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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
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
SECTION 3.5: CONCLUSION ..................................................................................................................................... 23
CHAPTER 4: CASE STUDY ................................................................................................................................ 24
SECTION 4.1: INTRODUCTION .................................................................................................................................. 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
SECTION 4.6: CONCLUSION ..................................................................................................................................... 45
CHAPTER 5: DISCUSSION AND CONCLUSIONS ................................................................................................ 46
SECTION 5.1: INTRODUCTION .................................................................................................................................. 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
SECTION 5.5: CONCLUSION ..................................................................................................................................... 49
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
Section 2.1: Introduction
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
Transport of processed products
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.
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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
Section 3.1: Introduction
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
Section 3.5: Conclusion
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
Section 4.1: Introduction
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
Transport of processed products
Wholesale
Transport of processed products
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
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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
Section 4.6: Conclusion
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
Section 5.1: Introduction
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.
Section 5.5: Conclusion
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
Appendix 9: Table interview 2
IX
Appendix 10: Radio frequency interview table
Appendix 10: Table interview 3
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
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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
13