traceability in fresh food supply chains

Traceability in Fresh Food Supply Chains

Kevin Donck

August 20, 2010

Traceability in Fresh Food Supply Chains

A case study from the meat industry

Master Thesis from the department of Organization and Strategy

Faculty of Economics and Business Administration

University supervisor:

ir. drs. Karin Thomas

Company

Zetes

Company Mentors:

Jeroen Donkers

Jeffrey Verberne

Author:

Kevin Donck

ANR:

876767

Program:

Master Logistics and

Operations Management,

Tilburg University

Word Count:

15,637

Place:

Tilburg

Date:

August 20, 2010

http://www.uvt.nl/

I

Management Summary

Traceability in supply chains is a topic that has been widely debated upon in the academic literature,

especially regarding the food industry. With supply chain performance improvements potential in

more than just product recall situation, but also in organizations’ understanding of their supply chain

and in logistics efficiency, traceability has become essential for businesses. In order to perform

traceability, product identification is necessary. For that purpose, several identification technologies

have been developed. Barcode and radio frequency identification are the most popular in the

academic literature. However, others such as computer vision and voice identification in combination

with barcode have been refined and give ground for the latter to compete with radio frequency

identification.

The issue remaining unsolved is how do traceability and identification technologies contribute to

supply chain performance in the fresh food industry? Especially relevant here is the analysis of what

effects the later technologies have on supply chain performances. For that purpose, the different

technologies recognized, or not, by the academic literature were categorized in two groups. The first

one being barcode in combination with computer vision and voice identification. The second one

being radio frequency identification. Furthermore, the agri-food chain model used by Knura et al.

(2006) is combined with the fresh food supply chain performance indicator framework developed by

Aramyan et al. (2007) in order to provide academic grounds for the analysis of identification

technologies effects on fresh food supply chain performances.

A case study for fresh meat industries is then developed to enable the appropriate evaluation of the

traceability and identification system effects on its supply chains performances. For that purpose, the

agri-food chain model is stripped from any processes that are not related to the meat industry.

As a result, the effects regarding supply chain performance of the two categories of identification

technologies are assessed for each stage and process of the adapted agri-food chain model. Those

effects, evaluated in terms of efficiency, flexibility, responsiveness and food quality, enabled the

development of a multi-modal identification and traceability system that is most appropriate for

each supply chain partners. Furthermore, the multi-modal system is also recognized to steer fresh

food supply chains towards higher performances and reduced labor costs.

II

Preface

I first encountered the topic traceability during the course Supply Chain Collaboration and Advanced

Planning. One of its lectures was dedicated to the necessity to be able to track and trace products in

Agri-food chains, especially for recall purposes.

Building on what I discovered during this lecture, I decided to write my thesis on food supply chains.

Zetes, a company that specialized in the automated identification of goods, gave me the possibility to

do a graduation internship at their Dutch subsidiary in Eindhoven. With the assistance of Jeroen

Donkers and Jeffrey Verberne, my supervisors at the company, I defined a research topic and a

problem statement that would satisfy Zetes’, Tilburg University’s and my own interests. Traceability

in fresh food supply chains is the subject that resulted from matching all those interests.

I would like to take this opportunity to thank all the people who have helped me during this research

project. First of all, I would like to thank Jeroen Donkers and Jeffrey Verberne from Zetes B.V. who

shared their knowledge and time and so supported me during the course of my research. The

feedback you provided me with has been extremely valuable to the elaboration of this thesis.

Secondly, I would like to thank Karin Thomas, my university supervisor, whose help, time and

comments have enabled me to write my thesis in the best possible way.

Thirdly, I would also like to thank Jean-François Jacques for putting me in contact with Zetes and for

his support and feedback.

Fourthly, a special thanks to my parents and grandmother who have always supported and trusted

me. This thesis completes the wonderful opportunity you gave me at having an international

education. Thanks to you I now have all the tools in hand to build my own independent life.

Finally, I would like to thanks Denisse, my girlfriend, for her support during the last three years.

Kevin Donck

III

Table of Content

MANAGEMENT SUMMARY ............................................................................................................................... I

PREFACE ........................................................................................................................................................... II

TABLE OF CONTENT ......................................................................................................................................... III

CHAPTER 1: INTRODUCTION ............................................................................................................................. 1

SECTION 1.1: INTRODUCTION .................................................................................................................................... 1

SECTION 1.2: PROBLEM INDICATION ........................................................................................................................... 1

SECTION 1.3: PROBLEM STATEMENT ........................................................................................................................... 3

SECTION 1.4: RESEARCH QUESTIONS ........................................................................................................................... 3

SECTION 1.5: STRUCTURE OF THE THESIS ...................................................................................................................... 3

CHAPTER 2: THEORETICAL FRAMEWORK .......................................................................................................... 4

SECTION 2.1: INTRODUCTION .................................................................................................................................... 4

SECTION 2.2: SUPPLY CHAIN MANAGEMENT ................................................................................................................ 4

SECTION 2.3: TRACEABILITY ....................................................................................................................................... 5

SECTION 2.4: THE FRESH FOOD SUPPLY CHAIN ............................................................................................................... 7

Section 2.4.1: General agri-food chain ........................................................................................................... 7

Section 2.4.2: Fresh food supply chain performance indicators ..................................................................... 9

SECTION 2.5: INTRODUCTION TO THE FOUR IDENTIFICATION TECHNOLOGIES ..................................................................... 11

Section 2.5.1: Barcode Identification ............................................................................................................ 12

Section 2.5.2: Radio Frequency Identification .............................................................................................. 13

Section 2.5.3: Benefits .................................................................................................................................. 14 Section 2.5.3.1: Barcode Benefits .............................................................................................................................. 15 Section 2.5.3.2: Radio Frequency Benefits................................................................................................................. 15

Section 2.5.4: Challenges and Constraints .................................................................................................... 16 Section 2.5.4.1: Challenges and Constraints of Barcodes .......................................................................................... 16 Section 2.5.4.2: Challenges and Constraint of RFID ................................................................................................... 17

Section 2.5.5: GS 1 – Global Traceability Standards ..................................................................................... 18

SECTION 2.6: CONCLUSION ..................................................................................................................................... 18

CHAPTER 3: RESEARCH METHODOLOGY ......................................................................................................... 20

SECTION 3.1: INTRODUCTION .................................................................................................................................. 20

SECTION 3.2: RESEARCH TYPE .................................................................................................................................. 20

SECTION 3.3: RESEARCH QUALITY............................................................................................................................. 20

Section 3.3.1: Construct Validity ................................................................................................................... 21

Section 3.3.2: Internal validity ...................................................................................................................... 21

Section 3.3.3: External validity ..................................................................................................................... 21

Section 3.3.4: Reliability ............................................................................................................................... 22

SECTION 3.4: PROBLEM STATEMENT QUALITY ............................................................................................................. 22


CHAPTER 4: CASE STUDY ................................................................................................................................ 24


SECTION 4.2: PRESENTATION OF THE CASE STUDY ........................................................................................................ 24

Section 4.2.1: Internal interviews ................................................................................................................. 25

SECTION 4.3: TWO ADDITIONAL IDENTIFICATION TECHNOLOGIES ..................................................................................... 26

Section 4.3.1: Computer Vision Identification .............................................................................................. 26

IV

Section 4.3.2: Voice Identification ................................................................................................................ 28

Section 4.3.3: Technology regrouping .......................................................................................................... 28

SECTION 4.4: RESULTS FROM INTERVIEWS .................................................................................................................. 29

Section 4.4.1: Barcode identification in combination with computer vision and voice identification .......... 29 Section 4.4.1.1: Primary production .......................................................................................................................... 29 Section 4.4.1.2: Slaughtering and Processing ............................................................................................................ 30 Section 4.4.1.3: Wholesale ........................................................................................................................................ 32 Section 4.4.1.4: Retailing ........................................................................................................................................... 34 Section 4.4.1.5: Consumer ......................................................................................................................................... 36

Section 4.4.2: Radio Frequency Identification .............................................................................................. 36 Section 4.4.2.1: Primary production .......................................................................................................................... 36 Section 4.4.2.2: Transport of animals and of processed meat ................................................................................... 38 Section 4.4.2.3: Slaughtering and Processing ............................................................................................................ 39 Section 4.4.2.4: Wholesale ........................................................................................................................................ 41 Section 4.4.2.5: Retailing ........................................................................................................................................... 41 Section 4.4.2.6: Consumer ......................................................................................................................................... 42

SECTION 4.5: TECHNOLOGY BEST FIT ......................................................................................................................... 42


CHAPTER 5: DISCUSSION AND CONCLUSIONS ................................................................................................ 46


SECTION 5.2: FRESH FOOD SUPPLY CHAIN ................................................................................................................... 46

SECTION 5.3: ASSESSMENT OF TRACEABILITY TECHNOLOGY WITH THE FRAMEWORK OF ARAMYAN ET AL. (2007) ..................... 47

SECTION 5.4: LIMITATIONS AND RECOMMENDATIONS .................................................................................................. 48


REFERENCES: ..................................................................................................................................................... I

APPENDICES: ................................................................................................................................................... IV

Appendix 1: Traceability across the supply chain .......................................................................................... IV

Appendix 2: 1D Barcode ................................................................................................................................ IV

Appendix 3: 2D Barcode ................................................................................................................................. V

Appendix 4: Voice head set and belt terminal ................................................................................................ V

Appendix 5: Visidot reader ............................................................................................................................. V

Appendix 6: Single vs two-sided Visidot gate ................................................................................................ VI

Appendix 7: Visidot Director .......................................................................................................................... VI

Appendix 8: Barcode and voice interview table............................................................................................ VII

Appendix 9: Computer vision interview table .............................................................................................. VIII

Appendix 10: Radio frequency interview table .............................................................................................. IX

Appendix 11: Voice terminal combined with finger barcode reader .............................................................. X

Appendix 12: Truck environmental sensor ..................................................................................................... X

Appendix 13: Performance indicator framework, adapted from Aramyan et al. (2007) .............................. XI

Appendix 13 (Continued): Performance indicator framework, adapted from Aramyan et al. (2007) .......... XII

1

Chapter 1: Introduction

Section 1.1: Introduction

This thesis is written as a completion of the master Logistics and Operations Management at the

department of Organization and Strategy of Tilburg University. Its central theme is the traceability of

fresh food products along a supply chain with an emphasis of identification technologies. The first

chapter starts by a problem indication which outlines the symptoms of the issues that are researched

in this thesis. Thereafter, the main question dealt with in the thesis known as the problem statement

is depicted, followed by the research questions which divide the problem statement in a series of

issues that will be subsequently answered to solve the main problem. Finally, the overall structure of

the thesis is outlined.

Section 1.2: Problem indication

Since 2002, the European Union’s Food Law requires that all food and feed businesses implement a

traceability system to enable accurate withdrawals in case of food safety issues (Cox & Piqué I

Champs, 2002). In other words, the law enforces every organization involved in the food industry to

be able to track and trace their products. Fritz and Schiefer (2009) defined tracking as the capability

to identify the precise location of any product at any given point in time, and tracing as the ability to

name the source and the destination of any product at any stage of the supply chain. Furthermore,

these new legal requirements take place in a context where supply chains complexity is increasing,

where the need for information and collaboration across organizational boundaries is seen as a

fundamental condition for long-term competitiveness of a supply network (Bartlett, Julien, & Baines,

2007). Consequently, the discipline of Supply Chain Management (SCM) is also affected by supply

chain complexity. On the one hand, SCM requires organizations to widen the activities that must be

managed while the nature of these activities has become more challenging as a result of shorter

product life cycle, increased product variety and customization levels, and partners that are

becoming more geographically dispersed (Bozarth et al., 2008). On the other hand emerging

information and communication technologies have been supporting closer and more transparent

collaboration between supply chain partners as well as improving the efficiency of the network

operations and the effectiveness of overall customer service (Akkermans et al., 2003). Moreover,

Kemppainen and Vepsäläinen (2003) identified that information technology that enables and creates

transparency will be a precondition for supply chain success in the next decade. Even though

2

ambushed by challenging and complex success requirements, the need for traceability solutions in

the food industry that provide accurate real time data of products along a supply chain has become a

necessity.

The previous paragraph depicts the context in which identification technologies have been evolving.

Traditional ones such as Barcode ID systems have been further refined and new ones such as Voice

ID, Computer Vision ID and Radio Frequency Identification (RFID) systems have been developed.

Although RFID technologies have been gaining momentum in academic literature (Ngai, Moon,

Riggins, & Yi, 2008), Barcode ID technologies continue to be used in practice to support or even

replace the former when not applicable (Véronneau & Roy, 2009). Voice ID and Computer Vision ID

are, on the other hand, identification technologies that were not yet considered and discussed in the

business research literature.

As a result of the wide variety of goods identification solutions, it remains unclear which one of the

latter fits best at each stage of the path followed by a fresh food product within a supply chain.

Furthermore, implementing the appropriate goods identification technology at each stage of a fresh

food supply chain to fullfill the legal requirements has often been disassociated from profitable

supply chain management strategies. However, such an investment has “the potential to improve

supply chain efficiency through integration of traceability with operations management functions”

(Wang, Li, & O’Brien 2009. pp2865).

Through an organic development and through acquisitions, Zetes Industries has been the key player

in the automatic goods identification European market as an independent systems integrator and

solution provider. With experience in retail (e.g. Aldi), manufacturing (e.g. Sony), transport and

logistics (e.g. TNT express), utilities (e.g. Electrabel/Suez) and banking (e.g. Citibank) industries, Zetes

Industries focuses on providing full solutions to supply chains, in order to improve process flows.

Zetes offered me the possibility to conduct research on traceability and identification issues in fresh

food supply chains through a case study on meat supply chains. The supply chain under examination

is essentially based upon the general agri-food chain provided by the Irish food safety authorities,

which is used in academic literature on food quality and safety. The motivation for Zetes to develop

this assignment is to on the one hand, centralize experts’ knowledge on fresh food supply chains and

on the other hand, beneficiate from an academic research that can be presented to external parties.

3

Section 1.3: Problem statement

The problem statement that arises from the above problem indication is:

How can the implementation of goods identification systems contribute to fresh

food supply chains performance?

Section 1.4: Research questions

The problem statement mentioned above is divided in three research questions. The latter form the

structure of the research project and will be subsequently answered to define the ultimate solution

to the problem statement.

1. What are the necessary requirements for the implementation of a goods identification

solution within fresh food supply chains?

2. What type of goods identification systems is most appropriate for each partner of fresh food

supply chains?

3. What effects does the implementation of goods identification systems have on fresh food

supply chains performances?

Section 1.5: Structure of the thesis

After this introductory chapter, the structure of the thesis is depicted as follow. Chapter 2 is the

theoretical framework, where the academic perspective of supply chain management and

traceability as an entire part of supply chain management are first discussed. Thereafter the

currently most used technology, Barcode ID and RFID, for the identification fresh food products in

supply chains are described. Chapter 3 depicts the research methodology that was undertaken to

define the problem statement and to gather qualitative data. The fourth chapter presents the case

study and the results from the internal interviews. The fifth and final chapter discusses the results

and proposes a conclusion to the problem statement.

4

Chapter 2: Theoretical Framework


This chapter starts by a literature review, introducing the concept of supply chain management first

and then of traceability. Thereafter, the theoretical framework of the thesis is presented. Two

distinct parts can here be identified, the first one being the presentation of the general agri-food

chain model and the second one being the explanation of the fresh food supply chain performance

indicators framework. The latter parts provide grounds for the goods identification that fits best each

stage of fresh food supply chains as well as the necessary framework for the evaluation of the

contribution of goods identification on supply chains performance. The theoretical framework is

followed by an introduction to the two main identification technologies in order to enumerate the

necessary requirements for the implementation of a goods identification solution within a meat

supply chain.

Section 2.2: Supply Chain Management

Supply Chain Management (SCM) has been and still is considered by both practitioners and

academics as a major management focus (Wang & Chan, 2009). Furthermore, Brewer and Speh

(2000) recognized that supply chain management is a requisite for organizations seeking to

strengthen their position in the marketplace. In the Netherlands, for example, the commission Van

Laarhoven was appointed on the 1st of November 2007 in order to insure that the country’s

industries would excel and become European leaders in the area of logistics and supply chain

management because of their crucial importance for businesses economic performances. The latter

discipline was defined as:

“the systemic, strategic coordination of the traditional business functions and the tactics

across these business functions within a particular company and across businesses within

the supply chain, for the purposes of improving the long-term performance of the

individual companies and the supply chain as a whole” (Mentzer, William, Keebler,

Soonhong, Nix, & Smith (2001) p.10).

This definition encompasses two aspects that are particularly relevant to this thesis. The first aspect,

‘coordination across business within the supply chain’, emphasizes on need for collaboration and

synchronization between the different organizations and parties involved in a supply chain. Wang et

5

al. (2009) emphasized that traceability systems in the food industry were, in most cases, developed

for individual organizations without taking into account supply chain activities as a whole. The

contrast that lies between the individual traceability system requirements and global supply chain

perspective highlights the fact that synchronization and coordination continue to represent a

challenge for most organizations. The second aspect that is of particular relevancy to this thesis is

‘performance’. Several research (Viaene & Verbeke 1998, Golan et al. 2004, and Schwagele 2005),

have identified the potential for ameliorated performance when managing effectively traceability

practices in supply chains. More specifically, performance improvements were accentuated by lower

inventory levels, rapid detection of issues in manufacturing processes, and increased efficiency of

logistics and distribution processes. This introduction sets supply chain management as the backbone

of the thesis on which a variety of concepts that are discussed below rely upon.

One of the latter concepts, traceability, is described in the next section. Its importance in the food

industry and its potential for supply chain success and competitive advantage are elaborated upon.

Section 2.3: Traceability

The concept of traceability has been at the forefront of academic literature in the last decade, in

food safety and quality as well as in production economics. Traceability in the food industry is

defined by the European Food Safety Authority in association with the International Organization for

Standardization (ISO) 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” (Cox & Piqué I Champs, 2002, L31/8). Two key aspects of

this definition must be emphasized on. The first one, ‘through all stages of production, processing

and distribution’, refers to the scope of the latter definition. This encompasses any phase of the

supply chain, beginning with the importation of the initial production of food up to and including its

sale or supply to the final consumer (Choe et al. 2008). The second key aspect of the former

definition is the ability to trace and follow which implies two distinct capabilities. The ‘tracing’

capability is the ability to name the source of any product at any stage of the supply chain going

backward. The ‘follow’ or ‘tracking’ capability is the ability to identify the precise location of any

product at any given point in time going forward (Bechini et al. 2008). The two latter functions are

graphically represented in figure 1.

6

Figure 1: Typical scenario for a product recall in a supply chain (adapted by Bechini et al. 2008)

As recognized by GS11 – Global Language for Business, traceability in the food industry has for first

priority the protection of consumers through faster and more precise identification of implicated

products. This statement becomes particularly relevant when a food product must be withdrawn

from the supply chain for safety reasons (Global Traceability Standards – GS1). Figure 1, also provides

a typical scenario for a product recall in a supply chain. In this simplified setting, consisting of four

supply chain partners, the existence of a well adapted traceability system permits that the product

withdrawal or recall is limited to the items that are really infected, which is essential to minimize

recovery cost (Bechini et al. 2008).

Fritz and Schiefer (2009) identified two different types of traceability: internal and external. Internal

traceability refers to activities confined to an organization. Whereas external traceability refers

practices that reach beyond the organization’s border. The latter involves the necessity for

agreements and coordination between the different partners involved which as discussed in the

previous section is a difficult state to reach. Appendix 1 provides a graphical representation of the

latter segmentation of the different types of traceability.

With the purpose of demonstrating that traceability systems are more than just mechanisms

imposed by governments to insure food safety, Alfaro and Rábade (2009) identified a research

1 GS1 is a leading global organization dedicated to the design and implementation of global standards and

solutions to improve the efficiency and visibility of supply and demand chains globally and across sectors. Source : http://www.gs1.org/about/overview

7

literature stream that promoted traceability as a tool for differentiation where emphasis is put on

the improvement of organizations’ understanding of their supply chain and on the potential to

reinforce the degree of coordination in the supply chain. Furthermore, this latter stream further

described track and trace capacities as a practice with the potential to increase logistics efficiency

and supply chain performance. Now that the concept of traceability was described and its potential

for supply chain success and competitive advantage was outlined, the theoretical framework of the

thesis is presented in the next section.

Section 2.4: The fresh food supply chain

In this section, a general agri-food model issued in the food quality academic literature and a supply

chain performance indicators framework issued in the academic literature of supply chain

management come together to form the theoretical framework. This framework will be the guideline

for the assessment of the effects of traceability enabling technologies (identification technologies) on

supply chain performance. The two following sections describe and elaborate on the previously

discussed model and framework.

Section 2.4.1: General agri-food chain

As previously mentioned, the food industry is facing increasingly complex competitive and global

markets. Furthermore, the wide scope of different actors involved in fresh food supply chains

deepens this latter trend. According to Knura et al. (2006), agricultural supply chains are

characterized by a segregated structure. That is, organizations are specialized on basis of the

production segment they are involved in. This latter aspect is reflected in the general food supply

chain that is depicted below.

The Food Safety Authority of Ireland proposed a general food supply chain model (figure 2) that

offers a stable to table approach. The latter model was used in food quality and safety academic

literature by Knura et al (2006).

8

This general fresh food framework is of particular interest because it serves as a basis for the

performance analysis of the different supply chain actors as well as for a supply chain as a whole. It is

valid for meat, vegetables and fish supply chains. One essential characteristics of model is that it

encompasses all stages in food production going from ‘FARM’ to ‘FORK’ which enables this model to

comply with the European Food Law since it fulfills the ‘all stages of productions’ requirement.

The stages of agri-food supply chain depicted above in figure 2 are described below:

1. The actor of the first stage of the agri-food supply chain is the animal feed, the fertilizer or the

chemical manufacturer. Even thought, it is recognized as a crucial stage for full traceability to

ensure food quality and security (Food Safety Authority, 2004), this thesis concentrates on the

traceability from primary production to consumer (FARM to FORK). The first stage will

therefore not be further discussed in this research.

2. The next stage of the general framework is concerned with primary production which

represents in the meat industry the farm where the animal is bred, where the vegetables are

1

Figure 2: Agri-food chain: The stages in food production (Food Safety, 2004)

Animal feed/fertilizer/ chemical product manufacturer

Primary production (FARM) e.g. planting, breeding, rearing, growing, dairy

production, fish production

Transport of animals or of raw products

Slaughtering and processing

Transport of processed products

Wholesale


Retailing e.g. restaurants, catering services, food stores

Consumer (FORK)

2

3

4

5

6

7

8

9

9

gown or where the fish are reared. Although the term primary production is often associated

to further activities such as the primary processing of animal product, it is here kept to its basic

signification. According to Luning and Marcelis (2009), who discussed the factors affecting

product quality in food supply chain, this first stage processes comprises animal breeding, fish

rearing and vegetable growing management as well as the order selection for transport to

slaughtering and processing stage.

3. The following stage is the transport of animals, fish or vegetables to the slaughtering and/or

processing stage.

4. Thereafter, the slaughtering and processing stage of the agri-food supply chain is responsible

for the slaughter of the animal or fish and the processing vegetables. Subsequently, the

processing of the carcasses into specific meat or fish cuts. Furthermore, the resulting meat,

fish and vegetables cuts need to be packed before being pre-transport stored.

5. Subsequently, the processed meat, fish or vegetables are transported to wholesale points.

6. At the wholesale stage extensive warehousing and inventory management activities are done.

The processes recognized at this stage are order reception, put away, order mixing, order

preparation and shipping verification.

7. The packaged products are finally being transported to retailers.

8. The retailing stage generally represents food stores, catering services or restaurants and is

commonly known as the last stage before consumer purchase. For the purpose of this thesis

the retailing stage will be solely represented by supermarkets. The related processes where

identification is necessary are order receptions and shelf replenishments.

9. The final stage, the consumer also represented as FORK in the agri-food supply chain. As this

stage is the final one of the agri-food chain model it also serves as a conclusion for the

assessment of the analyzed identification technology.

The previously described model of agri-food supply chain is the basic framework that is referred to all

along the course of this thesis. In the next section, a performance indicator framework used for the

assessment of the contribution of traceability and identification technology is presented.

Section 2.4.2: Fresh food supply chain performance indicators

As the aim of this research is to assess if the traceability and identification solutions can contribute to

supply chain performance, an adequate supply chain performance measurement framework must be

presented. The framework should permit each partner of the supply chain to assess its own

10

performance within its boundaries, but also provide a global chain perspective to enable the

evaluation of the supply chain as a whole.

Aramyan et al. (2007) developed a framework resulting from a literature review regrouping key

performance indicators from academic papers in logistics and manufacturing. An overview of the

framework including the definitions and the measure of the indicators can be found in appendix 13.

The authors identified seven reasons for the complexity and the specificity of measuring

performance of agri-food supply chains:

1. Perishability and shelf life constraints of raw materials and products;

2. Long production throughput time;

3. Seasonality in production;

4. Physical product features such as taste, odor, appearance and color;

5. Requires conditioned transportation and storage;

6. Product safety issues;

7. Natural conditions affect the quantity and quality of farm products

The latter specificity and complexity are what differentiate fresh food supply chains from any other

one.

After having incorporated the latter complexities to general supply chains, Aramyan et al. (2007)

proposed the following four main categories for agri-food supply chain performance indicators

(Appendix 13)

1. Efficiency: which is responsible for the measurement of how well the resources are utilized.

2. Flexibility: which is responsible for the measurement of how well supply chains can cope with

a changing environment and with extraordinary customer service request.

3. Responsiveness: which is responsible for measuring the lead-time between requested

products and their delivery.

4. Food Quality: which is responsible for the measurement of product safety and health,

sensory properties and shelf life, and product reliability and convenience.

An essential attribute of the latter performance measurement framework is that it provides

indicators both for the organizational level and for the supply chain level. That is, each fresh food

supply chain partner can adjust the different categories (efficiency, flexibility, responsiveness and

food quality) of its own framework based on its own organizational objectives while maintaining the

overall picture of the supply chain performance. As a result both organizational level and supply

chain level are represented in the performance framework.

11

The assembly of the general model of agri-food supply chain with the agri-food supply chain

performance framework provides the ground to analyze the effect of the different traceability

technologies on supply chain performances. As one of the aims of the research is to identify what

identification technology fits best each stage and partner of the supply chain, regrouping and

opposing them in one framework provides the rationale for an appropriate comparison.

Two main technologies for the identification of products are recognized by the academic literature.

These are Barcode ID and RFID. They are presented and discussed in the next section.

Section 2.5: Introduction to the four Identification Technologies

Barcode ID and RFID are currently the two main technologies used for the identification of products

in supply chain wide traceability systems (Youssef et al. 2007, Lee et al. 2010). Even though, an

extensive amount of literature has been published in the last five years on RFID, an appropriate

comparison of the effects of the latter with the rest of the identification technologies on supply chain

performance is still missing. Traceability, RFID and Barcode ID in supply chain management context

have been at the forefront of academic literature in the last decade (see table 1). The following table

illustrates some of the articles resulting for searches for traceability, track and trace, radio frequency

identification and barcode on Science Direct and Elsevier.

Research Topic Authors Date

Traceability in Supply Chains Schwägele 2005

Regattieri et al. 2007

Kelpouris et al. 2007

Alfaro et al. 2008

Montari et al. 2008

Bechini et al. 2008

Fritz et al. 2008

Choe et al. 2009

Wang et al. 2009

Shanahan et al. 2009

Holmström et al. 2010

Wang et al. 2010

Table 1: Traceability, RFID and Barcode in the academic literature

12

Research Topic Authors Date

RFID in Supply Chains Fleisch et al. 2004

Angeles 2005

Twist 2005

Attaran 2007

Kelpouris et al. 2007

Sellitto et al. 2007

Ngaï et al. 2008

Véronneau et al. 2009

Lee et al. 2010

Barcode in Supply Chains Manthou et al. 2001

McFarlae et al. 2003

Youssef et al. 2007

Table 1 (continued): Traceability, RFID and Barcode in the academic literature

In order to provide an academic answer to the research question regarding the requirements of

goods identification technology, the two main identification technologies used for the identification

of fresh food products in supply chain wide traceability systems are discussed in the following

section, starting with barcode identification.

Section 2.5.1: Barcode Identification

Barcodes are the most familiar data capture technologies (Youssef & Salem, 2007). Present on the

majority of merchandise packaging in supermarkets since the early 1980’s, they generally provide

specific information about the product, its characteristics, its price and its origin. However, barcode

are also used throughout organizations to improve accuracy of information as well as to accelerate

the diffusion of data (Manthou & Vlachopoulou, 2001). Sutton (2002) defined barcodes as visual

format on a surface, graphically representing information that is machine readable. There are

nowadays two main forms of barcodes. Initially, barcode exclusively stored data in a visual format

that was represented by the width and the spacing of parallel lines (e.g. appendix 2). These types of

barcodes have been categorized as one dimensional (1D) since the extent of the height of each of the

parallel lines does not affect the storing capacity of the barcode. It only increases redundancy which

aims at increasing reliability when the barcode is damaged. 1D barcodes can hold up to 12 characters

of information. However, two dimensional (2D) barcodes also exist (e.g. appendix 3). The latter, as

opposed to 1D barcodes, make use of the vertical dimension and contain more data representation

capability. Another particularity of 2D is its capacity for error correction. That is, even if a major part

of the barcode was for any type of reason destroyed the encoded data can still be retrieved thanks to

error correction encrypted in the matrix.

13

Originally, data encrypted in barcodes was solely retrieved using manually handled terminals.

However, nowadays information retrieval of barcodes can also be done automatically for which no

human intervention is needed. The latter usually operate on conveyor belt and are capable of

‘stream scanning’ barcoded products (scanning product that are following each other on a conveyor

belt at high speed).

Coming back on the seven complexities for measuring performance of agri-food supply chains

discussed in section 2.4.2, automated barcode identification as defined above, can contribute to a

reduction of pre-shipping throughput time and therefore contributing positively to shelf life

constraints. Furthermore, limited specification about the product characteristics can be incorporated

in barcodes. However, if one wants to add new information about product characteristics and

environment a new tag would have to be applied which represent a considerable limitation.

In the following section, the second major traceability technology, RFID is presented.

Section 2.5.2: Radio Frequency Identification

Radio Frequency identification has emerged in the research literature in the last decade because of

its potential, as an inter-organizational system, for improvement of supply chain processes efficiency

(Ngai et al. 2008). The proliferation of RFID in academic literature recently pushed the Production

and Operation Management Journal and the International Journal of Production Economics to

dedicate special issues on the matter.

In practice, RFID has also been the center of attention. Large retailing organizations such as Wal-

Mart, Tesco and Target have been the initiators of the experimentation of RFID. Those retailers have

leveraged their most important suppliers (e.g. Procter and Gamble, Kimberly-Clark, and Unilever) to

implement RFID at the pallet and case level for their products in order to stream line supply chain

processes (Sellitto, Burgess, & Hawking, 2007; Lee & Lee, 2010).

RFID is not a new technology. It was first developed for military purposes during the Second World

War. Nowadays, RFID is defined as “e-tagging technology that can be used to provide electronic

identity to any object” (Attaran, 2007, pp 249). This identification technology provides a solution to

the major constraint of barcode identification technology. That is, for barcoding, the scanner must be

able to ‘see’ the barcode to be able to read it. RFID on the other hand does not require the tag to be

in line of sight to be able to read it and store the information is comprises (Attaran, 2007). According

to Li, Visich, Khumawala & Zhang (2006), all RFID systems consist of three main elements:

1. an RFID tag, situated on the item to be identified and carries the data in the RFID system;

14

2. an RFID reader, which has to capability to read data from and write data on an RFID tag;

3. a data base which connect records with data collected by the RFID readers.

RFID tags can be further specified and categorized in three types that are described in descending

price order. The first one, active tags, are characterized by the fact that they transmit a signal to a

reader thanks to a battery. The second one, semi-passive tags, are characterized by the fact that they

are powered by an internal battery and by electromagnetic waves. Furthermore, the latter type of

RFID tags can monitor environmental variables which are particularly relevant in the context of fresh

food traceability. The third and final one, passive tags, can only be read when passing through an

electromagnetic field because it does not contain a battery which also makes it the cheapest

alternative of the three RFID tags types (Li et al. 2006).

Both Barcode and RFID technologies implementation in supply chains are characterized by potential

benefits and constraints that are discussed in the following two sections.

Section 2.5.3: Benefits

Several advantages of using Barcode ID or RFID for the purpose of traceability have been identified in

the academic literature. The latter are summed up in table 2 providing the reader with a graphical

representation to rely upon. The benefits of barcode identification are discussed first following by

the ones for RFID.

Barcode Radio Frequency

Inventory control and management improvement

Improved inventory monitoring and tracking

Increase organization's process efficiency Potential for process improvement

Availability of improved data for consumer market research

Update information on real-time basis

Buyers' and seller's communication enhancement

Enhanced collaboration between supply chain partners

Increase profitability of the organization Reducing the cost of defective items reaching consumers

Flexibility to changing customer requirements Potential for reduction of labor costs

Low tag price Enhanced cross docking operations

Speed of identification Improved lead time management

Accuracy of identification Improved accuracy and visibility of inventory data throughout the supply chain processes

Increased competitiveness of the organization Table 2: Benefits of Barcode and Radio Frequency Identification

15

Section 2.5.3.1: Barcode Benefits

Youssef et al. (2007) name three essential benefits of barcodes: speed, accuracy of identification

processes and the very low price of barcode tags. Furthermore, other benefits resulting from the

implementation of barcode systems in supply chain are also identified by Manthou and Vlachopoulou

(2001). Those are:

Inventory control and management improvement

Increase organization’s process efficiency

Availability of improved data for consumer market research

Buyer’s and seller’s communication enhancement

Increase profitability of the organization

Increase the competitiveness of the organization

Flexibility to changing customer requirements

Those benefits were identified and enumerated in a context where identification was previously

done by manual encoding of data via keyboards where regular human errors were obviously

inevitable. A last benefit that is further described when discussing the constraints of RFID (Section

2.5.4.2) is the fact that barcodes tags are considerably cheaper than RIFD ones. In a context where

another technology (RFID) with different attributes and capabilities is available several constraints

arise with the use of barcodes. Those are discussed in section 2.5.4 along with the ones for RFID.

Section 2.5.3.2: Radio Frequency Benefits

Different academic literature from operations, supply chain management and information systems

research areas have been discussing the potential benefits of RFID. Lee and Lee (2010) conducted a

literature review and listed five essential benefits:

Improved accuracy and visibility of inventory data throughout the supply chain processes

Improved lead time management

Enhanced cross docking operations

Improved inventory monitoring and tracking

Reducing the cost of defective items reaching consumers

Potential for reduction of labor costs

Furthermore, Shanahan et al. (2008) identified the potential for reduction of labor costs due to the

suppression of human intervention in the item identification process and Tzeng et al. (2008)

recognized the potential of RFID to update information on a real-time basis as a benefit.

16

Along with its potential benefits resulting from an adequate implementation, RFID is ambushed by

several challenges and limitations that are nowadays still affecting it progression as the dream

identification technology. Those are presented in the next section.

Section 2.5.4: Challenges and Constraints

In this section, the challenges and constraints that identification technology still has to overcome are

discussed. As for section 2.5.3, a table summing up the different limitation of Barcode ID and RFID is

first outlined.

Barcode Radio Frequency

Scanner must be placed in distance close to zero from barcode to retrieve information

High cost of implementation

Limited capacity of information storage Data management due to high volume

Low resistance to environmental constraints. Physical environmental constraints

Low operational flexibility Globally interoperable standardization problem

Need for new tag when up-dating information Varying tag failure rate

Need for RFID trained professionals

Need for management commitment

RFID is not necessarily used by everyone

Table 3: Challenges and Constraints of Barcode and Radio Frequency Identification

The next two subsections discuss the challenges and constraints outlined in the above table for the

two main identification technologies.

Section 2.5.4.1: Challenges and Constraints of Barcodes

Even though barcode identification has been used for over a decade, it is still faced with some

challenges and constraints. As recognized by Youssef et al. (2007), a major constraint of barcode

technology lies in the retrieval of its information. Information enclosed in barcodes can be retrieved

with the use of optical scanners or when scanned from an image. A major constraint of optical

scanners is that they must be placed in a close to zero distance from the barcode in order to be able

to read it. This may result in two types of issues. Firstly, inspection difficulty since the human

operator of the barcode reader or has to manipulate inconveniently either the sensor or the product.

This subsequently results in an obvious time loss and decrease in efficiency (Youssef et al. 2007).

Secondly, because of human operator inaccuracy when scanning manually, barcode tagged product

may have been forgotten (de Kok, van Donselaar & van Woensel, 2007). For the two latter motives,

the human operator and most specifically the manually handled barcode reader must be removed

17

from the process in order to increase efficiency, which ultimately will have a positive effect on the

durability of bar-coding as an identification technology.

Another type of constraint of barcode technology recognized by Attaran (2007) is its low resistance

to environmental conditions such as dirt, temperatures, humidity or other hazardous contaminations

that result in the incapacity of the barcode reader to scan the tag.

Section 2.5.4.2: Challenges and Constraint of RFID

Even though RFID offers a great potential for processes improvement in a supply chain, its adoption

is faced with a number of issues and challenges (Ngai, 2009). The latter are listed and described

below:

Globally interoperable standardization problem: As a result of the use of two different

standards, namely: the International Standard Organization (ISO) and the Electronic Product

Code (EPC), there a lack of inter-operability between the different applications or devices. A

global adoption of standards for RFID would result, according to Ngai (2009), in the

acceleration of the adoption of RFID.

Environment: RFID tags can be by two environmental factors. The first one, liquids make data

capture difficult because the liquid absorbs the emitted signals. The second one is the

presence close to the tag or the receiver of other equipment that also emit frequencies such

as mobile phones.

Data management: The high volume of data resulting from the deployment of RFID must be

supported by a robust data management system to handle the quantity of information and

to filter the latter into relevant information.

Tag Failure Rate: The report of Deavours (2005) revealed that non-performing tags statistics

could vary between 0 and 19 percent. As a consequence, some items may not be scanned

which results in missing of false information that needs to be rectified.

RFID expertise for deployment: The lack of trained professionals in RFID technologies is

considered by multiple organizations as one of the major issues faced when adopting or

implementing RFID.

Cost challenges: Return On Investment (ROI) for RFID technology has been and still is a major

issue faced by organizations because of the high cost of implementation.

Management commitment: Tightly associated with the previous issue, because of the high

cost and the difficulty to prove positive ROI, it is complicated to obtain senior management

commitment for the adoption of RFID as an identification technology.

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Dual system: Since all partners of a supply chain do not necessarily use RFID, having to use a

dual system that recognizes not only RFID but also barcode represents an additional cost.

The previously stated issues and challenges put lights on the pitfalls to avoid and on limitations of

RFID. The next section discusses global standards that aim at providing industry standards for

barcode and RFID technology.

Section 2.5.5: GS 1 – Global Traceability Standards

In order to support the different actors involved in supply chains, there is a strong need for global

standards for the encryption of any barcode or RFID tag. As discussed in section 2.3, food traceability

is set as a requirement by governmental institutions but can also be attractive for the purpose of

increase competitiveness and profitability of supply chains. However, one can understand the need

for a global standard for the encoding of data in barcodes. Global standards are the basis for

comprehensible communication, information and data exchange between organizations. If each

business would use its own way of encoding barcodes, how could buyers and seller communication

be possible? Having a global standard on bar-coding enhances supply chain visibility and enables

businesses to efficiently manage their supply chains by enabling them to communicate with each

other (GS1, 2010). GS1 standards are the most widely used for barcodes.

As for barcodes, GS1 also developed standards for RFID, which provide the same advantages as

mentioned for barcode. However, on top of that, EPC’s encoded tag give the exact information of

what the item is but also where it is now and where it has been before to the operator that reads it.

This enables an even more accurate supply chain visibility as well as real-time data. Furthermore, EPC

collected data which are passed to and shared through the EPC global network enable authorized

partners to retrieve logistical information (Bottani & Rizzi, 2008). The latter events have the potential

to considerably improve traceability and supply chain visibility.

The next section concludes on this second chapter covering the theoretical framework of the thesis.

Section 2.6: Conclusion

The chapter covering the theoretical framework first provided academic rationale for the choice of

fresh food supply chain model followed by a performance indicator framework that enables

assessment of each of its stages and processes. Furthermore, the requirements of traceability were

19

outlined. Thereafter, the presentation of the two goods identification technologies recognized and

researched in the academic literature enlightened the reader necessary implementation

requirements from an academic perspective.

The following chapter presents the methodology that was applied during the course of the research

needed for the elaboration of the thesis.

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Chapter 3: Research Methodology


The research methodology chapter aims at certifying the grounds of the research objective and at

confirming the process undertaken to solve the problem statement. An adequate description and

justification of the methodology used to conduct the research is therefore needed. The description of

the way in which the research was conducted does not solely provide grounds for justification but

also grounds for judging research quality.

Section 3.2: Research Type

Saunders et al. (2009) identified six different types of researches that could be used when

undertaking a research project. Those are: experiment, survey, case study, grounded theory,

ethnography and action research. The type of research that was conducted for the purpose of this

thesis is a case study. A case study is an empirical inquiry that investigates a contemporary

phenomenon within its real-life context (Yin, 2003). In this case, the contemporary phenomenon is

the application of traceability identification technology in meat supply chains. The meat industry was

chosen because of Zetes experts’ knowledge of slaughtering and processing practices. The real-life

context refers to Zetes as an organization that designs, develops and delivers traceability and

identification solutions for supply chains. The research focuses on the identification technologies

effects on supply chain performance. Furthermore, the research type can be further specified into an

explanatory case study which establishes and explain causal relationships between variables. The

justification for this segmentation is that the thesis aims at explaining what effects identification

technologies have on supply chain performance.

Section 3.3: Research Quality

As outlined in the introduction of this chapter, methodology provides grounds for judging the quality

of the research. According to Yin (2003), four criteria are commonly used to establish the quality of

any empirical social research:

Construct validity: which examines the correctness of operational measures.

Internal validity: which distinguishes causal relationships from spurious relationships

21

External validity: which establishes to what extent the findings of a study can be generalized.

Reliability: which establishes the extent to which the study can be repeated and obtain the

same results.

The next four sub-sections section will therefore, for each one of the four criteria, provide proof of

research quality.

Section 3.3.1: Construct Validity

The criterion ‘construct validity’ assesses the correctness of the translation of the theory into

operational measures. For that purpose, the theoretical framework was derived from the research

questions and the problem statement. Furthermore, when collecting data, multiple sources of

evidence through multiple interviews were conducted as recommended by Yin (2003).

The types of interviews that were conducted were semi-structured, allowing for flexibility in the pre-

defined framework and enabling new questions to be brought up. Those type of interviews are

according to Davis (2004) best suited to explanatory research study because their flexible nature that

allows in-depth understanding of the subject of interview. The interviews enabled the collection of

primary data based on qualitative research. Qualitative research entails in-depth analyses of a few

observations which involve semi-structure questioning of the interviewees (Davis, 2004). The

methodology theory discussed in this section was applied selecting interviewees and conducting the

interviews. Furthermore, after the results and data were collected, additional confirmations of their

accuracy was performed by presenting the findings to one of the interviewees.

Section 3.3.2: Internal validity

Internal validity is the inference that a particular event resulted from an earlier occurrence (Davis,

2004). In order to maximize internal validity, interviews were done at several points in time and with

several interviewees as detailed in the previous section. This enables the opposition from rival

explanations to the same question when analyzing the outcomes of the conducted interviews.

Section 3.3.3: External validity

This third criterion assesses the generalizability of the findings of the research. The theoretical

framework clearly defines the scope of the research, limiting it to the fresh food industry.

Furthermore, the agri-food chain model developed at the University of Wageningen focuses on the

22

Netherlands and particularly on the retailing stage that is characterized by very little warehousing

activities in comparison to other European countries. The aim is the generalizability of the research

to fresh food supply chains in the same country. The objective of the case study presented in the

next chapter, is to generalize its findings to all fresh food supply chains.

Section 3.3.4: Reliability

This fourth and final research criterion provides grounds to assess reliability. That is “if a later

investigator followed exactly the same procedures as described by an earlier investigator and

conducted the same case study all over again, the later investigator should arrive to the same

findings and conclusion” (Davis, 2004, pp 36). For that purpose, the research methodology outlined

in this chapter was clearly described and as for the external reliability section, the clearly defined

scope of the research provides ground for the quality of the research.

Section 3.4: Problem statement quality

The problem statement was developed on basis of two essential aspects. The first one being the

disassociation of traceability systems with supply chain performance. Wang et al. (2009) recognized

that the development of a traceability system was frequently separated from profitable supply chain

management strategies. This ambiguity arising from businesses and emerging in the International

Journal of Production Research shaped this thesis’ problem statement. The second aspect was the

gap between the available identification technologies for traceability and the ones discussed in

operation academic literature. Researches from Lee et al. (2010), Véronneau et al. (2009), Ngaï et al.

(2008), Sellitto et al. (2007) and Youssef et al. (2007) focused on comparing RFID with Barcode ID in

its most basic format or solely praising the benefits of radio frequency while also naming the

challenges still to be overcome by the latter technology. Therefore opposing all the identification

technologies currently available on the market and analyzing there potential for supply chain

performance gives the opportunity to fill the gap discussed above. The two essential aspects

described above based on a disassociation and a gap identified by academic literature provide the

base for the quality of the problem statement of the thesis.

This final section closes the research methodology chapter that aims at outlining the processes

followed when conducting the research and providing grounds for research quality.

23


The third chapter main objective is to provide methodological rationale for the conducted research

aiming at solving the problem statement. Basing the research methodology on the four criteria

identified by Yin (2003) for the establishment of the quality of any empirical social research, provides

justification for the academic and scientific value of the thesis. The following chapter presents the

case study and the results from the interviews conduct with the traceability and identification

experts.

24

Chapter 4: Case Study


The fourth chapter of this thesis is first responsible for the explanation of the case study used to

assess how traceability and identification technologies contribute to fresh food supply chain

performance. Thereafter, the findings of the conducted interviews are presented. Furthermore, the

chapter provides answers for the research question regarding which technology is most appropriate

for each stage and process of fresh food supply chains. Finally, the effects of the implementation of

goods identification technology , with respect to supply chain performances, are assessed and

discussed.

In the next section the case study on traceability in the meat industry as well as the methodology

regarding the internal experts interviews are presented.

Section 4.2: Presentation of the case study

Zetes is active as a designer and developer of traceability and identification technology in multiple

industries as outlined in section 1.2. Zetes offers four types of identification systems: Barcodes, RF ID,

Voice ID and Computer Vision ID. Barcode ID and RFID have been discussed extensively in the

academic literature and therefore presented in the next section. Voice ID and Computer Vision ID

have not been discussed and are therefore presented here, based on information derived at Zetes.

The organization is particularly interested in possbilities of implementing their identification systems

in the meat industry. Eventhough, traceability is a legal requirement in food supply chains,

organizations having to make a decision on which identification to choose must be aware of what

each technology can and can’t do to support their logistical and operational processes.

The general agri-food chain discussed in the second chapter is here adapted and stripped to solely

encompass activities related to the meat industry (Figure 3). As such, it gives an academical base for

the case study.

25

The reason for this focus is that the research and its related interviews were performed for fresh

meat supply chains.

The rationale behind the interviews conducted with the experts of Zetes is depicted below.

Section 4.2.1: Internal interviews

Over the course of a month, seven interviews were conducted with experts from the Zetes group.

The distribution and division of the identification technologies was allocated according to the

different area of expertise of the interviewees. Three distinct areas can be identified:

1. Manually handled barcode, automated barcode and voice identification(Appendix 8)

2. Computer vision identification (Appendix 9)

3. Radio frequency identification (Appendix 10)

Three frameworks were developed on basis of the agri-food chain of the Irish Food Safety Institutions

(2004) and the performance indicator framework of Aramyan et al. (2007) to fit the three distinct

areas identified above. The first one is used to analyze the effects of manually handled barcode,

automated barcode and voice identification of supply chain performance (Appendix 8). The second

one focuses solely on the effects of computer vision identification (Appendix 9). The third and final

Primary production (FARM) e.g. breeding

Transport of animals

Slaughtering and processing


Wholesale


Retailing e.g. restaurants, food stores

Consumer (FORK)

1

2

3

4

5

6

7

8

Figure 3: Adapted agri-food chain: The stage in meat production (Food Safety, 2004)

26

one focuses on RFID (Appendix 10). The latter distribution was done according to the three pole of

expertise from the interviewees and is further discussed in the next chapter.

For all of the three expertise area, the interviewees were selected on basis of an acute knowledge of

the technology(ies) combined with the experience of implementing them at the client of Zetes.

Furthermore, due to the specificity of the technology, interviewees were also selected on basis of

their involvement in the business processes in order to insure that the answer would remain

operationally oriented and not solely information technology oriented. To insure reliability of the

data collected, at least two different interviews with two different experts were conducted for each

proficiency area. The overlapping data is confirmed whereas the rest are reconsidered, further

questioned with the area experts.

The following section discusses the two additional identification technologies, which have not been

yet discussed in the operational and business academic literature.

Section 4.3: Two additional identification technologies

Section 4.3.1: Computer Vision Identification

Computer vision identification is the first of the two additional technology used for the traceability of

products that is introduced in this thesis. Several attempts of solutions to the major constraint posed

by the barcode laser readers with the use of Computer Vision Identification (Computer Vision ID)

system have already been discussed in the research literature (Chen, Birk, and Kelley (1980);

Vermeyen, Van Gool, Vuylsteke, and Oosterlink (1986); Change, Pan, and Goldman (1987); Elliot and

Griffiths (1990); Al-kindi, Baul, and Gill (1992); Ravichandran and Casasent (1994)). However, as

recognized by Youssef and et al. (2007), the latter technology never managed to emerge as a

potential alternative to barcode scanner. The reasons for it are the long processing time, the

extremely large memory space for pre-stored feature patterns, and the tedious calibration and image

distortion. For the latter reasons, Computer Vision ID was never used in practice. That is, up to now.

ImageID, a subsidiary of the Zetes Group, developed a high speed, large field automatic identification

and data capture system called Visidot. This section will provide a more insight on what is the

Computer Vision ID system developed by ImageID and on how it operates.

The Computer Vision ID system developed by ImageID is composed of hardware units and a PC-based

processing unit. The hardware units called Visidot reader (Appendix 5) which is essentially industrial

high resolution capturing devices mounted on a pole. Depending on the complexity of the

27

configuration of the pallets a single or a two-sided gate is used. Single-sided gates are characterized

by one single Visidot reader whereas two-sided gates have two (Appendix 6). Those hardware units,

with software assistance, are capable of, on a single pallet, simultaneously scanning hundreds of

tagged product (1D or 2D barcodes) in one pass. The latter process is described in the next

paragraph.

Once the pallet is in place on a rotating platform, which enables a 360 degree perspective, the

Visidot reader initiates the image capture of the entire pallet filled with tagged items. The process

can take place on stationary as well as on moving assets and identifies the tags regardless of their

orientation and location. Thereafter, the captured images are firstly processed and decoded.

Secondly, the decoded data are combined and the duplicated data from overlapping captures are

eliminated. Finally, the results and there spatial coordinates on the pallet are sent in XML files to a

business application called Visidot Director which can handle one or more gates (Appendix 7). The

entire process is achieved in less than 5 seconds.

The Visidot Director software provides its operator with a set of six the tools and information needed

to avoid defect or discrepancies.

1. Verification tool: makes sure that requirements in weight, expiration dates, batch size and serial

numbers are validated.

2. Detection of Unlabeled Asset’s Location (DUAL) tool: which has the ability to determine the type

and even is some case the content of unlabeled items on a pallet.

3. Production sequencing tool: makes sure that the sequencing of the labeled parts arrive at the

assembly line in the adequate order, which eliminates the high costs resulting from bottlenecks.

4. Shipping verification tool: verifies that the actual pallet that is going to be shipped corresponds

with the actual order of the customer.

5. Image bank tool: can be used as a proof for claims and charge backs of damaged, missing or

incorrect items.

6. Multi-site logistics: provides a real-time global view of the status of the orders and shipments at

graphically dispersed sites.

The set of tools and information presented above to avoid defects closes the theoretical framework

chapter. Supply chain management was first presented as the backbone concept of the thesis, where

traceability and the four identification technologies rely upon. Furthermore, a general framework for

meat supply chain was presented and a corresponding supply chain performance indicator

framework was outlined. The association of the former and the later provide grounds for the

assessment of the impact of traceability identification technology on supply chain performance.

28

The next sub-section discusses the last of the identification technologies presented in this thesis.

Section 4.3.2: Voice Identification

Even though, Voice Identification (Voice ID) technology has been gaining momentum in warehousing

and inventory management, its coverage in business academic literature is rather limited. It is

however used in several industries (food, retailing and particularly distribution logistics) and has for

primary objective to increasing accuracy and productivity in order picking processes. The latter

technology proposes an alternative and/or an extra function to barcode retrieval technology.

Voice ID technology is based on speech synthesis and recognition. It is composed of a head set and a

voice terminal worn by the user on the belt (appendix 4) which communicates with a host control

system. The host control system which is integrated in the warehouse management system (WMS),

is typically used for order picking activities. The host control system first directs the operator to the

location of the product to be retrieved providing him with information of the raw and precise

location in the raw (e.g. RAW 12, COLLUMN 6, PRODUCT 24). In case the operator is located at the

right point the host control system states the amount of products that have to be picked (e.g. PICK

5). Finally the operator vocally confirms the picked order the ensure reliability (e.g. PICKED 5) before

being appointed to the next task. In the case the operator misunderstood the location the system

automatically detects it and redirects him to the appropriate location.

The primary asset of Voice ID technology is that the operator is working ‘hands free and eyes free’,

allowing him to solely perform the order picking tasks and relocate himself to the next activity to be

performed. This system therefore provides a novel solution to the warehousing academic literature

that has been focusing on minimizing elapsed time during order picking activities (Chen et al, 2010).

Section 4.3.3: Technology regrouping

The four different identification technologies, that have been reviewed and discussed during the

interviews, are regrouped into two categories:

1. Barcode identification in combination with computer vision and voice identification. Although,

the latter technologies were presented separately in the theoretical framework, they are all

essentially retrieving information encoded in barcodes. Adding the latter technologies to

barcode, gives it the tools to compete with RFID. This new segmentation also permits the

comparison at each of stage of the agri-food supply chain that is done in chapter 5.

2. Radio frequency identification

29

Section 4.4: Results from interviews

The results are here presented for each stages of the agri-food chain model. Two subsections

reproduce the division of the identification technologies discussed in the previous section. Barcode,

computer vision and voice identification will be discussed first. Subsequently, findings of radio

frequency identification are discussed.

Two important aspects regarding fresh food performance indicator framework the adapted agri-food

chain must be first mentioned. The first one concerns the ‘flexibility’ assessment criteria. All

interviewees recognized the need for further specifying flexibility in terms of operability. That is, the

level of ease the information can be retrieved with barcode readers and the associated handling that

must be undertaken to achieve the process. Flexibility as such contributes positively to efficiency and

the responsivenss of the achieved processes.

The second one is the role of transport in the agri-food supply chain model. The transportation

process is solely responsible for the animals or meat from stage to stage. The animals or meat is not

transformed or mixed. For those reasons, interviewees from barcode, computer vision and voice

identification considered this stage as a process where the animals or processed products did not

require any identification during the transport. However, the radio frequency experts recognized

potential for environmental sensors that will be discussed in section 4.2.2.2. For the findings

regarding barcode, the transport stages will therefore not be covered as no data and no information

were collected.

Section 4.4.1: Barcode identification in combination with computer vision and voice

identification

The findings within the barcode, the computer vision and the voice identification category are

presented following the agri-food chain model starting with the primary production.

Section 4.4.1.1: Primary production

This stage of the meat supply chain represents the farm were the animals are bred. The interviews

were concetrated on the processes of animal breeding management and order preparation. The five

experts that were interviewed recognized that in most of the cases, identification of animals is done

by hand or paper based, retrieving the numerical code on the ear tag. However, all recognized the

rare use and possibility to use handheld barcode at this level. The use of fixed barcode readers,

30

computer vision and voice identification was immediately discredited due to the nature of the tagged

cattle who is in constant movement and might not be visible to fixed barcode readers. This results in

the following finidings for the four main categories of the agri-food performance indicator

framework:

- Efficiency: In terms of efficiency, the investment in such technologies is difficult to justify for

individual farms because of its effect on flexibility and process quality discuss below and its

relatively low capital to generate profit. Furthermore, the benefits, resulting from individual

barcodes for each animals, are mostly experienced by later members of the supply chain.

- Flexibility: The degree to which the farm can respond to change in customer request is

according to the interviewees not affected by the use of barcodes at this stage of the supply

chain. However, flexibility in terms of operability, is affected by changing environments such as

dirt covering the tag. The information retrieval would in this case require further handling

which negatively affects flexibility.

- Responsiveness: Even though information retrieval is done automatically, the barcode reader is

still manually handled. This limits the speed of achievement of the process which in turn does

not have a significant effect on delivery lead times. However, identification errors are

positively affected as informational retrieval mistakes are considerably reduced as opposed to

paper based retrieval.

- Food quality: Food quality is at this stage not affected by the application of barcode and by the

retrieval of its encoded information. However, in case of product recall, information of

barcode tagged animals can be both faster and more easily retrieved than in the case of a

paper based information storage.

Section 4.4.1.2: Slaughtering and Processing

For this stage, data was collected with the help of a figure that served as graphical representation of

the processes that were achieved. Figure 4 was provided by one of the barcode expert that was

interviewed and depicts the five processes involved at this stage of the agri-food supply chain. Each

of the five processes are subsequently represented by a numerical figure and discussed below.

1. For the first process, order reception, solely handheld barcode retrieval is recognized as a

possibility due again to the nature of the tagged animal in constant movement.

2. During the second process that covers slaughter and processing of the cattle, traceability and

identification is primarily time based per batch. The animals that were identified in the

previous process are divided into batches that differ depending on the capacity, the amount

31

that can be slaughtered and processed at a time. The animals that are transformed into meat

cuts are retagged with a barcode on basis of the time batch that is previously determined. This

time batch approach gives the opportunity slaughterhouses to be efficient in case of recall.

Furthermore, it also provides an alternative to the expensive and time consuming retagging of

every single cut resulting from each work centers as outlined in figure 4.

3. For the following stage, interviewees recognized manually handheld barcode is most common.

However, the application of voice identification can here be considered. The technology, being

particularly efficient in cold and wet2 environment for put away and order picking activities,

suits perfectly this process at the slaughterhouse and processing stage. Furthermore, as

recognized by the voice identification experts, productivity and accuracy can be improved to

up to 20% as opposed to manually handled barcode scanners.

4. The fourth and final process of the slaughter and processing stage is responsible for the

shipping verification. If barcode tagged containers or crates are properly placed on a pallet,

the vision identification is the quickest in retrieving the encoded information and analyzing the

entire content of a pallet.

Figure 4: The slaughtering and processing process (Zetes, 2010)

2 Wet here refers to blood from the animals that might have leaked from the crate or pack the meat is

contained in.

WC A.1 WC A.2

WC B.2 WC B.1

WC C.2 WC C.1

WC E.1

WC D.1

WC D.2

WC A.1 WC A.2

WC B.2 WC B.1

WC C.2 WC C.1

WC E.1

WC D.1

WC D.2

4

2

1

3

3

32

The results from the slaughtering and processing stage are now presented in terms of the

measurement criteria defined in chapter 2.

- Efficiency: Following the above proposed technologies permits a very high level of efficiency.

According to interviewees, the third process could be imporved up to 30% in terms of

efficiency due to the reduction in labour costs and the improved productivity. Furthermore,

the fourth process enables precise order verification, minimizing shipping errors, maximizing

accuracy and as for the third process improve productivity. Overall, barcoding in combination

with computer vision and voice identification as a traceability technology permit a better

utilization of the resources at the slaughtering and processing stage of the agri-food supply

chain.

- Flexibility: As the application of the previously discussed identification technology at the

slaughtering and processing stage increase in producivity it also leaves room for faster and

more accurate responses to change in customer demands. However, traceability and

identification technology is limited by the capacity of the instalations of the slaughterhouse

and processing stage. It does not improve the slaughter and processing activities when they

are running at full capacity. Nonetheless, it provides the tools to eliminate the bottleneck that

is frequent when having to identify products for traceability purposes.

- Responsiveness: From a responsiveness perspective, as productivity increases and the

identification process is speed up, processes 3 and 4 of figure 4 are achieved faster. For that

reason, responsiveness measures such as lead times and customer response time improve.

- Food quality: Eventhough the increase shelf life due to the application of the traceability and

identification system discussed above is minimum, the reliability3 and the quality of the

processed meat exiting the slaughter and processing stage are assured. Furthermore, in case

of recall, the ability to trace the history of the product is singnificantly improved as those

information are stored electronically and ERP integrated.

Section 4.4.1.3: Wholesale

At the wholesale level, five successive processes were identified. They are represented by the

numerical figures in figure 5. For each of the five processes, the traceability and identification

technologies were first discussed with the interviewees. The following three bullet identifie which

technology fits best each process.

3 “Product reliability refers to the compliance of the actual product composition with the product description”

(Aramyan et al. 2007)

33

1&5. The first and the fifth processes are very similar. The first one must identify the crates of an

incoming pallet and the second one must identify crates of an exiting pallet. An essential

aspect is the fact that there must be a sense of continuity with the previous identification

process which in this case is the shipping verification of the slaughter and processing stage. As

it was done using computer vision, using any other technology would annihilate the benefits

gained in the previous process. The pallets that are delivered to the wholesale distribution

center are characterised by multiple barcoded tagged crates. Therefore, any of the barcoding

identification technologies that does not capture all the tags accuratly, efficiently and that

require further handling wipes out the benefits from the previous stage.

2&4. The second and the fourth processes are also similar. Both involve put away and order

selection. The physical environment at wholesale level is also characterized by cold but is, as

there is no further meat processing after the slaughtering and processing stage. Voice

identification technology was again here identified as the ideal traceability technology for its

speed of execution and for its accuracy.

3. The third process as outlined in figure 5, is responsible for the mixing of the different meat

cuts in view of the next process, order preparation. Traceability and identification is here solely

achieved by manually handled barcode scanners due to the complexity of the mixing process.

WC A.1

WC A.2

WC B.1

WC C.1

WC C.2

1

3

2 4

5

Figure 5: Wholesale Process (Zetes, 2010)

34

The combination of technologies as described in above and outlined in figure 5 are now assessed

following the performance indicator framework of Aramyan et al. (2007).

- Efficiency: The use of the multimodal identification technologies, using computer vision, voice

and barcode identification positively impacts the efficiency of the wholesale stage. Physical

resources and human resources are utilized efficiently, minimizing inventory and maximizing

inventory turnover. Furthermore, the increase in productivity in terms of identification

capacity eliminates the possibility of it turning into a bottleneck.

- Flexibility: As a result from an increase in productivity, the interviewees recognized greater

room for flexibility. First in terms of customer satisfaction, through the efficient and accurate

execution of the operations. Second in terms of volume and delivery flexibility, where the

ability to change output levels and delivery dates is no longer restricted by the need for

identification.

- Responsiveness: The improved efficiency and flexibility resulting from the application of a

combination of barcode identification technologies is also accompanied by an increase in

accuracy. The increase in accuracy of the identification of products minimizes shipping error

and as a result customer complaints. Furthermore, also related to the improved efficiency, also

interviewees recognized that lead time and fill rate were positively affected by this

combination of identification technology as it eliminates its possibility to turn into a bottle

neck.

- Food Quality: Two main indicators were recognized here as being affect by the previously

discussed combination of identification technology: shelf life and traceability. Firstly, the

improvement in speed and accuracy of the identification process ensure that the right product

is delivered at the right time positively contributes to the length of time that the meat will last

without deteriorating on its shelf. Secondly, the use of identification technology that is all

coordinated by the same information system was recognized by inventory to significantly

improve traceability enabling to retrieve real time inventory information.

Section 4.4.1.4: Retailing

The retailing stage here represented by supermarkets is characterized in the Netherlands by very

little inventory and warehousing space. Interviewees recognized e crucial need for products to arrive

exactly when needed. Meat products arriving before date would require cold storage that is in most

case not available and after date would have a significant impact on customer satisfaction. The

processes recognized for the retailing stage where identification is needed are order reception and

35

in-store replenishment. The order reception process, following the same need of consistency that

was discussed at the wholesale stage, is once again achieved by computer vision. For the in-store

replenishment, a typically labor intensive process, interviewees recognized that identification

technology must ensure productivity and flexibility. Voice technology in combination with barcode

scanners attached to the wrist and finger (appendix 11) ensures the need for staff productivity and

flexibility.

The proposed identification technologies for the retailing stage are now assessed following the

performance indicator framework proposed by Aramyan et al. (2007).

- Efficiency: The application of computer vision and voice in combination with barcode

identification was recognized to affect positively efficiency at the retailing stage. The order

reception and in-store replenishment, known as labor intensive tasks, where the support from

identification technology helped increasing staff productivity. Especially at the order reception

identification process where labor can be reduced to only one individual. The voice in

combination with barcode identification maximized productivity of replenishment staff and

suppressed time consuming paper based operations. As those technologies are integrated to

inventory management systems and ERPs, the availability of accurate real-time data enables

efficient inventory management.

- Flexibility: As a result from real-time data information, appropriate quantities of meat product

can be replenished at the right time to ensure maximum shelf availability, which ultimately

results in customer satisfaction. Furthermore, the availability of real-time data minimizes the

necessity to rely on backorders and to lose sales. Interviewees recognized that identification

technology’s effect on volume flexibility and delivery flexibility at this stage was insignificant

and would not represent a bottleneck which would reduce the flow of products.

- Responsiveness: The interviewees recognized that the accuracy improvement in identification

resulting from the application of the traceability technologies provided the appropriate

information to positively affect responsiveness performance measures. As such identification

technologies provide real-time information to be able to respond quickly to customer

demands.

- Food Quality: The speed, efficiency and accuracy of execution of the preceding identification

processes from each stage contribute to the shelf life of the meat product in the supermarket.

The combination of identification technologies that were proposed along the fresh food supply

chain model all contributed the speed and efficiency of each stage. Therefore, shelf life is

36

expected to increase. Regarding traceability, the availability of real-time information that is

integrated to organizations ERP enable data the retrieval for recall purposes.

The next section discusses the effect of the application of barcode identification technology in

combination with computer vision and voice identification on the consumer also represented in the

agri-food chain model as the FORK.

Section 4.4.1.5: Consumer

The consumer stage serves as an overall evaluation of the performance of the supply chain.

Ultimately, all the application of identification technology should beneficiate to the consumer of the

product, in the case the piece of meat. When using solely barcode identification in combination with

computer vision and voice identification, most of the history of the product is lost at the time based

per batch process. Furthermore, even though identification solutions were proposed for the

processes at the primary production stage, the benefits as opposed to paper based solution remain

quite low especially when considering the investment costs.

The next section evaluates the implementation of RFID following the same stages that were reviewed

all along section 4.2.1.

Section 4.4.2: Radio Frequency Identification

The findings for the application of RFID on a fresh meat supply chain are presented in this section.

The presentation scheme is once again following the agri-food chain model described in section

2.4.1. In order to gather information about the application of RFID in meat supply chains three

experts from two different countries were interviewed. The presentation of the results begins with

the primary production stage.

Section 4.4.2.1: Primary production

The application of RFID at the first stage of meat supply chains is, according to the interviewees, still

at the experimental stage. However, experts recognized the immense potential of using the latter

identification and traceability technology at the primary production stage. The grounds for this

prospective is the ability to track the cattle, to trace its medical and feed history, and to update it in

real time wihtout having to retag the animal after every new action. Furthermore, interviewees also

recognized that the speed of execution of animal breeding task is significantly improved with the

37

application of RFID. The latter findings are evaluated below following the perfomance indicator

framework presented in chapter 2.

- Efficiency: The application of RFID at the primary production represents an investment that is

difficult to justify in terms of the actual profits it will bring back to the cattle breeder.

According to the interviewees, not only the RFID ear tags but also the RFID reader are costly

investment that cannot be justified if the costs are solely bared by the primary production

stage. However, a Norwegian experimental RFID project in an organic meat chain highlighted

the labour savings resulting from the automation of identification tasks. Although this

reduction in labor cost contributed positively to the efficiency indicator of performance,

experts considered this input to be irrelevant compared to the extra cost of investment in RFID

material.

- Flexibility: The ability to respond to changes in customer demands was recognized to be

positively affected by the interviewed experts. As the primary producer has real-time data

about the amount of cattle meeting the requirements of his customer, the former is capable of

ansering quickly to extrordinary request. Flexibility as defined in section 4.2 is however

significantly improved with the use of RFID. Processes can be automated as the RFID tag

doesn’t need to be visible to be decrypted. The manual handling required with paper based

solutions and barcode solutions is eleminated which enables significantly more flexibility in

terms of operability.

- Responsiveness: Interviewees recognized that radio frequency application at the primary

production stage affected significantly the responsiveness performance identicator. Customer

response time, lead time and shipping error performance indicators are considerably improved

when using RFID. The speed of execution of breeding and order preparation is reduced,

positively affecting customer response time and lead time. Whereas, the accuracy of

identification of cattle is improved which has a positive impoct on customer complaints and

shipping errors. Overall, RFID experts considered that responsiveness is significantly improved

with RFID.

- Product Quality: Although the effects of RFID application at the primary production stage on

shelf life was recognized as difficult to evaluate, traceability is recognized as the most

significant improvement. The ability to update and access real-time data such as medical and

feed history steers towards excellence in traceability. An additional benefits from using RFID

that is recognized by the experts, is the ability to work in rainy environment which is not

negligable in north western europe.

38

The next stage of the agri-food mode is discussed below. Unlike barcode identification, RFID enables

some processes improvement that are presented below. The results of the transport of animals was

however regrouped into the following section. That is the two other transport stages of the agri-food

model will solely be discussed in section 4.4.2.2. to avoid repetition.

Section 4.4.2.2: Transport of animals and of processed meat

The experts in RFID, unlike the ones for barcode identification, recognized the possibility of applying

RFID in the transport of animals and processed meat. The addition of environmental sensors to

individual pallets or to different location of the trailer were recognized to be an essential asset to

reduce waste in meat supply chains. Waste in supply chains is meat supply chains is mostly due to

products that reach their best before date before they are sold. Such events can results from

negative environment impacts during transport. Although environmental aspects are rarely affecting

cattle during transport, one can envisage the negative effect of transporting animals under severe

heat waves during summer months. For the transport of processed meat the need for refrigerated

transportation and distribution facilities is more understandable.

Appendix 12 provide a visual representation for the use of environemental sensors during

transportation processes. An important aspect to signal here is that a pallet in a refrigerated trailer

placed in the back is not affected the same way as the ones closer to the doors. For that purpose

several environmental sensors (represented by red dots in appendix 11) are strategically scattered

around the trailer. The sensors continuously communicate through radio frequency waves the

characteristics of it environment. The information can be retrieved when the truck passes through an

RFID gate at its arrival destination.

Effects on efficiency and flexibility were immediately discredited by the RFID experts as no reduction

of costs nor increased flexibility could be identified. The investment cost in this technology is on the

other hand justifiable as it enables the logistics service provider to defend himself in case of waste

identification. Some benefits are however recognized in the responsiveness and product quality

performance indicators. Those are discussed below.

- Responsiveness: The speed of execution of the transportation process is not affected by the

application of RFID. Therefore, the indicators such as lead time and product lateness are not

affected. However, the amount of registered customer complaints decreases as the

environmental history of the delivered product can be certified.

- Product Quality: As the environmental history of the product can be certified and traced, shelf

life accuracy in shelf liffe determination are considerably improved. The benefits at this stage

39

are therefore, the constant monitoring of the real shelf life and the ability to determine who is

responsible for an out of specification condition of a meat product.

The slaughtering and processing stage is presented and discussed in the next section before being

evaluated on basis of the performance indicator framework of Aramyan et al. (2007).

Section 4.4.2.3: Slaughtering and Processing

For this stage the same figure presented in the presentation of the findings for barcode. However,

different identification technologies are proposed for each of the process represented by the

numerical figures in the figure below.

The rational of continuity that was applied in the section dealing with barcode in combination with

computer vision and voice identification, is also employed here. As cattle was individually RFID

tagged during the primary production stage, enabling the real time update of their feed and medical

history, switching to barcode identification would annihilate the benefits previously recognized. The

following bullet points present the traceability solution that recognized by the interviewees as most

appropriate.

1. The first process of the above figure is the point of entry and requires order reception

examination. An RFID gate scanning the incoming cattle was recognized by the experts as most

Figure 5: Slaughtering and processing process (Zetes, 2010)

40

appropriate. The speed at which cattle crosses the RFID gate enables accurate and efficient

identification.

2. For the second process which represents the slaughtering of the animals and the processing of

the carcasses, RFID can be used to tag at every new cut that was made. The solution proposed

by the experts is the use of ‘RFID nails’ that can individually identify every piece of meat

enabling the traceability up to the animal feed and medical history.

3. The third process is responsible for put away and order picking. The accuracy constraints of

RFID due to environment factors discussed in section 2.5.4.2. shows here its limitations. As

meat cuts, which contain a very high concentration of liquid, are superposed in crates the

percentages of identification drop considerably. Nevertheless, the process with RFID

identification is assessed following the performance indicator framework of Aramyan et al.

(2007).

4. The fourth and final process, the shipping verification using RFID identification is also affected

by the environmental constraint discussed in the previous bullet point. As the third process,

the fourth one is still evaluated by interviewees in terms of efficiency, flexibility,

responsiveness and product quality.

The identification and traceability technologies previously discussed are now assessed following the

performance indicator framework of Aramyan et al. (2007).

- Efficiency: The use of RFID at the slaughtering and processing stage can be divided into two

main phases. The first one being before the meat cuts are superposed in crates and on pallets.

The second one being the superposition up to the shipping verification. For the first phase, the

automation resulting from the use of RFID identification contribute to the reduction in labor

costs and to the maximization of the use of its slaughtering and processing resources. For this

phase the contribution of RFID to efficiency is seen as positive by the experts. However, for the

second phase, the drop in accuracy of identification contributes negatively to the efficiency

indicator as processes need to be repeated and further handling of pallets is required.

- Flexibility: Following the division of the slaughtering and processing stage presented above,

volume flexibility and customer satisfaction would first beneficiate from the application of

RFID as a traceability technology before the annihilation of the later advantages in the second

phase of the stage. The effects of RFID implementation on

- Responsiveness: The customer response time, the customer complaints and the shipping errors

are negatively affected by the lack of accuracy in identification and in the resulting repetition

of the processes. Responsiveness is therefore considered as being negatively affected by

application of RFID as traceability and identification technology.

41

- Product Quality: Traceability is significantly improved in the first phase of the slaughtering and

processing stage as RFID tags retain information up to the feed and medical history of the

animals. Although the information is still available at the end of the second phase of the stage,

due to some unread tags, traceability could not be considered as optimal by interviewees.

Furthermore, shelf life was considered to be hampered do to the inaccuracy in tag reading and

the necessity of repetition of the processes during the second phase of the slaughtering and

processing stage.

The presentation of the findings using RFID as an identification and traceability solution continues

with the wholesale stage as the transport of processed products was already discussed.

Section 4.4.2.4: Wholesale

The findings for the application of RFID at the wholesale level were considerably affected by the

characteristics of meat products. As discussed in the slaughtering and processing stage, the

superposition of meat product containing considerable able of liquid significantly affects the accuracy

and the efficiency of the identification process. The use of RFID at the wholesale level for meat

products was therefore also recognized by interviewees as difficult to realize. Experts suggested that

the use of evolved barcode technologies as discussed in section 4.4.1.3 would be less costly, more

accurate and more efficient. Due to technological limitation of RFID regarding the information

retrieval when faced with products containing high amour of liquid, the wholesale stage is not

assessed and not discussed here.

The following stage that is evaluated following the performance indicator framework proposed by

Aramyan et al. (2007) is the one of retailing as the transport of processed products was discussed in

section 4.4.2.2.

Section 4.4.2.5: Retailing

The reception of products at the retailing stage also follows the principal of continuity that was

discussed along the chapter of the presentation of the findings. Order reception is therefore

achieved using computer vision technology as outlined in section 4.4.1.4. According to the

interviewees, the identification of products during the order reception process using RFID already

showed signs of inaccuracy when it was experimented by retailers such as Wal-Mart and Tesco.

RFID at the retailer could just like for the transport stages, be utilized for the control of temperatures

until the packaged meat arrival at in the fridge of the supermarket. Although interviewees recognized

that this type of application worked efficiently, it was not recognized to affect any other performance

42

indicator than customer satisfaction. The reason for this is that it is mostly recognized as a marketing

application rather than a tool to enable higher supply chain efficiency. For the shelf replenishment,

once again, RFID experts discredited the technology advancing that barcode in combination with

voice technology is considerably cheaper and more efficient.

The following section is the consumer stage of the agri-food chain model. As it is the last link of the

supply chain it also serves as conclusion for the presentation of the RFID findings.

Section 4.4.2.6: Consumer

As for the section covering barcode in combination with computer vision and voice identification, the

consumer stage enables the evaluation of the entire supply chain. RFID is enabling traceability of the

full history from cattle up to the second phase in the slaughtering and processing stage. As from that

point the superposition of crates filled with packaged meat cuts does not enable an accurate reading

of all the products present on a when passing through an RFID gate.

The need for an alternative solution is essential so that the identification of meat processes

contribute to the efficiency and productivity of each stage. The alternative solution is present in the

following section when outlining the best fit solution for meat supply chains.

Section 4.5: Technology best fit

For the purpose of providing a final answer to the second research question, this section presents

the agri-food chain model in combination with the identification technology that fits best each of its

stages and related processes.

Figure 6 presents the graphical representation of the latter combination. As the justification and the

effects with respect to competitive performances for each stage and process have been discussed in

the previous chapter, explanation for the swap of technology at the slaughter and processing stage is

now provided. The slaughtering and processing identification is mostly done in practice on time

based per batch for economical reasons. However, the application of RFID nails applied to every new

meat cut retaining the information that was encoded in the RFID ear tag of the cattle is from a

traceability perspective very attractive. The RFID nails placed in the meat cuts can be recovered

before packaging which on the long run permits the amortization of the RFID nails costs.

43

From there on, meat packages can be tagged with two-dimensional barcode that can contain a

summary of the history and indications of where to find the entire history of the packaged meat. The

latter can thereafter be placed in plastic crates in view of order preparations. This swap of

technology also provides a solution to the extensive limitations of RFID when having to identify meat

products containing high percentages of liquids.

44

Figure 6: Identification technology best fit on meat supply chains

Primary Production:

• Breeding Management : RFID

• Order Preparation : RFID

Transport of Animals:

• No RFID environmental sensors

Slaughtering and Processing:

• Order Reception: RFID

• Animal Slaughter and Carcass Processing : RFID

• Put away: Voice ID (group:Barcode ID)

• Order Picking: Voice ID (group:Barcode ID)

• Shipping Verification: Computer Vision ID (group:Barcode ID)

Transport of Processed Products

• RFID environmental sensors

Wholesale

• Order Reception: Computer Vision ID (group:Barcode ID)

• Put away: Voice ID (group:Barcode ID)

• Order Picking: Voice ID (group:Barcode ID)

• Mixing: Voice ID (group:Barcode ID)

• Shipping Verification: Computer Vision ID (group:Barcode ID)

Transport of Processed Products

• RFID environmental sensors

Retailing

• Order Reception: Computer Vision ID (group:Barcode ID)

• Replenishment: Voice ID (group:Barcode ID)

45


This chapter first presented the case study. Subsequently, two identification technologies available in

Zetes product portfolio that are not discussed yet in the operations and business academic literature

and therefore not included in the theoretical framework are described. This further outlines the

necessary requirement for the implementation of a traceability system. Thereafter, the answer to

the research question that analyzed the effects of the implementation of identification technology

on meat supply chains performance is provided by subsequently assessing each stage in terms of

efficiency, flexibility, responsiveness and product quality. Lastly, with respect to the second research

question about the most appropriate technology for each stage and process, it is shown that not one

single ID is useful for the whole chain due to different environmental circumstances or information

needed at certain moments in the chain.

46

Chapter 5: Discussion and Conclusions


In this final chapter, the main conclusion of the thesis are presented. The chapter starts by

evaluating the application of the performance indicator framework developed by Aramyan et al.

(2007) on traceability and identification technology is evaluated. Subsequently, some

recommendations are given and finally the main conclusion is presented.

Section 5.2: Fresh food supply chain

In order to recall the main objective of the research the problem statement is firstly restated.

How can the implementation of goods identification systems contribute to fresh

food supply chains performance?

Following the identification technology best fit on meat supply chain in section 4.5, its effect on

supply chain performances is now concluded upon in terms of the four indicator criteria for agri-food

chains developed by Aramyan et al. (2007).

- Efficiency: The implementation of the different identification technologies on fresh food supply

chains as presented has an ambiguous effect on the efficiency of fresh food supply chain as a

whole. Although, the multi-modal traceability system positively affects the labor costs, return

on investment cannot be justified for the primary production and for the slaughtering and

processing stages. However, the implementation of voice and computer identification is

recognized to positively affect profits of the other stages of the fresh food supply chain.

- Flexibility: The availability of accurate information at each stage of the fresh food supply chain

enables to positively affect the flexibility indicator. The reason for this is that the precise

information regarding the products facilitates inventory management which ultimately

positively contributes to customer satisfaction and delivery flexibility.

- Responsiveness: As for the flexibility performance indicator, the availability for managers to

rely on accurate data of the incoming and exiting products enables to respond faster and

better to customer request. The implementation of identification technology especially affects

positively measures such as lead time, customer complaints and shipping errors.

- Food Quality: The effects of the implementation of identification technology along fresh food

supply chains are mostly experienced in the food quality category. Traceability is significantly

improved with the use of RFID as from the first stage of the supply chain, enabling (in theory)

the final customer to trace his meat product up to the farm it was bred in. The environmental

47

sensors for the transport of processed product enable accurate monitoring of the quality of

the delivered products and subsequently positively affecting its shelf-life.

As a result, the contribution of identification and traceability technologies to meat supply chains is

recognized to be considerably effective for flexibility, responsiveness and food quality criteria. The

findings obtained for the meat industry can be generalized for fresh food supply chains. The reason

for this is that the case study’s foundations are based on an agri-food chain model that was only

stripped to encompass solely meat related activities without altering any of the stages and processes.

Furthermore, even though meat is a totally different product than fish, fruit or vegetables, all contain

relatively high percentages of liquid and are fast perishable goods. Mostly, the same complexities

identified in chapter 2 apply for meat, fish, fruits and vegetables. Only seasonality does not apply to

meat products. This in turn changes production throughput time as opposed to other fresh food

products. However, the rest of the complexities and specificities are fulfilled by meat products.

It can be concluded that identification technologies add value to fresh food supply chains by enabling

higher level visibility of products and accuracy of performed processes. This in turn permits a more

accurate management of resources. However, due to the expensive nature of identification

technology, its contribution to the efficiency criterion is still ambiguous.

Section 5.3: Assessment of traceability technology with the framework of

Aramyan et al. (2007)

The framework developed by Aramyan et al. (2007) enclosing measures for efficiency, flexibility,

responsiveness and food quality for every stage of a meat supply chain enclosed both financial and

non-financial indicators of performances. Although, the interviewee feedback received by Aramyan

et al. (2007) was positive, the application of such a framework for traceability and identification

technology was recognized as in some case too broad and in some case to narrow by the experts

from Zetes. The framework originally developed for food quality management was first adapted to

suit a supply chain management perspective. Performance indicators such as salubrity, pesticide use,

energy use and water used were therefore removed. Moreover, some of the remaining indicators

such as volume flexibility and delivery flexibility were not necessarily adequate for the assessment of

traceability and identification technology. The latter are not developed nor used to contribute to

volume nor delivery flexibility.

However, the aim of the thesis is to research how goods identification system applied to fresh food

supply chains could contribute to its performances. For that reason, evaluating the implementation

48

for each stage of the agri-food chain in terms of efficiency, flexibility, responsiveness and food quality

was necessary. An indicator was added under the flexibility criteria as the need for operators to

perform their tasks without being hinder by the handling of identification hardware.

Section 5.4: Limitations and Recommendations

The following limitations and recommendations are based on the findings of outlined in chapter 4

and on two previous sections.

- The first limitation and recommendation results from the refusal of external parties to

communicate any information about the way traceability and identification is achieve within

their organization for confidentiality reasons. Even though, the experts of Zetes could provide

with precision the processes requiring identification, external analysis and perspective on the

issue would have increased the reliability and validity of the research. External analysis

becomes also particularly relevant when having to evaluate the external traceability as

discussed in section 2.3. Further research on the implementation of identification technology

could therefore be conducted from a retailer, a wholesaler, a slaughter and processing, and a

primary producer perspective.

- The second limitation and recommendation is also related to the refusal or inability to accept

an interview. As all the stages from the agri-food chain were researched, the collaborative

aspects of supply chain management and buyer-supplier relationships are also an important

factor that was not covered in this research. Although the concept was introduced when

evoking the continuity principle between supply chain partners, further research could be

done on this aspect.

- The third and final limitation is the choice of product to identify and trace. Two aspects must

be outlined. Firstly, meat products that contain high percentages of liquids compared to other

food products limited the potential to use RFID as from the second phase of the slaughter and

processing stage. Secondly, the fact that the wholesale stage and the retail stage do not solely

identify and trace meat products. As from the wholesale stage, meat products are usually

mixed with other fresh food products that do not have the same characteristics of high liquid

concentrations. Furthermore, the traceability of meat product was facilitated by the use of

RFID nails. Using the same type of nails in the vegetable or fruit industry would deteriorate the

aspect of the product and therefore not be considered. Another solutions than nails would

therefore necessary for the identification of vegetables for this process.

49

The following section presents the conclusions of the conducted research.


The growing interest for RFID in academic literature is in line with the one of practioners. However, a

growing gap is taking place between academics perspective of RFID adoption and what is seen in

practices.

The conducted research in this thesis, proved that in some cases limitations of RFID cannot be

overcome and relying on evolved barcode identification remains the most appropriate solution. The

poor performance of RFID when applied to meat product can be generalized to all fresh food

containing high percentages of liquid. Which in fact, represent most of the vegetables, fruits, fish

and meats. This aspect confirms the possibility to generalize the research to other industries. For

those products, barcode reading technologies in combination with computer vision and voice

identification were recognized to be more appropriate. Barcode technology should therefore not be

disregarded.

When combining the four identification technologies on a meat supply chain, the considerable

traceability advantages of RFID can be united with the ones of the three other technologies. As a

result, consumers can beneficiate from higher quality standards and better services.

I

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IV

Appendices:

Appendix 1: Traceability across the supply chain

Appendix 1: Traceability across the supply chain from global traceability standards (adapted by GS1)

Appendix 2: 1D Barcode

Appendix 2: GS1 Barcode 1D

V

Appendix 3: 2D Barcode

Appendix 3: GS1 Barcode 2D

Appendix 4: Voice head set and belt terminal

Appendix 4: Voice head set and belt terminal (Vocollect)

Appendix 5: Visidot reader

Appendix 5: Visidot reader (Zetes)

VI

Appendix 6: Single vs two-sided Visidot gate

Appendix 6: Single vs two-sided Visidot gate (Zetes)

Appendix 7: Visidot Director

Appendix 7: Visidot Director (Zetes)

VII

Appendix 8: Barcode and voice interview table

Appendix 8: Table interview 1

VIII

Appendix 9: Computer vision interview table


IX

Appendix 10: Radio frequency interview table


X

Appendix 11: Voice terminal combined with finger barcode reader

Appendix 12: Truck environmental sensor

XI

Appendix 13: Performance indicator framework, adapted from Aramyan et al. (2007)

Categories and indicators Definitions Measures

Efficiency

Production costs/distribution costs

Combined costs of raw materials and labor in producing goods/ combined costs of distribution, including transportation and handling costs

The sum of the total costs of inputs used to produce output/services (fixed and variable costs)

Transaction costs The costs other that the money price that are incurred in trading goods or services (e.g. searching costs, negotiation costs, and enforcement costs)

The sum of searching costs (the costs of locating information about opportunities for exchange), negotiation costs (costs of negotiation the terms of exchange), enforcement costs (costs of enforcing the contract)

Profit The positive gain from an investment or business operation after subtracting all expenses

Total revenue less expenses

Return on investments A measure of a firm’s profitability and measures how effectively the firm uses its capital to generate profit

Ratio of net profit to total assets

Inventory A firm’s merchandise, raw materials, and finished and unfinished products which have not yet been sold

The sum of the costs of warehousing of products, capital and storage costs associated with stock management and insurance

Flexibility

Customer satisfaction The degree to which the customers are satisfied with the products or services The percentage of satisfied customers to unsatisfied customers

Volume Flexibility The ability to change the output levels of the products produced Calculated by demand variance and maximum and minimum profitable output volume during any period of the time

Delivery flexibility The ability to change planned delivery dates The ratio of the difference between the latest time period during which the delivery can be made and the earliest time period during which the delivery can be made and the difference between the latest time period during which the delivery can be made and the current time period

Backorders An order that is currently not in stock, but is being re-ordered (the customer is willing to wait until re-supply arrives) and will be available at a later time

The proportion of the number of backorders to the total number of orders

Lost sales An order that is lost due to stock out, because the customer is not willing to permit a backorder.

The proportion of the number of lost sales to the total number of sales

Responsiveness

Fill rate Percentage of units ordered that are shipped on a given order Actual fill rate is compared with the target fill rate

Product lateness The amount of time between the promised product delivery date and the actual product delivery date

De livery date minus due date

Customer response time The amount of time between an order being made and its corresponding delivery The difference between the time an order is made and its corresponding delivery

Lead time Total amount of time required to produce a particular item or service Total amount of time required to complete ne unit of product or service

Customer complaints Registered complaints from customers about product or services Total number of complaints

Shipping errors Wrong product shipments The percentage of wrong shipments

XII

Appendix 13 (Continued): Performance indicator framework, adapted from Aramyan et al. (2007)

Categories and indicators Definitions Measures

Traceability Traceability is the ability to trace the history, application or location of a product using

recorded identifications

Information availability, use of barcodes, standardization of quality systems

Storage and transport

condition

Standard conditions required for the transportation and storage of the products that

are optimal for good quality

Measure of relative humidity and temperature, complying with standard regulations

Working condition Standard conditions that ensure a hygienic, safe working environment, with correct

handling and good conditions

Compliance with standard regulation

Food Quality

Shelf life The length of time a packaged food will last without deteriorating The difference in time between harvesting or processing and packaging of the

product and the point in time at which it becomes unacceptable for consumption

Product Reliability Refers to the compliance of the actual product composition with the product

description

Number of registered complaints

traceability in fresh food supply chains

Documents