jonson, G. and Smith, D. (2006) Retailing Logistics and Fresh Food Packaging: Managing Change in the Supply Chain. Kogan Page, London. Strak, J. and Morgan, W. (1995) The UK Food and Drink Industry. Euro PA & Associates, UK.

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Index

Aberon information system, 144 agricultural production management systems, 67–82 fleet management, 70–75 use of robotics, 69–70 agrifood industries (general considerations) composition and structures, 8–11 evolutionary perspectives, 281–3 key benefits of new technologies, 284–5 key influencing factors, 281–3 algorithmic modeling approaches, vehicle re-routing and fleet management, 71–5, 106, 250–53, 257–8 animal feed industries, 8 and traceability, 118–19 Application Identifiers (AI), 160, 162 Arla Foods (Sweden/Denmark), 267–80 implementation of RFID tracking systems, 275–80 Asda (UK), market share and turnover, 10 asset management, use of RFID technologies, 122–4 automated check-outs, 124 automated harvesting systems, 69 Bacchus satellite imagery program, 173, 176–7 bar coding, 33, 59, 160–62 edible, 164 key features, 111 beverage product manufacturers, employment and turnover comparisons, 8–9 biometric features, identification and tracking systems, 164 Brandt Beef (US), 118–19 Budoubatake farmers’ market (Japan), 238–40 buy-one-get-one-free promotions, 21

Campofria (Spain), 119 centralisation trends, 29–30 cereal products manufacturers, employment and turnover comparisons, 8 chain traceability, 152–3 check-outs, automated, 124 cheese industry, use of RFID technologies, 119 city logistics see urban environments cold chain principles, 119–20 competition effects, 281, 282, 283 ‘composite distribution’, 30–31 consumer privacy, use of RFID technologies, 115 consumer trends, 11–14 dietary changes, 232–3 environmental impacts, 233–4 evolutionary perspectives, 282 impact on logistics management, 29–30 contamination threats, 12 ‘contract distribution’, 31–2 cross-docking warehouse facilities, 43 Curry Report (2002), 13 dairy product manufacturers employment and turnover comparisons, 8 use of RFID-enabled visibility systems, 267–79 data distribution and exchange, 17–21, 33–5 electronic data interchange (EDI), 17–21, 33–5 data processing, retail sector, 35–6 ‘dead reckoning’, 92 DEFRA, analysis of UK industry sectors, 8–10 Demeter system (automated harvesting), 69 DFMs see direct farmers’ markets

Intelligent Agrifood Chains and Networks, First Edition. Edited by Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis. © 2011 by Blackwell Publishing Ltd. Published 2011 by Blackwell Publishing Ltd.

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Index

direct farmers’ markets (DFMs) benefits and rationale, 230–31, 245–6 characteristics, 236 consumer support studies, 244–5 examples and case studies (Japan), 238–44 government funding, 236 market share and sales (Japan), 235 disease control and information systems, 136–46 predictive microbiology, 138–9 distribution management approaches and trends, 30–32 key processes, 49–57 problems within urban environments, 49–57 technology improvements (overview), 59–63 use of geographical information systems, 68, 73–4, 93, 97, 170, 177–8 use of positioning systems, 88–93 use of proof-of-delivery technologies, 62–3 use of telematics in freight transport, 94–101 use of telematics in product distribution, 101–5, 249–64 use of temperature management tools, 59–61 use of vehicle-routing technologies, 61–2, 250–64 see also logistics management downstream (forward) tracking, 152–3 e-business applications, 17, 19–20, 80, 98, 103–6, 113, 167–78 classification and categorisation, 168–9 implementation implications for large and SME companies, 286 implementation implications for managers, 285 key applications for agrifood management, 169–70 key benefits, 284–5 training needs, 189, 191–2 use in online selling, 171–2 use in procurement, 172 use in SMEs, 179–92 use in terrain mapping and monitoring, 175–7 EAN codes see tGTIN (Global Trade Item Numbering) codes EAN-UCC traceability systems see GSI systems ear tags, 118, 125, 158–9 EDI see electronic data interchange (EDI) education and training on diet and sustainability issues, 235 on implementation of e-business practices, 189, 191–2 efficiency drivers (new technologies), 285

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electronic data interchange (EDI), 17–21, 33–5 employment data (agri-food industries), 8–9 enterprise resource planning (ERP) systems, 14–16 uptake and usage, 15–16 environmental issues, best practice policies and requirements, 47 epidemiological data capture, 137–8 EPoS systems, 33 EQOS systems, 21 ERP (enterprise resource planning) systems, 14–16 uptake and usage, 15–16 EU quality assurance schemes, 133 EU Regulations on food hygiene, 13 on labelling, 115, 152 on refrigerated products, 39, 41–2 on traceability, 12, 115, 152, 154–5, 158–9, 211 Euro-Retailer Produce Working Group Good Agricultural Practices (EurepGAP), 133 European Food Safety Authority (EFSA), 41 evolutionary perspectives on food chain systems, 281–3 expiry dates, control mechanisms, 47–8, 57 eye recognition systems (livestock), 164 Farm Assurance schemes (UK), 134 farm management systems, 67–82 fleet-management technologies, 70–75 use of robotics, 69–70 farm vehicle management systems, 70–75 farmers’ markets benefits and rationale, 230–31, 245–6 characteristics, 236 consumer support studies, 244–5 examples and case studies (Japan), 238–44 government funding, 236 market share and sales (Japan), 235 fencing, virtual, 78–9 field monitoring systems, 81–2 use of satellite technologies, 175–7 fish product manufacturers, employment and turnover comparisons, 8 fleet-management systems for agricultural production, 70–75 for product distribution, 61–2, 250–64 use of algorithmic approaches, 71–5 see also distribution management flow models (for traceability), 13 food and drink manufacturing

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Index

composition of industry, 8–9 information systems, 14–16 retail ordering processes, 17–21 traceability demands, 11–14 food and drink retailing dominance of supermarkets, 9–11, 22–3 impact of consumer/societal changes, 29–30 industry dynamics in Greece, 198–9 IT systems, 17–21, 32–6 logistic operations, 27–36 food hygiene and safety, 132–3 case studies (Greece), 140–46 crises response systems, 138 decision-support systems, 139–40 predictive microbiology tools, 138–9 quality assurance schemes, 13, 46–7, 133 supply chain considerations (overview), 133–5 UK legislation, 12–13 use of information systems, 136–46 see also traceability Food Labelling Regulations 1996, 12 Food Safety Act 1990 (UK), 12 food scares consumer safety concerns, 132–3 cost to producers, 220–21 crises response systems, 138 impact on consumer buying trends, 11–12 product recalls, 120 Food Spoilage Predictor (FSP), 139 Food Standards Agency (FSA), 12 foraging, regulation, 155 frozen foods packaging processes, 215 quality controls, 215, 218–24 ready-meals sector, 10 storage, 216 use of RFID applications case study (Greece), 214–24 fruit harvesting, use of robotics, 70 fruit and vegetable product manufacturers, employment and turnover comparisons, 8 functional foods, 11 Galileo (European Position System), 92 geocoding, 93 geographic mapping see GIS (geographic information systems) Gillette, 211 GIS (geographic information systems), 68, 73, 74, 93, 97, 170, 173–7

Bourlakis_bindex.indd 291

291

Global Data Synchronisation Network (GDSN), 161 Global Food Safety Initiative (GFSI), 134 Global Location Number (GLN), 161 Global Navigation Satellite System (GNSS), 88–90 Global Trade Item Numbering (GTIN) codes 160–62 see also bar coding globalisation effects, 281, 282, 283 Go-Online programme (Greece), 180, 183–92 GPS tracking systems, 61–2, 88–93 components and design, 90–93 development history, 89–90 in real-time fleet-management systems, 256 and RFID integration, 79–80 grain and starch product manufacturers, employment and turnover comparisons, 8 Greece food safety case studies, 140–46 frozen food warehouse operations case study, 214–24 grocery retailing, 198–9 SMEs and ICT adoption, 179–92 green differentiation, 134 Growth Predictor software, 139 GSI eCom, 161 GSI MobileCom, 161 GSI system, 160–62 GTIN see Global Trade Item Numbering codes HACCP (hazard analysis and critical control point) approaches, 13, 133 case studies, 142–3, 145 certification, 47 healthy eating trends, 11–12 herbicides, microspraying, 69–70 Hoogvliet (Holland), 279–80 Hortibot (robot), 70 human resources practices, ICT compatibility, 180–81 hygiene and safety issues see food hygiene and safety information and communication technology (ICT) barriers to adoption, 185, 187 definitions, 2, 136 in agricultural production, 76–82 in food safety activities, 135–46 in logistics management, 2, 40, 57–63 in manufacturing, 14–16

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292

Index

information and communication technology (ICT) (cont’d ) in retail logistics, 32–6 in small and medium sized enterprises (SMEs), 179–92 in supply-chain management, 17–21 key benefits, 284–5 training needs, 189, 191–2 Infoterra (geo-information products), 174, 175–6 Institut Coopératif du Vin, 174–5 intelligent products, 124–5 intelligent systems barriers to adoption, 185, 187 key benefits, 284–5 training needs, 189, 191–2 see also e-business applications; individual technologies internal traceability, 152 internationalisation trends, 282, 283 Internet (general), 17, 19–20, 80, 98, 103–6, 113 safety and trust issues, 182 use in food safety tracking, 134, 136–8 use in procurement, 172 use in selling, 171–2 use in supply-chain management, 36, 134 see also e-business applications inventory processes, 122 Ireland, food product manufacturers, 9 ISO requirements for food safety management, 133 for traceability, 151–2, 155–9 for warehousing operations, 46–7 ISOBUS system, 76 Japan and sustainable food systems, 227–46 background and concept history, 227–31 consumer and dietary trends, 231–5 development of local food systems, 231–5 examples of farmers’ markets, 235–44 support by consumers, 244–5 ways forward for future developments, 245–6 ‘just-in-time’ approaches, 30–31 labelling regulations, 12 see also bar coding; traceability labour force (retail), IT scheduling models, 35 leasing operations, warehouses, 44 legislation EU traceability, 153–4 UK food industry regulation, 11–14

Bourlakis_bindex.indd 292

USA traceability, 154–5 LFS see local food systems livestock management feed source traceability, 118–19 health monitoring, 118–19 quality assurance schemes, 134 use of feature recognition systems, 164 use of RFID systems, 78–80 use of tags, 118, 125, 158–9 local food systems, 228–46 benefits and rationale, 230–31 described, 228–9 Japanese farmers’ markets, 235–46 location-based services (LBS), 106 logistics management, 27–36 background history, 27–8 concept definitions, 2, 28 distribution approaches and trends, 30–32 distribution processes, 49–57 impact of contracting-out operations, 31–2 in urban environments, 49–50, 50–57, 59–63 role of new technologies, 32–6, 40, 57–63 use of telematics, 94–101 see also warehousing operations manufacturers of food and drink products, employment and turnover comparisons, 8 marketing, use of RFID technologies, 124–5, 212–13 Marks and Spencer (UK) equipment tracking systems, 279–80 market share and turnover, 10 mobile assets management, 123 mAuction applications, 106–7 meat product manufacturers, employment and turnover comparisons, 8 Metro (Europe), 211 Michinoeki farmers’ market (Ukiha - Japan), 242–4 microspraying techniques, 69–70 Moraitis (Australia), 123 Morrisons (UK), market share and turnover, 10 MRP (materials requirements planning), 14 MRP-II (manufacturing resource planning), 14 multiple retailers location planning, 35 partnership working with suppliers, 20–21, 22–3 procurement (electronic) systems, 17–21 support systems and decision-making tools, 35–6 UK market share comparisons, 10

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Index

Nestlé (SA), 9, 21, 229 NIKASS SA (Greece), 259–62 Oenoview service (wine industry), 173–7 oils and fats manufacturers, employment and turnover comparisons, 8 online transactions, 171–2, 185 safety and trust issues, 182 optical signatures, 164 organic food consumer demand, 11 control and regulation, 155 ‘own-account distribution’, 31–2 own-label products, market share and turnover, 10 Parmigiano Reggiano (Italy), 119 Pathogen Modeling Program (PMP), 138–9, 142, 145 pathogens in food products see disease control and information systems; food hygiene and safety perishable foods characteristics, 40–42 cold chain principles, 119–20 distribution, 53–7 regulation authorities, 41 regulatory frameworks, 39, 41–2, 47 spoilage and wastage rates, 54 storage, 45–9, 47–9 temperature constraints by product and storage type, 55 use of telematics in distribution, 101–5 see also food hygiene and safety pesticide use, 41, 135 Petri nets, 73 picking-to-light systems (order picking), 197 point-of-sales processes automated check-outs, 124 marketing improvements, 124–5 smart shelves, 124 positioning systems, 88–93 poultry management, use of RFID systems, 79–80 precision agriculture (PA) definitions, 67–8 early applications and adoption, 68–9 privacy issues, use of RFID technologies, 115 procurement systems electronically generated orders, 17–21 online, 172 product differentiation and targeting, 212–13

Bourlakis_bindex.indd 293

293

product recalls, 120 costs, 220–21 Progressive Enterprises (New Zealand), 119 proof of delivery (POD) systems, 62–3 PulseNet system, 137 quality assurance schemes, 13, 46–7, 133 quality control management processes use of RFID systems, 119–20 in warehousing operations, 46–7 radio frequency identification (RFID) systems, 2, 35, 58–9, 109–25 development history and applications, 109–10, 210–11 efficiency and traceability drivers, 115–16 estimating costs-benefits of implementation, 273–5 ethical issues, 114–15 features and technologies, 110–15, 210–11 hardware and components, 111–13 implementation of new systems, 277 potential applications (overview), 115–17, 210–11 potential benefits, 273–5, 284–5 problems and drawbacks, 113–15 software enhancements and advanced technologies, 113, 163 use in agricultural production, 77–81 use in asset management processes, 122–4 use of disposable tags, 79 use in manufacturing processes, 120–21 use in marketing, 124–5, 212–13 use in quality control, 119–20 use in retail point of sales processes, 124–5 use of semi-passive tags, 60–61 use in soil monitoring, 80–81 use in storage and distribution, 58–9, 60–61, 106, 197 use in tracing and tracking produce, 117–19, 162–3 use in tracking equipment and theft prevention, 267–80 re-ordering processes, from consumer’s homes, 125 ready-meals, industry dominance, 10 real-time monitoring systems for use in distribution management, 57, 59–60, 106, 249, 250–64 future applications, 264 impact on specified arrival times, 261–2

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294

Index

real-time monitoring systems (cont’d ) in storage and warehousing operations, 48–9, 57–8 system architecture and requirements, 255–7 user acceptance, 264 vehicle surveillance devices, 252–3 see also e-business applications recall of products, 120 costs involved, 220–21 refrigeration operations, 54–5 cold chain principles, 119–20 temperature constraints by product and storage type 55 see also frozen foods regulations see EU Regulations retail sector see food and drink retailing retail warehouses see warehousing operations RFID systems see radio frequency identification (RFID) systems rice consumption trends, 233 Richmond Meats (New Zealand), 118 risk management consumer drivers, 12–13 regulatory frameworks, 12–14 robotics, 69–70 simple multiple vs complex single systems, 73–5 Rokko Blessing farmers’ market (Japan), 241–2 roll containers (dairy industry), 268–9 theft prevention initiatives, 271–80 Safeway (UK) cargo tracking, 123 stock control systems, 35 Sainsbury (UK) market share and turnover, 10 supply-chain technologies, 18, 21, 36 use of RFID systems, 122 salmonella, 11–12, 137–8 satellite technologies, 88–90, 173–4 components and design, 90–93 development history, 88–90 terrain mapping, 175–7 SCADA (supervisory control and data acquisition) systems, 15 Scottish Courage, 123 seed maps, 69 semi-passive RFID tags, 60–61 Serial Shipping Container Code(s) (SSCC), 161–2 sewage contamination, 135 small and medium sized enterprises (SMEs)

Bourlakis_bindex.indd 294

ICT applications, 179–92 impact of ICT adoption on performance, 181–2, 189–92, 286 smart collars (livestock), 79 smart labels, 59–60 Smart and Secure Tradelines for Africa project, 124 smart shelves, 124 SMEs see small and medium-sized enterprises (SMEs) soil monitoring wireless systems, 81–2 see also satellite technologies solar cells, 81–2 SSCC see Serial Shipping Container Code(s) (SSCC) Standard Industry Code(s) (SIC), 8 Starbucks (coffee), 123–4 stock control systems, 35, 124 see also supply chain management (SCM); warehousing operations storage and distribution centres (general overview), 30–31 see also distribution management; warehousing operations store space allocation, IT support systems, 35 Sudan Red contamination, 12 supermarket retailers location planning, 35 partnership working with suppliers, 20–21, 22–3 procurement (electronic) systems, 17–21 support systems and decision-making tools, 35–6 UK market share comparisons, 10 supply-chain management (SCM), 17–21, 131 characteristics, 2 definitions, 1–2 information sharing and collaboration, 19–20 roles in food safety management, 132–5 use of IT systems, 35–6, 135–46 use of RFID technologies, 210–11 surveillance devices (vehicles), 252–3 see also fleet-management systems; satellite technologies SUS-CHAIN project, 134 sustainability in agrifood chains, 227–31 development of local farm systems, 228–31 Japanese farmer’s markets, 231–46 telematics, 87–107 definitions, 2–3

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Index

infrastructure and technological prerequisites, 88–93 use in freight transport, 94–101 use in product distribution systems, 101–5, 249–64 value-added applications and advanced technologies, 105–7 temperature control regulations, 39, 42 sensors and monitors, 48–9, 57–8, 61 in storage, 48–9, 57–8 in transit, 53–5, 56 see also refrigeration operations terrain mapping, satellite systems, 68, 73, 74, 93, 97, 170, 173–7 Tesco (UK) equipment tracking systems, 280 inventory processes, 122 market share and turnover, 10 supply-chain technologies, 18, 21, 36 TETRA (terrestrial trunked radio), 89 tGTIN codes see Global Trade Item Numbering codes theft prevention initiatives, use of RFID technologies, 267–80 third-party logistics (3PL) companies, 31, 43, 94, 283 traceability, 117, 151–64, 211–13 benefits and rationale for use, 209–10, 211–13 cf. tracking, 152–3 concept definitions, 117, 151–2 drivers and trends, 11–12, 115–16, 151–2, 209–10 essential elements, 153 food sources, 118–19 forms and types, 152 information flows, 13, 152–3 key benefits, 152 legislative frameworks, 153–5 quality and safety management systems, 155–9 software decision support case studies, 140–46 system design principles, 156–9 techniques and methodologies, 159–64 use of biometric feature identification, 164 use of Global Trade Item Numbering, 160–62 use of internet, 134, 161, 163 use of RFID systems, 117–19, 162–3, 213, 214–24

Bourlakis_bindex.indd 295

295

use of voice-recognition systems, 163 see also radio frequency identification (RFID) systems; telematics Tracer Factory system, 145 tracking definitions, 152 for equipment thefts/losses, 267–9 use of RFID-enabled visibility technologies, 267–80 see also traceability transport food distribution, 51–3, 61–2 food production, 70–75 impact of centralisation trends, 30–31 use of telematics, 94–101 see also distribution management; fleetmanagement systems; vehicle routing trends in consumer demand, 11–14, 232–3, 282 trust issues (buyer-seller relationships), 284 UK-based agri-food industries, employment and turnover comparisons, 8–11 United Biscuits, 121 Universal Product Code(s) (UPC), 160–61 upstream (backward) tracing, 152–3 urban environments key issues and problems, 49–50 product distribution processes, 50–7, 59–63 US Department of Defense, 211 vehicle choice (distribution) for perishable goods, 55 see also fleet-management systems vehicle routing, 51–3 capacity calculations, 52 impact of real-time management systems, 250–52, 260–61, 262–4 influencing factors and incidents, 53 time considerations, 52–3, 251–2 use of algorithmic approaches, 106, 250–53, 257–8 use of telematics, 94–9, 105–6 see also fleet-management systems vehicle surveillance devices, 252–3 virtual fencing, 78–9 voice-recognition systems, 163–4, 197–8, 203–6 key benefits, 198 Waitrose (UK), market share and turnover, 10 Wal-Mart (US),121, 122, 211

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296

Index

warehousing operations, 42–9, 57–9, 195–206 basic functions and requirements, 195–6 common problems and inefficiencies, 47–9 control systems, 35–6, 57–9 facility types, 43–4 flow of goods, 44–5 order picking technologies, 163–4, 196–8, 203–6 product tracking, 49 quality control and certification, 46–7 retail case studies (Greece), 199–206, 214–24 storage of frozen goods, 214–24 storage of perishable goods, 45–9 use of RFID technologies, 58–9, 60–61, 106, 121–2, 197, 214–24 voice-controlled order picking, 163–4, 197–8, 203–6

Bourlakis_bindex.indd 296

weeding use of robotics, 70 use of wireless sensors, 82 wild foods, harvest regulation, 155 wine production, use of e-business technologies, 172–8 wireless communication technologies, 88, 89–90 value-added applications, 106–7 wireless sensors, 81–2 see also radio frequency identification (RFID); telematics WRAP (Waste Resources Action Programme), 11 Xtra Trade (information exchange system), 36 yield monitors, 68

2/2/2011 10:36:41 AM

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