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Supply chain traceability: a review of the benefits and its relationship with supply chain resilience


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There has been considerable recent growth in supply chain (SC) traceability research due to increased Industry 4.0 solutions and the potential of traceability systems to enable SCs to bounce back from a crisis, thereby having a long-term impact on firm/SC performance. However, to date, the relationship between SC traceability and SC Resilience (SCRes) has not been fully explored. Using a systematic literature review, this paper first provides a comprehensive state-of-the-art understanding of traceability to enable an appreciation of the inherent benefits of its implementation and its role in the improvement of SCRes. Building on this understanding, a conceptual framework is developed showing that there is a direct relationship between traceability benefits, such as improved risk awareness, and SCRes. The framework also demonstrates indirect relationships between these benefits and four enablers of SCRes: flexibility, velocity, visibility and collaboration. Finally, a future research agenda is proposed, including further development of this conceptual framework. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
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Production Planning & Control
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Supply chain traceability: a review of the benefits
and its relationship with supply chain resilience
Ghadafi M. Razak, Linda C. Hendry & Mark Stevenson
To cite this article: Ghadafi M. Razak, Linda C. Hendry & Mark Stevenson (2021): Supply chain
traceability: a review of the benefits and its relationship with supply chain resilience, Production
Planning & Control, DOI: 10.1080/09537287.2021.1983661
To link to this article:
© 2021 The Author(s). Published by Informa
UK Limited, trading as Taylor & Francis
Published online: 06 Oct 2021.
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Supply chain traceability: a review of the benefits and its relationship with
supply chain resilience
Ghadafi M. Razak , Linda C. Hendry and Mark Stevenson
Department of Management Science, Lancaster University Management School, Lancaster, UK
There has been considerable recent growth in supply chain (SC) traceability research due to increased
Industry 4.0 solutions and the potential of traceability systems to enable SCs to bounce back from a
crisis, thereby having a long-term impact on firm/SC performance. However, to date, the relationship
between SC traceability and SC Resilience (SCRes) has not been fully explored. Using a systematic lit-
erature review, this paper first provides a comprehensive state-of-the-art understanding of traceability
to enable an appreciation of the inherent benefits of its implementation and its role in the improve-
ment of SCRes. Building on this understanding, a conceptual framework is developed showing that
there is a direct relationship between traceability benefits, such as improved risk awareness, and
SCRes. The framework also demonstrates indirect relationships between these benefits and four
enablers of SCRes: flexibility, velocity, visibility and collaboration. Finally, a future research agenda is
proposed, including further development of this conceptual framework.
Received 25 February 2021
Accepted 17 September 2021
Traceability; supply chain
resilience; Industry 4.0;
blockchain; risk awareness;
literature review
1. Introduction
Supply Chains (SCs) have become increasingly complex in
recent years resulting in a greater susceptibility to risks, tur-
bulence and disruptions (Pettit, Croxton, and Fiksel 2013).
Nearly 65 percent of companies experience at least one dis-
ruption a year, and 13 percent of the firms that faced a dis-
ruption in 2019 reported over e1million in losses (Business
Continuity Institute 2019; Chang, Iakovou, and Shi 2020). The
fourth industrial revolution (Industry 4.0) provides potential
remedies for these issues. Specifically, it presents a timely
paradigm shift for SC management especially with regards to
technological innovations/digitalization that enhances an
organizations capability of predicting future events and
identifying and monitoring real-time events (Ivanov and
Dolgui 2020). Industry 4.0 with its associated technologies
such as Cyber-Physical Systems (CPS), 3 D Printing, Advanced
Robotics, Artificial Intelligence (AI), Unmanned Aerial Vehicles
(UAVs), Big Data Analytics (BDA), Blockchain, the Internet of
Things (IoT), and Augmented Reality (AR) presents a platform
that integrates and transforms SC management with
increased end-to-end transparency and connectivity
(Fatorachian and Kazemi 2021; Hopkins 2021; Mubarik et al.
2021). Kittipanya-Ngam and Tan (2020) identified efficiency,
traceability, sustainability, legal culpability, and e-commerce
as the main dimensions of this digitalization era.
Considering the consequences of a disruption on a firm,
its SC, and subsequently on human health and safety (Bode
et al. 2011; Ringsberg 2014; Stranieri, Orsi, and Banterle
2017), obtaining real-time information to identify and curb
disruptions before the escalation of damages has become an
important dimension expected of these emerging technolo-
gies (Granillo-Mac
ıas et al. 2020; Ivanov and Dolgui 2020). In
particular, traceability systems have increasingly been consid-
ered to be an important tool to improve SC performance in
relation to SC risk management because of its ability to
obtain, update and transfer information in real time with
minimal delays and errors (Ringsberg 2014; Stranieri, Orsi,
and Banterle 2017). A robust traceability system has become
necessary especially in customer-driven industries where con-
sumer loyalty, trust, and confidence is gained through the
assurance of the quality and safety of products (Montet and
Dey 2018; Kittipanya-Ngam and Tan 2020). Coupled with the
increased availability and accessibility of digital technologies,
the demands for transparency and traceability among the SC
actors continues to increase making it an effective capability
to minimize production and distribution disruptions and fur-
ther ensure the efficient tracking and tracing of potentially
deficient batches in case of any recalls (Montet and Dey
2018; Kittipanya-Ngam and Tan 2020).
Given the link between the effective management of dis-
ruptions and traceability, and that both can potentially be
supported by the digitalization era, it follows that traceability
is an enabler of Supply Chain Resilience (SCRes) as SCRes
has been defined as an operational capability that enables a
firm to prepare for, respond to and recover from a disrup-
tion/crisis to return to its normal operationscapacity or
even to a better capacity (Brusset and Teller 2017). The role
CONTACT Ghadafi M. Razak Department of Management Science, Lancaster University Management School, Lancaster, UK.
ß2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (
4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon
in any way.
of traceability as an enabler of SCRes has been particularly
emphasized in the context of food SCs (Van Rijswijk and
Frewer 2008; Zhao, Liu, and Lopez 2017). Studies in other
industries have also emphatically stressed the significance of
real-time end-to-end monitoring across the SC as an enabler
of SCRes. However, these studies have generally attributed
this requirement to visibility (J
uttner and Maklan 2011; Pettit,
Croxton, and Fiksel 2013; Mubarik et al. 2021) without an
analysis of the role of traceability either in facilitating visibil-
ity or SCRes directly. To fully understand and appreciate the
link between traceability and SCRes requires an encompass-
ing definition of traceability that transcends beyond the
tracking and tracing of products to include the generation,
updating and transferring of information on: (1) product
characteristics (such as weight and temperature); (2) energy
and resource consumption; (3) batch quantity/size; and (4)
production, transformation and distribution schedule and
capacity (Kar^
aa and Morana 2016; Marconi et al. 2017; Zhao,
Liu, and Lopez 2017; Casino et al. 2020). Thus, this paper
adopts this definition of traceability.
Research into the role of traceability dates back to the
late 1990s where its impact on quality assurance in the
European meat supply chain was examined (e.g. Simpson,
Muggoch, and Leat 1998; Viaene and Verbeke 1998).
Thereafter, a significant number of studies have been under-
taken across various industries, including the recent resur-
gence due to the increased need in modern SC management
operations in the Industry 4.0 era (e.g. Coronado Mondragon,
Coronado Mondragon, and Coronado 2021; Casino et al.
2020; Kayikci et al. 2020). However, there remains a lack of
consensus on the impact of traceability systems on SC per-
formance, which hence affects the willingness of companies
to adopt traceability systems voluntarily (Mai et al. 2010;
Mattevi and Jones 2016). There have been notable literature
reviews on specific themes of traceability, such as technology
(Costa et al. 2013; Pournader et al. 2020; Wang, Han, and
Beynon-Davies 2019) and legislation (Borit and Santos 2015);
as well as reviews based on its relationship with other SC
management concepts such as risk management (Ringsberg
2014) and sustainability (Garcia-Torres et al. 2019). There are
also some reviews on the benefits of traceability and its
impact on SC performance, but these reviews have been lim-
ited either to a particular industry, with a focus on food
(Opara 2003; Dabbene, Gay, and Tortia 2014) or computers
and software (Omar and Dahr 2017; Mustafa and Labiche
2017), or to a particular technology, with a focus on block-
chain (Pournader et al. 2020; Feng et al. 2020) or RFID
(Nambiar 2010; Costa et al. 2013). Thus, there is a need for a
comprehensive review of the extant literature to integrate
the benefits of traceability discussed across multiple indus-
tries and technologies. There is also a timely need to con-
sider the relationship between the benefits associated with
traceability and SCRes, as no literature reviews to date have
explored this relationship.
This paper adopts a systematic literature review approach
to address these gaps, and thereby address the following
research question: What are the benefits of the deployment of
a SC traceability system emphasized in the literature, and how
does the deployment of traceability enable/enhance the attain-
ment of SCRes? To fully appreciate the benefits of traceability
and its relationship with SCRes, it is first necessary to sum-
marize the current state-of-the-art understanding of trace-
ability systems in terms of: the drivers/motivations, the
evolution of technology; and the challenges/barriers that
inhibit its implementation. This is necessary given that there
is a clear link between these issues and the benefits
achieved. For example, the choice and subsequent success of
a traceability system is affected by: the reasons for its adop-
tion, the functionality of available technologies and how the
SC partners overcome any barriers to adoption. Thus, under-
standing these issues enables a deeper understanding of the
benefits. A comprehensive understanding of the benefits in
turn enables the development of an understanding of the
relationship between these benefits and SCRes.
The rest of this paper is structured as follows. Section 2
outlines the methodology adopted for this study. Section 3
provides a descriptive summary of the identified literature,
which includes the background information required to
answer the research question in terms of traceability drivers,
the evolution of technology and the barriers to implementa-
tion. Section 4 then discusses the findings in relation to the
benefits of traceability. Section 5 explores the relationship
between these traceability benefits and SCRes by further
analyzing the issues raised in the literature. Section 6 pro-
vides a conclusion, identifies the research gaps and suggests
potential future research directions.
2. Method
2.1. Systematic literature review (SLR)
An SLR was chosen for this study because of its ability to
eliminate bias and improve thoroughness in identifying and
selecting relevant studies (Tranfield, Denyer, and Smart 2003;
Denyer and Tranfield 2009). Thus, the SLR approach ensures
a comprehensive review of relevant studies thereby provid-
ing an important building block for the advancement of
traceability knowledge. This is especially needed at this point
in time given that evaluating the usefulness of SC digitaliza-
tion in curbing SC disruptions is currently high on the
research agenda. By collating existing literature into a rigor-
ous and reliable format, this study informs academic
researchers, practitioners and/or policymakers on the benefits
of this important dimension of digitalization (Denyer and
Tranfield 2009). It thereby enables firms to make informed
decisions in terms of their investment choices around the
digitalization of SC solutions, making effective use of their
limited resources. Specifically, Durach, Kembro, and Wieland
(2017) paradigm for conducting SLRs in SCM was adopted to
meet the specific philosophical characteristics of SCM
research. The stages are summarized in Figure 1 and
described in turn below.
2.1.1. Stage 1: Define the purpose of the SLR
The purpose of the study has been stated above using the
research question. In addition, the justification has also been
given above by identifying existing literature reviews on SC
traceability to avoid the repetition of studies. In summary,
previous SLRs are limited to the consideration of benefits
relating to specific industries only or a specific technology
only. Hence the unique purpose of this study is to consider
multiple industries and technologies, to develop a more
comprehensive understanding of the benefits to guide
researchers and practitioners in the future. In addition, this
review is unique in exploring the relationship between trace-
ability and SCRes.
2.1.2. Stage 2: Develop the inclusion and/or exclu-
sion criteria
The criteria that determines whether a publication can pro-
vide information to answer the research questions was
defined in advance of the actual literature search to avoid
manipulating procedures based on the researchers expecta-
tions (Tranfield, Denyer, and Smart 2003; Kitchenham and
Charters 2007; Durach, Kembro, and Wieland 2017).
Therefore, the literature sources, journal quality and search
words were specified at this stage.
Literature Sources: Scopus was the main search engine for
this study because it is an up-to-date database of relevant
journals. This was supplemented with the OneSearch
Library, which also incorporates a range of major business
and management databases such as EBSCOhost,
SpringerLink, Science Direct, IEEE Xplore, Emerald Insight
and Wiley Online Library. Despite the sophistication of
each search engine, combining them widened the cover-
age and improved the search results.
Keywords: The keywords were selected considering other
terms that could be used to refer to traceability.
Therefore, they were specified as: Trac(trace, track, trac-
ing, tracking, traceability etc.) OR Transparen(transpar-
ent, transparency etc.) OR Visib(visible, visibility etc.) OR
Recall(recall, recalls etc.) AND Supply Chain(supply
chain, supply chains etc.). The truncation symbol ()
ensured the inclusion of different endings to the search
term. It is also noted that the keywords focussed entirely
on traceability, with SCRes literature linked to traceability
identified in this way. A search of the SCRes literature
was also carried out, but this is not included here as it
did not significantly add to the findings.
Journal Quality: To ensure the quality and relevance of
the search results, only studies published in Association
of Business Schools (ABS) ranked journals were included.
This meant that all studies were internationally peer-
reviewed and published in English.
2.1.3. Stage 3: Identify potentially relevant literature
The search string TracOR TransparenOR VisibOR
RecallAND Supply Chainwas entered into Scopus and
OneSearch with the search directed to the Description(i.e.
title, keywords and abstracts). The searches retrieved 854
and 465 peer-reviewed articles from Scopus and OneSearch,
respectively. Mendeley reference management software was
used to keep a log of the retrieved articles and further man-
age the references cited.
Reporng the Results
Wring up the SLR into an understandable format for the target audience
Data Extracon and Synthesis
Microso Excel spreadsheet used to extract the relevant informaon from selected papers (n=107)
Select Relevant Studies
Eliminate Duplicates
(n=920) Eliminate by tle (n=535) Read Abstract and Conclusion
(n=236) Read full text (n=107)
Idenfy Potenally Relevant Studies
Scopus Search Results: (n=926) OneSearch Search Results: (n=505)
Develop Inclusion/Exclusion Criteria
Journal Quality: Must be an ABS
approved journal
Source of Literature: Scopus and
OneSearch Library
Keywords searched in the
“Descripon” (i.e. tle, keywords
and abstracts).
Define the Purpose of the SLR
Scoping study to idenfy the current state of knowledge
and research gaps
Guides the formulaon of the review quesons and
avoids the possibility of a repeon of exisng studies
Figure 1. Systematic literature review process.
2.1.4. Stage 4: Select relevant studies
The inclusion and exclusion criteria for this study involved
passing the 1,319 (854 þ465) articles through screening
stages to assess them individually for their relevance to the
research question. With regards to inclusion and exclusion at
each stage, the papers had to fit the definition of traceability
as coined in the introduction above. This led to the removal
of several papers because some of the keywords, such as
transparency,visibility,tracking and tracingand even
traceabilitydid not necessarily refer to the type of traceabil-
ity in question. Articles clearly addressing the role, purpose,
impact or benefits of a traceability system or a specific trace-
ability technology were selected. However, any such articles
that were not related to supply chain management were
excluded such as on the use of blockchain in cryptocurren-
cies, or the use of RFID for race timing or attendee tracking.
The stages followed were:
1. The articles were cross-checked to eliminate duplicates
retrieved from multiple databases. This reduced the
number of articles to 920 studies.
2. The articles were screened by their titles and keywords
for their potential relevance reducing the number of
articles to 535 studies.
3. The abstracts and conclusions were read to determine
their potential relevance, reducing the set further to 236
articles. To avoid excluding relevant articles, studies for
which there was any doubt on whether or not to
exclude them were retained and passed on to the final
screening stage.
4. Finally, the remaining articles were fully read to deter-
mine their relevance.
107 articles were finally selected and passed on for extrac-
tion and analysis.
2.1.5. Stage 5: Data extraction and synthesis
This SLR used a Microsoft Excel spreadsheet to record and
monitor the data obtained from the selected studies. This cat-
aloguing also provides an audit trail to map the claims made
in the SLR to the source of the evidence (Denyer and
Tranfield 2009). The findings of the primary studies were then
analysed and integrated to answer the research question.
3. Overview of the current state-of-the-art
regarding SC traceability
3.1. Summary of literature descriptive analysis
This section evaluates the descriptive characteristics of the
selected papers to generate an overview of the selected
sample to ensure consistency in the content analysis
(Durach, Kembro, and Wieland 2017; Seuring and Gold 2012).
Table 1 below provides a statistical summary of these charac-
teristics to illustrate that the traceability literature is a vibrant
research area with publications in highly ranked journals.
The SLR selected 107 papers dated between 1998 and
2021, of which 50 percent (54 papers) were published
between 2016 and 2021, indicating that traceability related
studies are still a significant research focus. Geographically,
Europe accounted for most papers (44) whereas Africa and
Oceania had the least research focus with 2 and 1 paper
respectively. This indicates that studies on traceability have
usually been centred on developed countries whilst develop-
ing countries have received little or no attention. This may
be due to the relative level of consumer agitation and
demands for traceability from the respective SCs.
The sample also exhibited a balance of qualitative and
quantitative methods with case studies (37) representing the
most used method whilst experiments (2) were the least
used methods. 95 papers adopted a single method whereas
only 12 papers adopted a mixed method.
Furthermore, 79 papers addressed the issues from a spe-
cific industrial perspective with the food industry accounting
for most studies (45 papers), followed by studies carried out
across industries(11 papers). The healthcare industry also
accounted for 5 studies whilst mining, leather, and the trans-
port and aviation sectors had the lowest number of studies
with 1 each. The dominance of the food industry can be
attributed to an increase in societal attention because of the
monetary and health implications of previous food scares
and the test-runs of new technologies in the food SCs
(Ringsberg 2014; Casino et al. 2020; Kayikci et al. 2020).
3.1.1. Adoption of theoretical lenses in the traceabil-
ity literature
Only 16 of the 107 papers explicitly referred to the use of a
theoretical lens, with one paper adopting 3 theoretical
approaches, as shown in Table 2. This shows that studies in
this area have not significantly considered a theoretical
approach. However, 12 out of the 16 studies that did use a
theoretical lens were published between 2016 and 2021, sig-
nalling an increasing drive towards the use of theories over
the last 5 years. As shown in Table 2 below, resource-
focussed theories account for 8 papers with the Resource
Based View (RBV) being the most applied theory. This sug-
gests a view of traceability systems as a unique resource
controlled by a firm to gain competitive advantage. Beyond
the resource focussed perspectives, Transaction Cost
Economics (TCE) was also adopted in 3 papers to justify
implementing traceability systems using Cost-Benefit Analysis
(CBA), whereas stakeholder theory (2 papers) was used to
indicate the drivers of traceability and their role in determin-
ing its adoption.
3.1.2. SC tiers studied in empirical papers
This study identified 5 tiers of the SC that served as the
focus of data collection consumers, traders (wholesalers
and retailers), distributors, manufacturers/processors and sup-
pliers. Only 19 out of the 64 empirical papers that were iden-
tified focussed on more than one tier, as shown in Table 3
below. Thus, empirical studies primarily focussed on a single
tier, meaning the findings were generally limited to firm-
based data and were not conclusive across the SC.
The distribution of papers across the tiers is summarized
in Table 4 below. This table shows that most studies
focussed on manufacturing/processingwhereas the end
downstream tier consumershad the least focus. The extant
literature also confirms that there is a stronger incentive to
implement traceability among upstream enterprises than
among downstream firms (Ringsberg 2015).
3.2. Drivers/motivations to adopt traceability systems
The motivations/drivers (also referred to as incentives) of
traceability systems are the forces that influence stakeholder
interest in the implementation of traceability systems
(Mattevi and Jones 2016). They can also serve as a yardstick
against which the benefits of traceability can be measured to
determine whether the desired goals for its implementation
have in fact been achieved. It is therefore important to
understand the various factors that drive the initial interest
in order to appreciate the perceived benefits of traceability.
The drivers identified in this SLR are summarized in Figure 2
below. This figure builds on the terminology used in the
extant literature, fully collating the research to date, and
thereby presents a novel holistic nomenclature that high-
lights the various drivers identified and their hierarchical
3.2.1. Internal factors
Internal factors are the motivations that stem out of a firm/
SCs pursuit of improved effectiveness through the real-time
exchange of information (Mattevi and Jones 2016). In turn,
this improved effectiveness aims to lower transaction costs
and risks associated with SC vertical interactions (Stranieri,
Table 1. Descriptive analysis of the literature.
Year period Continents Research methods Industry of focus Journals
Up-to-2000 (3)
20012005 (1)
20062010 (19)
20112015 (30)
20162021 (54)
Africa (2)
Asia (23)
Europe (44)
South America (3)
North America (11)
Oceania (1)
Action (3)
Case Study (37)
Modelling (25)
Simulation (3)
Conceptual (13)
Experiment (2)
Lit. Review (13)
Survey (25)
Across Industries (11)
Automotive Manufacturing (3)
Consumer Goods (2)
Electronics (2)
Fashion (3)
Food (45)
Forestry (3)
Healthcare (5)
Leather (1)
Mining (1)
Service (2)
Transport & Aviation (1)
British Food Journal (13)
Supply Chain Management: An International Journal (12)
International Journal of Production Economics (10)
International Journal of Production Research (10)
Journal of Cleaner Production (8)
International Journal of Physical Distribution & Logistics
Management (7)
Industrial Management & Data Systems (7)
Production Planning and Control (5)
Supply Chain Forum: An International Journal (5)
Computers in Industry (4)
Production and Operations Management (3)
Others (23)
Total ¼107 Subtotal ¼84 Total ¼121Subtotal ¼79 Total ¼107
Notes:(n): nrepresents the number of studies; some studies used more than one research method.
Table 2. The distribution of articles based on theoretical approaches adopted.
Theory Count Papers
Adoption Theories 2 (Kar^
aa and Morana 2016; Kamble, Gunasekaran, and Arha 2019)
Agency Theory 1 (Resende-Filho and Hurley 2012)
Diffusion of Innovation Theory 1 (Kar^
aa and Morana 2016)
Enactment Theory 1 (Oliveira and Handfield 2017)
Normal Accident Theory 1 (Skilton and Robinson 2009)
Resource Based View (RBV) 5 (Brofman Epelbaum and Garcia Martinez 2014; Timmer and Kaufmann 2017; Dubey et al.
2018,2019; Agyabeng-Mensah et al. 2020)
Resource Dependency Theory 2 (Kamble, Gunasekaran, and Gawankar 2020; Agyabeng-Mensah et al. 2020)
Resource Orchestration Theory 1 (Bradley et al. 2018)
Stakeholders Theory 2 (Kar^
aa and Morana 2016; Timmer and Kaufmann 2017)
Systems Theory 1 (Fatorachian and Kazemi 2021)
Transaction Cost Theory 3 (Banterle and Stranieri 2008; Vo, Mainetti, and Fenies 2016; Stranieri, Orsi, and Banterle 2017)
Total Papers using Theory 15
Table 3. Studies that focussed on two or more tiers.
Number of tiers Count Papers
2 Tiers 10 (Bottani, Montanari, and Volpi 2010; Canavari et al. 2010; Mai et al. 2010; Azevedo et al. 2013; Hinkka, Fr
and T
a2013; Kumar, Heustis, and Graham 2015; Ringsberg 2015; Scholten and Schilder 2015; Sander,
Semeijn, and Mahr 2018; Hoek 2019)
3 Tiers 5 (K
ainen et al. 2007;Bj
ork et al. 2011; Papert, Rimpler, and Pflaum 2016; Vanany et al. 2016; Wowak,
Craighead, and Ketchen 2016)
4 Tiers 4 (Simpson, Muggoch, and Leat 1998; Brofman Epelbaum and Garcia Martinez 2014; Ringsberg and Mirzabeiki
2013; Gunawan, Vanany, and Widodo 2021)
Table 4. Distribution of empirical papers based on supply chain
tier researched.
SC tier No of papers
Consumers 1
Traders (wholesalers & retailers) 22
Distributors 14
Manufacturing/Processing 50
Suppliers 18
Cavaliere, and Banterle 2016). The internal factors were sub-
categorized as either monetary or non-monetary mar-
ket incentives.
Non-monetary market incentives encompass the drivers that
cannot be directly quantified economically and have no bearing
on profit in the short-to-medium term (Stranieri, Cavaliere, and
Banterle 2016).TheliteraturepointstofirmandSCbrandcom-
petitiveness, product complexity and SC entry requirements as
the main non-monetary elements that drive traceability systems
(Stranieri, Cavaliere, and Banterle 2016; Resende-Filho and
Hurley 2012; Manos and Manikas 2010;Maietal.2010;Mattevi
and Jones 2016). The most significant internal drivers were var-
ied across studies depending on the nature of the sample of
companies studied (Manos and Manikas 2010;Matteviand
Jones 2016)for example, small-sized firms may not necessarily
invest in traceability for long-term gains (such as to improve
brand image or competitiveness). Traceability may also be
driven by the dominant actors within the SC when they impose
a traceability system on other actors as a SC entry requirement
(Sun and Wang 2019; Heyder, Ludwig and Thorsten 2012;
Canavari et al. 2010). For instance, food retailers such as ASDA,
Morrisons and Walmart may require all suppliers to adopt a
traceability system.
Monetary market incentives are the drivers that can be easily
quantified economically within the firm and SC (Stranieri,
Cavaliere, and Banterle 2016; Brofman Epelbaum and Garcia
Martinez 2014; Canavari et al. 2010).Driversinthiscategory
were either to increase firm profits or to improve SC efficiency
(Stranieri, Cavaliere, and Banterle 2016; Brofman Epelbaum and
Garcia Martinez 2014; Canavari et al. 2010). Firstly, increasing
short-term drivers such as the desire to reduce costs and elimin-
ate liabilities associated with SC failures, (e.g. the cost of recalls,
financial penalties and damage to market share) (Mai et al.
2010; Stranieri, Cavaliere, and Banterle 2016;Kayikcietal.2020).
Secondly, companies consider the tracking and swift transmis-
sion of information among SC actors as a value-adding activity
that impacts SC efficiency (Hinkka, Fr
amling, and T
Hence, firms that seek to improve operations and become more
efficient are motivated to adopt traceability systems.
3.2.2. External factors
These are factors beyond the control of a firm and its SC
partners that influence the adoption of traceability systems.
They range from mandatory and imposed drivers, such as
local and international regulations, quality and safety stand-
ards set by government and NGOs, through to voluntary
standards (Manos and Manikas 2010; Donnelly, Mari Karlsen,
and Dreyer 2012; Mattevi and Jones 2016); and also include
technological advances and customer concerns, as summar-
ized in Figure 2.
Mandatory regulatory drivers refer to requirements
imposed on firms and SCs that do business within a geo-
graphical area i.e. either locally (within a country) or inter-
nationally (within a continent) (Stranieri, Cavaliere, and
Banterle 2016; Mattevi and Jones 2016). These enforcements
to a large extent are aimed at ensuring the assurance of
product quality and safety, and hence are usually limited to
the minimum requirement of tracing one tier in both direc-
tions i.e. one-up, one-downtraceability (Mattevi and
Jones 2016; Vo, Mainetti, and Fenies 2016).
The global recognition and prestige attached to voluntary
standards and certifications, such as the Codex Alimentarius
Commission (CAC), the International Organization for
Standardization (ISO), the Marine Stewardship Council (MSC),
the Global Standardization Organization 1 (GS1), and the
Global Good Agricultural Practices (GLOBALG.A.P.) also drives
the implementation of traceability systems. That is, since firms
seek certification by such bodies to assure SC partners and
consumers of their adherence to the highest standards of
operations, they are driven to comply with the requirements
of these bodies, which includes the deployment of traceability
systems (Ringsberg 2015; Mattevi and Jones 2016; Kar^
aa and
Morana 2016; Stranieri, Cavaliere, and Banterle 2016).
The user-friendliness, availability, effectiveness and other
characteristics of traceability technology play a vital role in
its implementation (Manos and Manikas 2010; Mattevi and
Jones 2016; Kittipanya-Ngam and Tan 2020). Although trace-
ability can be achieved without technology, to ensure the
efficiency of the system and its ability to deliver information
as quickly as possible, there is the need to integrate appro-
priate technology (Kar^
aa and Morana 2016). Thus, as
Technology Consumer
Quality and
and Ethical
costs and
SC entry
Figure 2. Categorization of the drivers/Motivations of traceability systems.
advances in technology are developed and become available,
this can drive the adoption of either new or improved trace-
ability systems.
Traceability systems are also driven by the need to address
consumer concerns relating to health and safety, ethical and
religious beliefs (Folinas, Manikas, and Manos 2006; Pouliot
and Sumner 2008; Ringsberg 2015). In recent years, consumer
purchase decisions have become increasingly based on the
assurance that there is adequate information regarding the
provenance of what they procure (Folinas, Manikas, and
Manos 2006; Mai et al. 2010; Kayikci et al. 2020). Although
traceability does not improve the quality and safety of a prod-
uct per se, it assures consumers and other stakeholders of
safety and quality given its effectiveness in swiftly recalling or
withdrawing products during crises (Folinas, Manikas, and
Manos 2006; Manos and Manikas 2010; Ringsberg 2015).
Religious and ethical concerns of consumers also drive trace-
ability adoption as, for example, consumers are interested in
evidence of adherence to animal welfare certifications
(Bumblauskas et al. 2020; Kittipanya-Ngam and Tan 2020).
3.2.3. Use of theory in understanding drivers
aa and Morana (2016), drawing from the theory of adoption
and diffusion of innovation, suggest that despite the signifi-
cance of technology, the adoption of traceability depends on a
firms internal readiness (as included under the heading of
internal resourcesin Figure 2). Thus, they confirm the role of
internal management with the CEO as the champion(Rogers,
2003, cited in Kar^
aa and Morana 2016). Notwithstanding the
sophistication of a technology, the CEO is still critical since he/
she is an internal actor and can easily transcend his/her per-
sonality to encourage staff to adopt the technology. Timmer
and Kaufmann (2017), based on Stakeholder and RBV theories,
also asserted that the final decision on traceability systems
depends on the internal motivations; thus, external stakeholder
salience supplements the internal resources available.
Furthermore, the use of TCE theory highlights the monetary
drivers of traceability. Stranieri, Orsi, and Banterle (2017)argued
that traceability standards are a transaction governance mech-
anism adopted as a tool to reduce transaction costs (profits)
and manage transaction risks (SC efficiency). Hence, a firms
perception about transaction risks determines the choice of
traceability system, emphasizing that internal risk is positively
related to the complexity of the traceability technology
adopted. This perspective also highlights the risk of opportun-
istic behaviour by dominant SC actors and related inter-firm
risk (Banterle and Stranieri 2008). Vo, Mainetti, and Fenies
(2016) and Banterle and Stranieri (2008) added that the imple-
mentation of a traceability system directly impacts three trans-
action attributes as it: augments asset specificity; decreases the
level of uncertainty; and augments transaction frequency.
3.3. Evolution and contribution of technology to
traceability systems
The choice of traceability technology determines the
breadth, depth and efficiency of a traceability system, and
therefore is a critical aspect of the impact of traceability on
SC performance (Banterle and Stranieri 2008; Manos and
Manikas 2010). The evolution of traceability systems from
paper-based to IT-enabled devices has enhanced the ability
and efficiency of firms in collecting relevant information and
keeping track (Banterle and Stranieri 2008; Manos and
Manikas 2010; Kayikci et al. 2020). This evolution began in
industries like pharmaceuticals and has now also been
adopted in other industries such as food, thereby helping to:
reduce the errors associated with manual handling; improve
the transmission and analysis of large volumes of data; and
improve tracking (Wilson and Clarke 1998; Manos and
Manikas 2010).
From an RBV perspective, a firms ability to create a valu-
able, rare, inimitable and non-substitutable resource from a
traceability system, and hence to gain competitive advan-
tage, depends on its embedded technology (Brofman
Epelbaum and Garcia Martinez 2014). However, from the
Resource Orchestration Theory (ROT) perspective, Bradley et
al. (2018) argued that obtaining technology (resource) does
not guarantee competitive advantage until it is effectively
bundledand leveraged. Thus, effectively integrating tech-
nologies was more likely to improve traceability systems
faster than simply adopting new technologies since users
attitude towards new technology is likely to affect its useful-
ness (Shou et al. 2021). This confirms the theoretical model
developed by Kamble, Gunasekaran, and Arha (2019) based
on the integration of three adoption theories the technol-
ogy acceptance model (TAM), technology readiness index
(TRI) and the theory of planned behaviour (TPB) - which
infers that the attitude of the traceability technology users
towards its adoption is positively linked to its perceived use-
fulness, which is also influenced by its perceived ease of use.
Expanding on the identification and/or communication
functions of traceability technology, as recognized by earlier
literature (e.g. Brofman Epelbaum and Garcia Martinez 2014),
Papert, Rimpler, and Pflaum (2016) identified six functional
capabilities that a traceability technology may exhibit
depending on its characteristics. Table 5 below assesses the
identified technologies based on these functional capabilities.
The table confirms the evolution of technologies and an
associated significant improvement in functional capabilities
(George et al. 2019). New technologies do not always
replace/wipe out existing technologies instead both may
remain as complements of each other, as seen in the case of
RFID and barcodes.
Although no technology was limited to a product or
industry (as shown in Table 6 below), some specific technolo-
gies are better aligned to certain products, based on their
unique characteristics, that require particular functional capa-
bilities (Papert, Rimpler, and Pflaum 2016; Musa,
Gunasekaran, and Yusuf 2014). For instance, Isotopic and
DNA-based technologies trace products using their unique
composition of isotopes (elements) and molecules, hence
they are mostly used in bio-products/industries such as agri-
food and forestry (Saikouk and Spalanzani 2016; George et
al. 2019). RFIDs do not require line-of-sight and can simultan-
eously identify multiple products, and hence can be effective
Table 5. Functional capabilities of traceability technologies.
Identification Locating Sensors Communication
storage Logic Description/ Appraisal
Stable isotopic technology xx xUses the unique isotopic compositions of a product to determine its provenance and authenticity (Saikouk and
Spalanzani 2016; George et al. 2019).
Complex to use for simple traceability since it requires laboratory tests to determine the provenance and the isotopic
composition of products (George et al. 2019).
DNA-based tracers x x A sophisticated tool for product verification that certifies a products origin and authenticity based on a DNA added
to the product (Saikouk and Spalanzani 2016; George et al. 2019).
Useful for traceability in the food industry for the identification of organic crops, livestock against adulterated and
genetically modified organisms (GMOs).
Not very effective with finished products composed of different raw materials with different origins (George et
al. 2019).
Nano-capsules x x Generates unique codes as molecular prints that are merged into a product for identification and authentication
(Saikouk and Spalanzani 2016).
Accommodates several codes, hence permits the effective reading of complex combinations.
Magnetic markers x x x Fuses silica-coated magnetic particles into a product during its manufacturing, to help identify and convey secured
information about a product along the SC (Saikouk and Spalanzani 2016).
Simple, safe, effective and generally a low-cost technology since the magnetic markers automatically generate a
unique readable code for the product (Saikouk and Spalanzani 2016).
Barcode (1D barcode) x x An optical technology that uses horizontal bars to represent, identify and encode product information.
Read-only technology, i.e. data printed cannot be modified along the SC.
The scanner requires a relatively short direct line-of-sight to the barcode, hence time consuming.
Does not guarantee the authenticity of products because its limited information density is liable to duplication
(Saikouk and Spalanzani 2016).
Matrix code (2D barcode) x x x An optical technology that uses geometric patterns in two dimensions to represent, identify and store product
The codes represent data such as a product number, charge number, serial number, expiry date, etc.
2D barcodes encode more information than a 1D barcode.
The simplicity, universality and low cost of barcodes explains its popularity despite its deficiencies (Musa,
Gunasekaran, and Yusuf 2014).
Labels easily become unreadable since they are usually exposed to weather and other conditions that cause wear
and tear (Kumar, Heustis, and Graham 2015).
Data logger x x x x Sensor-driven devices used to measure and store temperature profiles of a product along the SC (Papert, Rimpler,
and Pflaum 2016).
The sensor records and saves temperature at defined intervals (communication and storage) but is unable to regulate
extreme high or low temperature (logic) (Papert, Rimpler, and Pflaum 2016).
Lacks the basic function of identification unless merged with another technology.
RFID x x x x Referred to as the next-generation barcodebecause of its enhanced features.
Enables the simultaneous automatic identification of multiple objects without direct contact (Kumar, Heustis, and
Graham 2015).
Saves cost with reusable tags instead of labels and stickers (Ringsberg and Mirzabeiki 2013).
Allows modification of product information as it moves along the SC (Gautam et al. 2017).
Despite its functional limitations, it can be easily integrated with other devices to enhance its functionalities (Papert,
Rimpler, and Pflaum 2016).
The high investment required for its deployment is a disincentive for most SMEs (Kar^
aa and Morana 2016).
RFID tags are subject to being cloned and counterfeited and security may be undermined since it runs on wireless
networks (Azzi, Chamoun, and Sokhn 2019).
Wireless Sensor
Network (WSN)
xxx x xxIntegrated sensors with embedded product logic that combines with RFID to enhance traceability communication to
achieve real-time product monitoring along the SC (Yan et al. 2016; Papert, Rimpler, and Pflaum 2016).
Facilitates the outlay Internet of Things (IoT) an intelligent system that has proven to be capable of realising all the
six functional capabilities (Yan et al. 2016).
Relatively unpopular because its setup requires a completely new framework, hence new skills training, and
configuration to align with existing legislations within the SC (Papert, Rimpler, and Pflaum 2016).
for bulky products or palletized goods (Lee and
Ozer 2007;
Kang and Lee 2013). The continuing demands of traceability
from stakeholders mean that the system requires persistent
enhancement through innovation to ensure that it is con-
tinuously able to record and disseminate the information
required by authorized stakeholders.
To enhance the functionalities of traceability systems, an
existing system may serve as a grounded technological
framework that is integrated with other devices to upgrade
its functions instead of switching to the adoption of an
entirely new technology. RFIDs dominance as an underlying
technology is due to its ability to be integrated with other
traceability technologies, such as DNA and barcodes, as well
as sensory devices such as: Time Temperature Indicators
(TTI); electronic data-interchange (EDI); the internet-of-things
(IoT); and global positioning systems (GPS) (Mai et al. 2010;
Musa, Gunasekaran, and Yusuf 2014; Bradley et al. 2018;
George et al. 2019; Coronado Mondragon, Coronado
Mondragon, and Coronado 2021). Therefore, RFID technology
can be integrated with sensors to solve its lack of logic and
sensor functionality (Papert, Rimpler, and Pflaum 2016). For
example, in the case of RFID and TTI (Rf-TTI), TTI augments
the underlying capabilities of RFID (i.e. identification, loca-
tion, communication and data storage) with the ability to
monitor temperature (sensor) and recognize fluctuations that
impede quality (logic).
Papert, Rimpler, and Pflaum (2016) noted that despite the
desire for a technology that provides accurate and secure
information, companies also consider its ease of adoption
and alignment with their existing structure. Bradley et al.
(2018) stressed the value of joint useof newly adopted
technologies with other technologies already in use, arguing
that consistent use of such a bundled resourceis more
likely to lead to long term successful traceability. Thus, as a
technology meets the traceability needs over time, users
become more accustomed to it and hence more willing to
accept it (Musa, Gunasekaran, and Yusuf 2014; Kamble,
Gunasekaran, and Arha 2019).
To override the loopholes of the Auto-ID based technolo-
gies, blockchain technology (BCT) and the Internet of Things
(IoT) have emerged as essential underlying traceability tech-
nologies for the future, though some experts remain rather
pessimistic about expectations being fulfilled (Tsang et al.
2018; Pournader et al. 2020; Wang, Han, and Beynon-Davies
2019). This advancement in technology, enhances the trans-
parency and awareness of the SC and makes traceability
more capable in exploring larger volumes of data quickly
(Ivanov and Dolgui 2020; Shou et al. 2021). Despite some
failed attempts to implement BCT in industry, it continues to
have huge potential with some successful business cases
(Pournader et al. 2020). Likewise, IoT presents an expanded
system based on existing technology such as RFID, WSN,
barcodes etc. (Coronado Mondragon, Coronado Mondragon,
and Coronado 2021) that extends traceability beyond the
functional capabilities into a network infrastructure that ena-
bles it to connect both virtual and physical objects (Tsang et
al. 2018). It is therefore concluded that the potential ability
of traceability systems to provide significant firm and SC
Table 5. Continued.
Identification Locating Sensors Communication
storage Logic Description/ Appraisal
Blockchain technology (BCT) x x x x x x A peer-to-peer (distributed) ledger technology that provides SC actors within a blockchain network with enhanced
visibility and transparency of transactions, assets, stock items, etc. (Pournader et al. 2020).
Offers consistency and immutability of data, hence errors in records are minimised.
Reliable for product recalls because it facilitates the tracking of the origin of a product with accurate details of its
journey from the producer to final consumer (Azzi, Chamoun, and Sokhn 2019).
Eliminates paperwork and expedites contract fulfilment and payment through smart contracts (Hald and Kinra 2019).
BCT interfaces are complex, hence requires some level of blockchain knowledge to fully appreciate its potential
(Chang, Iakovou, and Shi 2020).
Excessive transparency may lead to powerful SC actors unduly monitoring and dominating surveillance to the
detriment of the less powerful firms (Hald and Kinra 2019).
Its enhanced automation eliminates nearly all forms of human intervention, which has adverse effects on worker skills
and competencies (Hald and Kinra 2019).
Notes: Identification: To determine the unique identity information about a product; Locating: to determine timely and accurate information about the position of a product; Sensors: to determine the current object and
environmental-related status of the product; Communication: to assess and exchange product information among SC actors; Data storage: retention of product history and other information to facilitate information shar-
ing in real-time; Logic: recognition of the critical events in the journey of a product (temperature fluctuations, quality issues, etc.).
level benefits continues to expand as the technologies them-
selves continue to evolve.
3.4. Challenges/barriers to the adoption of
traceability systems
Despite the remarkable improvements that firms and SCs
desire from the implementation of traceability systems, and
the capabilities of the technologies themselves, it is also
worth noting that there are several challenges/barriers associ-
ated with technology adoption that may hamper the associ-
ated benefits. Thus, there can be a difference between
expected and actual outcomes. The various challenges/barriers
encountered in the implementation of traceability systems
can be summarized in four categories, as previously applied
to the categorization of the challenges associated with block-
chain technology adoption identified by Saberi et al. (2019):
1. Challenges Internal to the firm (Intra-Firm);
2. Challenges Internal to the SC (Inter-Firm);
3. Technical/System Related Challenges; and,
4. External Challenges.
3.4.1. Intra-firm challenges
Implementing a traceability system usually involves a reconfig-
uration of the internal operations with new technology and
new skill-sets, and hence there is a need for step-
by-step guidelines prior to implementation (Manos and
Manikas 2010;Guoetal.2015). Obstacles to implementation
are therefore likely to emanate internally from the firmsfinan-
cial capacity and the attitude of both management and
employees (Saberi et al. 2019). These include: financial con-
straints (Mattevi and Jones 2016; Accorsi et al. 2018;Kayikciet
al. 2020); lack of management commitment (Guo et al. 2015;
Saberi et al. 2019); employee resistance to change (Alfaro and
abade 2009;Kwoketal.2010); and the lack of required skill
and expertise (Canavari et al. 2010;Saberietal.2019;Kayikci
et al. 2020).
3.4.2. Inter-firm challenges
Efficient traceability systems harness inter-firm relationships
to create value for stakeholders (Saberi et al. 2019). However,
organizational differences and the individual rights of firms
along the SC pose challenges to the implementation of
traceability systems. Amongst these challenges are: ethical
and privacy concerns due to a lack of trust among SC part-
ners (Sanfiel-Fumero, Ramos-Dominguez, and Oreja-
ıguez 2012; Hald and Kinra 2019; Chang, Iakovou, and
Shi 2020; Shou et al. 2021); the uneven distribution of costs
and benefits of the implementation (Mai et al. 2010; Sanfiel-
Fumero, Ramos-Dominguez, and Oreja-Rodr
ıguez 2012;
Hinkka, Fr
amling, and T
a2013); and the reluctance of SC
partners to sacrifice their internal policy for the advantage
of the SC (Canavari et al. 2010; Gunawan, Vanany, and
Widodo 2021).
Table 6. Technologies adopted and the industrial contexts studied.
Technology Industry (product) Sources
Barcode Food SC (Vanany et al. 2016; Li et al. 2017)
Forestry SC (Saikouk and Spalanzani 2016)
General SC (Li 2013; Musa, Gunasekaran, and Yusuf 2014; Choi, Yang, and Cheung 2015; Dai, Ge, and Zhou 2015; Dai,
Tseng, and Zipkin 2015)
Blockchain Food SC (Sander, Semeijn, and Mahr 2018; Behnke and Janssen 2020; George et al. 2019; Feng et al. 2020; Casino et al.
2020; Kayikci et al. 2020; Kittipanya-Ngam and Tan 2020)
General SC (Hald and Kinra 2019; Azzi, Chamoun, and Sokhn 2019; Chang, Iakovou, and Shi 2020; Hastig and Sodhi 2020;S.
Kamble, Gunasekaran, and Arha 2019; Pournader et al. 2020; Saberi et al. 2019; Hoek 2019; Wang, Han, and
Beynon-Davies 2019)
DNA-based Tech. Forestry SC (Saikouk and Spalanzani 2016)
IoT Food SC (Tsang et al. 2018; Coronado Mondragon, Coronado Mondragon, and Coronado 2021; Kittipanya-Ngam and
Tan 2020)
General SC (Fatorachian and Kazemi 2021)
Isotopic Technology Forestry SC (Saikouk and Spalanzani 2016)
Magnetic Tracing Forestry SC (Saikouk and Spalanzani 2016)
Nano-Capsules Forestry SC (Saikouk and Spalanzani 2016)
RFID Automotive (Modr
ak and Moskvich 2012)
Fashion SC (Guo et al. 2015; Landmark and Sjøbakk 2017)
Food SC (Kelepouris, Pramatari, and Doukidis 2007; Mai et al. 2010;Ringsberg and Mirzabeiki 2013; Yan et al. 2016;
Gautam et al. 2017; Li et al. 2017)
Forestry SC (Bj
ork et al. 2011; Appelhanz et al. 2016; Saikouk and Spalanzani 2016)
General SC (Spekman and Sweeney 2006; Attaran 2007; Lee and
Ozer 2007; Lee and Park 2008; Lee and Lee 2010; Hong,
Kim, and Kim 2010; Cui et al. 2017; Dai, Ge, et al. 2015; Musa, Gunasekaran, and Yusuf 2014; Kang and Lee
2013;Li2013; Shi et al. 2012)
Healthcare (Hospital) (Bradley et al. 2018)
Manufacturing SC (Dai, Tseng and Zipkin 2015; Liukkonen 2015)
Pharmaceutical SC (Kwok et al. 2010; Papert, Rimpler, and Pflaum 2016)
Retail SC (Bottani, Montanari, and Volpi 2010)
WSN Pharmaceutical SC (Papert, Rimpler, and Pflaum 2016)
Food SC (Coronado Mondragon, Coronado Mondragon, and Coronado 2021)
Unspecified technologies
Food Trak Food (Wilson and Clarke 1998)
Sanitel Food (Viaene and Verbeke 1998)
3.4.3. Technical/system related challenges
As traceability systems have evolved from paper-based systems
to be more IT-enabled system, their implementation has also
faced challenges that stem from the use of IT tools and sys-
tems (Saberi et al. 2019). Notable challenges under this cat-
egory include: technological limitations in capacity and the
availability of suitable technology (Bentahar, Benzidia, and
Fabbri 2016;Wowak,Craighead,andKetchen2016; interoper-
ability challenges (Musa, Gunasekaran, and Yusuf 2014; Chang,
Iakovou, and Shi 2020;vanHoek2019; Gunawan, Vanany, and
Widodo 2021); depreciation of technology (Liukkonen 2015),
and security challenges (D. Lee and Park 2008;Li2013;Saberi
et al. 2019; Azzi, Chamoun, and Sokhn 2019;vanHoek2019).
3.4.4. External challenges
This category of challenges refers to the challenges that arise
from stakeholders and entities that do not directly economic-
ally benefit from a firm and its SC activities (Saberi et al.
2019). External bodies like government, industrial stakehold-
ers and other NGOs have a critical role to play in ensuring
the effectiveness of traceability systems, and hence when
there is a lack of clearly defined governmental policy on
traceability (Kwok et al. 2010; Chang, Iakovou, and Shi 2020;
Saberi et al. 2019; Gunawan, Vanany, and Widodo 2021) and/
or no unified industrial standard (Bentahar, Benzidia, and
Fabbri 2016; Accorsi et al. 2018; Saberi et al. 2019), this lack
of clarity will also act as a barrier to the successful imple-
mentation of traceability systems.
In conclusion, although firms expect to reap benefits from
their investments in traceability systems, it is important to note
that the challenges described above may hinder system
effectiveness. It is therefore important to have an overview of
these challenges and to be fully aware that these challenges
are inherent not only at the adoption stage but also varied
across the lifespan of the traceability system. It is also import-
ant to note that financial constraints, as identified as the princi-
pal impediment to the implementation of traceability systems
(Kwok et al. 2010; Mattevi and Jones 2016), should not be lim-
ited to only the initial purchase cost but also include other
aspects of implementation, such as the cost of staff training,
skills upgrading, administrative and legal costs associated with
information accessibility (Kayikci et al. 2020).
4. Benefits resulting from the implementation of
As discussed above, a firm may be driven to adopt traceability
by many factors which, to a large extent, determines the
choice of traceability technology i.e. either they adopt a basic
or an advanced traceability system. Despite the unique advan-
tages of these technologies, the benefits of the traceability sys-
tem can only be fully obtained through the effective bundling
and integration of the traceability resources (Bradley et al.
2018). The potential rewards firms desire from the implementa-
tion of traceability systems must sufficiently outweigh the chal-
lenges and barriers they must overcome to achieve them.
This section discusses the perceived benefits generated from
the effective implementation of a traceability system. The
papers reviewed here highlighted various qualitative and quan-
titative benefits, which were then classified based on the
nomenclature of Mattevi and Jones (2016)(1) impact on crisis
management, (2) impact on firm/SC performance, and (3)
Table 7. Benefits of traceability.
Category Benefits of traceability Example authors
Impact on
crisis management
Improved monitoring
and visibility
(Attaran 2007; Kher et al. 2010; Ringsberg 2014; Dubey et al. 2018; Kamble, Gunasekaran, and Arha
2019; Kayikci et al. 2020; Ivanov and Dolgui 2020; Kittipanya-Ngam and Tan 2020; Coronado
Mondragon, Coronado Mondragon, and Coronado 2021; Sumukadas 2021)
Efficient recall management (Kher et al. 2010; Mai et al. 2010; Dai, Tseng, and Zipkin 2015; Kumar, Heustis, and Graham 2015;
Bumblauskas et al. 2020; Casino et al. 2020; Kayikci et al. 2020; Sumukadas 2021)
Assurance of product safety
and quality
(Folinas, Manikas, and Manos 2006;Kher et al. 2010; Mattevi and Jones 2016; Sun and Wang 2019;
Agyabeng-Mensah et al. 2020; Kayikci et al. 2020; Coronado Mondragon, Coronado Mondragon,
and Coronado 2021; Shou et al. 2021)
Eliminate counterfeiting
and fraud
(Li 2013; Hald and Kinra 2019; Hastig and Sodhi 2020; Kayikci et al. 2020; Yao and Zhu 2020)
Impact on firm & SC
Reduced operations cost (Mai et al. 2010; Modr
ak and Moskvich 2012; Appelhanz et al. 2016; Kurniawan et al. 2017; Bradley
et al. 2018; Feng et al. 2020; Casino et al. 2020; Fatorachian and Kazemi 2021)
Reduced risk of SC disruption
inventory inaccuracy
(Jonsson and Mattsson 2013; Chang, Iakovou, and Shi 2020; Pournader et al. 2020; Ivanov and
Dolgui 2020; Kamble, Gunasekaran, and Gawankar 2020; Kayikci et al. 2020; Kittipanya-Ngam and
Tan 2020; Yao and Zhu 2020; Coronado Mondragon, Coronado Mondragon, and Coronado 2021;
Fatorachian and Kazemi 2021; Shou et al. 2021; Sumukadas 2021)
Real-time asset tracking (Bradley et al. 2018; Hald and Kinra 2019; Fatorachian and Kazemi 2021)
Enhanced SC trust and
confidence (collaboration)
(Alfaro and R
abade 2009; Kumar, Heustis, and Graham 2015; Feng et al. 2020; Casino et al. 2020;
Kittipanya-Ngam and Tan 2020)
Improved reliability
and security
(Li 2013; Bentahar, Benzidia, and Fabbri 2016; Casino et al. 2020; Kayikci et al. 2020; Fatorachian
and Kazemi 2021)
Improved brand image (Banterle and Stranieri 2008; Kumar, Heustis, and Graham 2015; Saak 2016; Wowak, Craighead, and
Ketchen 2016; Kayikci et al. 2020; Kittipanya-Ngam and Tan 2020; Coronado Mondragon,
Coronado Mondragon, and Coronado 2021)
Impact on consumers
& society
Improved retainment and
attraction of new customers
(Marucheck et al. 2011; Appelhanz et al. 2016; Landmark and Sjøbakk 2017; Bumblauskas et al.
2020; Kittipanya-Ngam and Tan 2020)
Evidence of sustainable/
ethical production/
sourcing methods
(Cousins et al. 2019; Saberi et al. 2019; Gunawan, Vanany, and Widodo 2021; Kittipanya-Ngam and
Tan 2020)
Improved reverse logistics and
(Rotunno et al. 2014; Dai, Ge, et al. 2015; Agyabeng-Mensah et al. 2020; Sumukadas 2021)
impact on consumers/society. For each of these categories,
novel sub-categories were then also developed, as summarized
in Table 7. These benefits are discussed in turn below
4.1. Impact on crisis management
This category of benefits of traceability relates to the expedi-
ency and efficiency that traceability systems present to SC
stakeholders in the event of a crisis/disruption (Mattevi and
Jones 2016). Thus, it includes the combination of benefits
that relate to: prevention of the crisis, containmentduring
the crisis, and quickly recovering from the crisis. As summar-
ized in Table 7, dominant benefits include improved moni-
toring and visibility, given that traceability systems enhance
the monitoring of the physical conditions (such as weight,
temperature and texture) of a product in transit or storage
(Mai et al. 2010; Ringsberg and Mirzabeiki 2013; Kumar,
Heustis, and Graham 2015). In particular, traceability is essen-
tial for the visibility of longSCs to inform on who made it,
what was made,when it was madeand its real-time loca-
tion (Tse and Tan 2012; Sumukadas 2021) which are essential
during crisis management. In particular, a lack of visibility
and control procedures will hinder effective decision making
because detailed knowledge of what is happening at other
parts of the SC is not available.
Product recalls represent a major crisis event for manufac-
turers and their SCs which have a negative bearing on share-
holder value, a products brand, firm profits and goodwill
among customers (Donnelly, Mari Karlsen, and Dreyer 2012),
especially in cases of mass media coverage. There is there-
fore a need for preparedness to swiftly withdraw defects
from the market to minimize the impact (Kumar, Heustis,
and Graham 2015). Product recall management is effective
when it efficiently combines the identification of the prob-
lem, mitigation of the risk and learning from the recall
(Marucheck et al. 2011; Casino et al. 2020). Researchers have
asserted that identifying a problem requires the collaborative
efforts of SC partners through sharing timely information on
potential malfunction issues (Marucheck et al. 2011; Kumar,
Heustis, and Graham 2015; Sumukadas 2021). Despite the
assertion that a traceability system does not reduce the likeli-
hood of a SC crisis (Resende-Filho and Hurley 2012), its role
in controlling the consequences by enabling rapid recalls of
harmful products cannot be overemphasized (Folinas,
Manikas, and Manos 2006; Sumukadas 2021). For example,
logistics information provided by traceability systems (such
as batch quantity, origin, destination and dispatch date)
ensures knowledge of the up-to-date location of a product
to facilitate its swift withdrawal from the market (Folinas,
Manikas, and Manos 2006; Ringsberg and Mirzabeiki 2013;
Dai, Ge, et al. 2015; Kumar, Heustis, and Graham 2015).
Traceability systems also serve as a quality verification
platform that firms can use to assure all concerned parties
that the product has duly followed the right production pro-
cedures and hence is safe for usage (Folinas, Manikas, and
Manos 2006; Sun and Wang 2019). In addition, it has the
ability to curb counterfeiting and fraud by securing the
integrity of the SC through effective monitoring and
ensuring that the right information can be accessed by SC
actors at the right time to verify the authenticity of the prod-
uct (Li 2013; Hald and Kinra 2019; Hastig and Sodhi 2020).
This role of traceability is particularly beneficial to the food,
beverage and pharmaceutical industries where consumers
health and safety are paramount (Li 2013; Hastig and Sodhi
2020; Casino et al. 2020).
4.2. Impact on firm and SC performance
This category encompasses the perceived benefits to the
operations of the immediate firm and its wider SC (Mattevi
and Jones 2016). These benefits can be categorized as either
internal to a firm or internal to the SC. Benefits in this cat-
egory include reduced operations costs through a reduction
in internal inefficiencies (e.g. shortages, stock errors, theft
and shrinkages) and improved product recall management
through the real-time exchange of logistics information
ak and Moskvich 2012; Appelhanz et al. 2016;
Sumukadas 2021). In addition, the outputs of traceability,
such as up-to-date information on inventories and the cur-
rent capacity of SC partners (including suppliers, distributors,
manufacturers and retailers), improve decision making at
both the firm and SC level (Azevedo et al. 2013; Jonsson and
Mattsson 2013; Scholten and Schilder 2015). This track-and-
trace information creates a wider visibility that helps to
anticipate potential disruptions in either production capacity,
transport capacity or warehousing capacity at any of the tiers
(Alfaro and R
abade 2009; Marucheck et al. 2011; Scholten
and Schilder 2015). This helps SC firms to devise strategies
ahead of a disruption and, in a worst-case scenario, to
quickly recover from such disruptions using SCRes.
Traceability systems enhance the real-time tracking of
assets, which facilitates the exchange and joint use of assets
and resources for the mutual benefit of SC partners (Bradley
et al. 2018; Hald and Kinra 2019). In the healthcare sector,
for example, traceability has proven useful in the efficient
tracking of expensive, durable and mobile equipment such
as wheelchairs, infusion pumps, blood supplies and other
materials such as pharmaceuticals, surgical trays and sup-
plies. Thus, it aids in maintaining a high service level in the
delivery of healthcare (Bradley et al. 2018; Hald and
Kinra 2019).
Christopher and Lee (2004) argued that the quality of SC
information is directly proportional to the level of trust and
confidence in that SC. Traceability creates an efficient com-
munication protocol that builds trust and confidence among
SC actors and consumers, hence establishing long-term col-
laborative relationships among them (Alfaro and R
2009; Kumar, Heustis, and Graham 2015; Feng et al. 2020;
Sumukadas 2021).
Traceability technology also provides accurate point-
of-sale data that can subsequently provide an effective
avenue for the reconciliation of inventory records with actual
inventories within the firm (Bottani, Montanari, and Volpi
2010; Hong, Kim, and Kim 2010; Fatorachian and Kazemi
2021). This level of traceability enhances reliability and secur-
ity by facilitating the swift transfer of inventory information
across the SC to decrease inventory errors and eventually
mitigate the bullwhip effect in the SC (Bottani, Montanari,
and Volpi 2010; Cui et al. 2017; Pournader et al. 2020). It also
provides reliable transaction history for financial audits (Hald
and Kinra 2019). Advanced traceability systems, in particular
the blockchain, exhibit security features such as stability and
immutability, hence, information on past transactions can be
easily retrieved, thus ensuring fairness and trust, reducing
corruption (Hald and Kinra 2019; Saberi et al. 2019).
Traceability systems also serve as a reliable platform to
enhance brand competitiveness. When issues arise in the SC
operations, notifying the concerned stakeholders such as
government agencies, consumers, and SC partners is a very
important step that can protect or destroy the firms reputa-
tion (Kumar, Heustis, and Graham 2015; Wowak, Craighead,
and Ketchen 2016). Traceability presents an effective commu-
nication approach that firms can use to reassure stakeholders
that they are in full control of the situation (Banterle and
Stranieri 2008; Kumar, Heustis, and Graham 2015; Wowak,
Craighead, and Ketchen 2016). The ability to eliminate coun-
terfeits also boosts the brands reputation (Azzi, Chamoun,
and Sokhn 2019) and builds customer confidence in the
integrity of the SC.
4.3. Impact on consumers and society
The third category of benefits extend beyond firm and SC
improvements to address consumer expectations and posi-
tively impact society (Mattevi and Jones 2016). For example,
traceability acts as a driver for trust among consumers who
might be willing to pay more for safer products especially
for food and pharmaceuticals (Alfaro and R
abade 2009;
Mattevi and Jones 2016). Thus, for concerns related to ethics,
health and safety, and religious beliefs, consumers have
become increasingly interested in knowing the source and
composition of what they consume, hence the ability of
traceability systems to provide such evidence retains existing
and attracts new customers (Marucheck et al. 2011;
Bumblauskas et al. 2020). For example, the continuous moni-
toring of drug distribution and sales helps ensure patients
safety through the early detection of counterfeiters (Rotunno
et al. 2014).
Mattevi and Jones (2016) added that traceability has a
positive impact on the environment by providing evidence
of the ethical and sustainable sourcing of materials. In par-
ticular, Pournader et al. (2020) and Saberi et al. (2019) con-
test that sustainable logistics and SC operations are one of
the most anticipated benefits of traceability data. Saberi et
al. (2019) opined that blockchain traceability presents an
avenue to promote social SC sustainability by ensuring
adherence to human rights, including fair and safe working
conditions. They hinted that since data cannot be modified
without the consent of authorized actors, any unethical prac-
tices by individuals, firms or governments can easily be
detected to ensure that corrupt individuals are held
Moreover, traceability helps manage returns in situations
of unfit products and recyclable artefacts. The efficiency with
which these reverse logistics activities are carried out goes a
long way towards instilling consumer confidence and mini-
mizing the risk of lost sales (Rotunno et al. 2014; Dai, Ge, et
al. 2015). Traceability information also helps to reduce the
direct and indirect costs associated with reverse logistics
since there is verifiable information on the location of the
product and its safe handling procedures (Rotunno et al.
2014; Agyabeng-Mensah et al. 2020).
4.4. Attaining the full potential of a traceability system
Notwithstanding the enormous benefits that can be derived
from the implementation of traceability systems, these bene-
fits may be preceded in the short-term by a significant
increase in operational expenses (Bradley et al. 2018) and
relationship friction among SC actors (Shou et al. 2021;
Sumukadas 2021).
Moreover, the benefits are not wholly reliant on the level
of investment (Resende-Filho and Hurley 2012) as it may be
more advantageous to make relatively inexpensive comple-
mentary improvements to an existing traceability system
than to adopt a new, more sophisticated and hence more
expensive system. In addition, it is important to note that
the gathering of tools and systems does not guarantee the
desired benefits unless these resources are effectively
bundled and integrated (Bradley et al. 2018). That is, despite
the varying capabilities of the technologies, they only act as
enablers of the traceability system, thus attaining the full
benefits of traceability will require a focussed integration of
other elements such as user skills and resource layout.
Despite literature claims that traceability is an enabler of
inter-firm trust and confidence, it is also important to note
that empirical findings suggest the presence of opportunistic
behaviour in the implementation of traceability (Shou et al.
2021), as firms are more likely to implement traceability sys-
tems to mitigate their internal risks than the external risks in
the SC (Stranieri, Orsi, and Banterle 2017). Thus, larger brands
may be more likely to exert pressure on smaller firms to
meet stringent traceability demands to harmonize their verti-
cal transactions (Stranieri, Orsi, and Banterle 2017). Therefore,
some of the potential benefits within the SC are not
always realized.
5. Traceability as an enabler of SCRes
The benefits of traceability, especially under the category of
crisis management, highlight some key points that guide the
discussion on the role of traceability as an enabler of SCRes.
Although literature has aligned SCRes with temporary SCs
established in response to a disaster, such as a hurricane,
earthquake or famine (Johnson, Elliott, and Drake 2013), any
potential or actual disruption to the flow of goods, materials,
services or related information in the normalSC may also
require SCRes (Scholten and Schilder 2015). SCRes represents
an essential part of the broader perspective of business con-
tinuity planning that addresses the stance that most threats
to business survival lie outside the focal firm (Kurniawan
et al. 2017). Firms in a SC are vulnerable to risks emanating
from their lack of control over the dynamic environment in
which they operate, resulting in coordination problems that
lead to supply and demand inconsistencies (Kurniawan et al.
2017). Hence, appropriate strategies are needed to explore
the sources of risks and potential solutions that improve the
responsiveness of SC operations to consumer demand. In
this context, this section discusses both the direct and indir-
ect relationships between traceability and SCRes by analogis-
ing the themes related to the benefits identified from the
traceability literature to the key theoretical constructs sur-
rounding SCRes. As discussed and summarised in Table 8,
this paper thus builds on the identified benefits vis-
a-vis the
dominant enablers of resilience flexibility, velocity, visibility
and collaboration (Scholten and Schilder 2015), which are
key theoretical constructs in the SCRes literature.
5.1. Direct impact on SCRes
The prevalence of internal and exogenous risks has major
implications for the performance of SCs, hence the manage-
ment of risks remains a core issue in establishing resilience
in SCs (Ringsberg 2014). Risks cannot be fully eliminated due
to increasing SC complexity, hence firms must devise strat-
egies to efficiently control the impact and rate of disruptions
(Stranieri, Orsi, and Banterle 2017). Within a competitive
industry, exogenous risks are inherent in the presence of
substitutes and the frequent safety and quality regulatory
interventions that have several implications for customer
quality preferences, leading to demand uncertainties.
Traceability helps acknowledge the provenance of prod-
ucts, the authenticity of its raw materials/composition/ingre-
dients and the sustainability and ethical adherence of the
production process (Timmer and Kaufmann 2017; Stranieri,
Orsi, and Banterle 2017). This helps firms gain market recog-
nition that impacts strongly on consumer preferences. Thus,
the implementation of a traceability standard that assures
consumers of quality and safety helps to avoid disruptions
in demand.
Traceability as a risk identification tool presents an avenue
to develop a proactive and holistic approach to manage a
SC crisis. The pursuit of SCRes seeks to ensure that a disrup-
tion at one node of the SC does not impede the entire sys-
tem (Musa, Gunasekaran, and Yusuf 2014). Traceability
technologies such as blockchain and IoT enhance the relay
of real-time event notifications which enhance the pro-
activeness of other SC partners in the event of a disruption
at any node in the SC (Oliveira and Handfield 2017; Ivanov
and Dolgui 2020). Improving traceability systems thus helps
uncover potential vulnerabilities inherent at any stage of the
SC and prepare a response and recovery strategy in advance
(Timmer and Kaufmann 2017).
Furthermore, counterfeiting and fraud along the SC may
be considered SC disruptions that require SCRes to control
their occurrence and impact. Traceability enables the attain-
ment of SCRes in this regard by providing an audit trail of
the provenance and authenticity of products that can be
verified at the various tiers to limit the likelihood of counter-
feits (Chang, Iakovou, and Shi 2020). Traceability supports
the early detection of deviations or potential deviations to
alert all stakeholders of potential disruptions and as well,
develop measures to curb it (Ivanov and Dolgui 2020).
5.2. Indirect impact on SCRes
Traceability also plays an indirect role by enhancing other
enablers of SCRes. The analysis below focusses on the indir-
ect relationship between traceability and the dominant for-
mative elements of SCRes captured in the literature i.e.
flexibility, visibility, velocity and collaboration (Johnson,
Elliott, and Drake 2013; Scholten and Schilder 2015).
Flexibility enables SCRes by ensuring that resources are
easily redeployed to quickly adapt operations in the event of
a disruption, whereas velocity contributes to this by ensuring
that adaptation or recovery occurs at a fast pace. Ensuring
flexibility and velocity in SCs requires close relationships
between SC actors to facilitate timely information flow on
any changes, such as those related to delivery schedules and
equipment availability (Johnson, Elliott, and Drake 2013).
Continuous monitoring and real-time tracking facilitated by
traceability systems enhances SC responsiveness (flexibility
and velocity) to disruptions (Sumukadas 2021). Moreover,
these improvements in reliability and security also lead to
consistency in the performance of SC partners, thus building
trust and confidence among them (Shou et al. 2021). This
facilitates swift access to information and support during a
crisis by eliminating the need for new formal contractual
negotiations as all parties are confident that any monetary
liabilities will be harmoniously resolved (Johnson, Elliott, and
Table 8. SCRes as a benefit of traceability.
Benefit of traceability SCRes enabler Definition of enabler
Direct relationship
Improved risk awareness and pro-activeness Traceability SC capability used to advance SC transparency and visibility by providing traces of the
provenance, location, status, composition etc. through all stages of production, processing
and distribution (Kelepouris, Pramatari, and Doukidis 2007; Timmer and Kaufmann 2017).
Improved consumer trust and confidence
Indirect relationship
Improved monitoring of events and risk
Visibility Timely knowledge of the identity, location and status of operating assets transiting
through the SC (Johnson, Elliott, and Drake 2013).
Real-time tracking and exchange of information Flexibility Velocity Flexibility refers to the ease with which a SC can alter its operations to cope with
changes in market situations or any other unexpected event (J
uttner and Maklan
2011; cited in: Scholten and Schilder 2015)
Improved reliability and security Velocity refers to the speed with which a SC can respond to and recover from an
unexpected disruption (Scholten and Schilder 2015; Johnson, Elliott, and Drake 2013).
Improved trust and confidence among SC actors Collaboration The capability of inter-organizational interactions to plan and execute SC operations to
achieve common goals (Scholten and Schilder 2015).
Drake 2013). In addition, since traceability ensures the avail-
ability of the right type of information at the right time, it
expedites preparation for, response to and recovery from a
disruption, thereby improving SC velocity (Scholten and
Schilder 2015). Thus, there are several factors that lead to
improved velocity when using an appropriate traceabil-
ity system.
Timely information sharing among SC partners is vital to
achieve the required level of SC visibility (Christopher and
Lee 2004). Greater visibility is considered an antecedent of
SCRes because it facilitates the identification and under-
standing of market events, with increased access to relevant
information, thus enabling firms to manage potential risks
and reduce the adverse effects of the disruption (Brandon-
Jones, Squire, and Van Rossenberg 2015). To achieve
visibility and subsequently create SCRes, a firm must be
able to track and trace the right information to assist in
anticipating disruptions (Scholten and Schilder 2015). This
capability is enhanced by the ability to continuously track
inventory in storage and transit and monitor their condi-
tions (Ivanov and Dolgui 2020), which is facilitated by
traceability systems.
Collaboration also facilitates inter-firm interactions and
the exchange of real-time information among SC actors
(Scholten and Schilder 2015) with the aim of jointly planning
before, during and after a SC disruption to reduce its impact
(Johnson, Elliott, and Drake 2013; Scholten and Schilder
2015; Sumukadas 2021). However, collaboration must be
nurtured(Sumukadas 2021, p.6). This is dependent on the
commitment, trust and confidence among SC stakeholders
which is enhanced by the assurance of reliability and security
of information shared among SC actors (Johnson, Elliott, and
Drake 2013; Scholten and Schilder 2015). Trust refers to the
good intent and genuine concern of SC partners for one
another, which reflects confidence in the capacity and reli-
ability of each other (Johnson, Elliott, and Drake 2013).
5.3. Framework showing traceability as an enabler of
SC resilience
Based on integrating the traceability literature with the key
theoretical constructs from the SCRes literature, it is con-
cluded that traceability systems can be explored as a SC cap-
ability that both directly enables SCRes and further indirectly
enhances the attainment of the other enablers of SCRes. This
relationship is illustrated in the proposed framework in
Figure 3. This does not represent a cause-and-effect relation-
ship, but rather a conceptual representation of how trace-
ability can be linked to SCRes both directly and indirectly.
Further empirical research is needed to investigate the
strength of each link and the likelihood of a simultaneous
fulfilment of more than one link from a traceability system.
6. Conclusions and research gaps
6.1. Summary of findings
Traceability has become an increasingly important research
topic in recent years. The urgent need for quality and safety,
especially in food and pharmaceutical SCs, coupled with
recent evaluations of new technologies predicted to have a
major impact on traceability, have significantly contributed
to this increased research attention. As captured in the
research question, this study sought to provide a compre-
hensive overview of the benefits of traceability systems as
identified in the literature and further explain the relation-
ship between traceability and SCRes. To answer this research
question, this SLR first highlighted the current state-of-the
art in the traceability literature, both by using descriptive
analysis and by discussing three of the key themes identified:
drivers, technology evolution and barriers to adoption. Key
points raised under these themes included:
Despite the relevance of external drivers, such as manda-
tory regulations, the ultimate decision to adopt a
Improved risk awareness and
Improved trust and
confidence among SC actors.
Improved reliability and
Improved consumer trust and
Improved monitoring of
events and risk identification
Real-time tracking and
exchange of information
Supply Chain
Benefits of Traceability Enablers of SCRes Outcome
Figure 3. Proposed framework with traceability as a direct & indirect enabler of SCRes.
traceability system depends on internal motivations either
to: meet the demands of the product; control excessive
costs of failure (profit); or to improve SC performance.
There is no wholly overriding traceability technology all
technologies have their strengths and weaknesses, and
some perform better than others in some industries due
to specific product characteristics. Nonetheless, it is con-
cluded that, in the future, there should be less focus on
developing new technological systems and instead more
focus on creating a more universally accepted system
that enhances interoperability globally.
The challenges to the implementation of traceability can
be categorised as either intra-firm, inter-firm, technical or
external. Financial constraints are a key hurdle faced in
the implementation of traceability systems, and these can
be encountered in different forms at different stages of
traceability implementation, such as: the cost of technol-
ogy (hardware and software); cost of staff training; and
legal costs associated with information accessibility.
Secondly, this SLR has summarized the benefits of trace-
ability systems under three categories impact on crisis man-
agement, impact on firm and SC performance, and impact on
consumers and society, providing detailed sub-categories, as
summarized in Table 7. This study further emphasized that
the benefits of the implementation of traceability may be
preceded by a significant increase in operational costs in the
short-term and by inter-firm relationship friction. It is also
concluded that the tools and technologies only act as ena-
blers of traceability and require an effective integration with
other resources to fully attain the desired benefits. In add-
ition, it is important to note that the use of incentive-based
contracts or contingent payments (i.e. where a principalpays
an agentbased on their ability to meet the quality and
safety standards agreed) is persuasive in ensuring adherence
to quality and safety requirements (Resende-Filho and Hurley
2012). However, these contingent payments are likely to lead
to adversarial buyer-supplier relationships where the most
influential tier may be overly opportunistic. Process traceabil-
ity is therefore recommended to ensure the continuous moni-
toring of the production process, modifying potential threats
at source to avoid the wasted production and distribution of
compromised products.
Thirdly, this study explored the benefits of traceability that
enhanced the attainment of SCRes. Building on the detailed
benefits specified in Table 7, it is concluded that the follow-
ing have a relationship with SCRes: improved risk awareness
and pro-activeness; improved consumer trust and confidence;
improved monitoring of events and risk identification; real-
time tracking and exchange of information; improved reliabil-
ity and security; and, improved trust and confidence among
SC actors. These benefits either directly enable the develop-
ment of SCRes or have an indirect impact through other
known enablers of SCRes flexibility, velocity, visibility and
collaboration. As summarized in Table 8 and Figure 3, these
results advance understanding of the traceability-SCRes rela-
tionship and set the tone for further empirical research that
seeks to validate this relationship. Previous studies have
focussed on identifying strategies that enable SCRes, whilst
this study has added emphasis on how to implement these
strategies to successfully overcome the associated barriers.
6.2. Managerial implications
From a managerial perspective, this study increases practi-
tioner awareness of the challenges and potential benefits
associated with traceability systems, which are essential con-
siderations in making strategic decisions. It addresses the
opportunities inherent in various technologies to aid an
objective cost-benefit analysis in selecting technologies thus
guiding traceability-related SC initiatives. This study also
offers valuable insights for both practitioners on the import-
ance of building trust and confidence in SC relationships to
maintain shared values among all SC actors.
Moreover, the study provides a justification for investment
in digitalization in response to the increased susceptibility of
SCs to disruptions by outlining the various benefits of trace-
ability that help improve both the proactive capacity to pre-
vent a disruption and the reactive capacity to respond
appropriately after experiencing a disruption. Specifically,
traceability increases a firms ability to monitor real-time
events and obtain, update and transfer information quickly
among SC partners to ensure a responsible partner takes the
required action.
6.3. Research gaps and future research
The study identified the following broad gaps in the litera-
ture to steer future research.
The literature differed on the most important driver of
traceability because of the varying complexity of the SCs
studied and, to some extent, the theoretical lens adopted.
To objectively determine the significance of the drivers
and gain a better understanding of them, it is proposed
that future studies consider the complexity of the SCs by
focussing on cases from similar industries to gain literal
replication, and/or contrasting industries to gain theoret-
ical replication.
Unlike mandatory traceability, voluntary standards are
likely to result in a restructuring of existing relationships
because of the amount of information that must be
shared among SC partners. Future research should
explore the level of information firms are willing to share
with partners and the potential benefits of stipulating
boundaries on the demands for information that partners
should realistically request from others.
Further research is needed to compare the effectiveness
of alternative technologies, given that to date the com-
parisons in the literature have considered technologies
that were at different stages of implementation, with
some still being tested in specific industries. Surveys to
compare the effectiveness of technologies at similar oper-
ational levels (such as according to years of adoption) are
therefore recommended to better assess their potential
for SC traceability. Case study research is also needed to
analyse receptiveness towards advanced traceability and
hence find effective implementation strategies for emerg-
ing technologies.
In contrast to traceability as an enabler of inter-firm trust
and confidence, from a TCE perspective, Stranieri, Orsi,
and Banterle (2017) concluded that firms are more likely
to implement traceability systems to mitigate their
internal risks than to mitigate external risks in the SC.
Further research is needed to explore strategies that
jointly address these objectives and mitigate opportunis-
tic behaviours in the SC.
Notwithstanding the capacity of traceability systems to
improve risk awareness by identifying risk sources along
the SC, a comprehensive understanding of the relation-
ship between traceability and SCRes is missing from the
literature. Although it is explicitly mentioned in a few
studies on food SCs, traceability has either been ignored
or merged with other enablers in studies of other indus-
tries. As highlighted in Section 5 above, traceability plays
a significant role as an enabler of SCRes both directly and
indirectly. Future empirical research is needed to verify
these insights, thereby extending understanding beyond
the purpose of traceability for monitoring and identifying
risks to also consider its impact on developing vulnerabil-
ity mitigation strategies.
The lack of a unified traceability standard obstructs the
effectiveness of traceability since the various systems
have different data manipulation attributes, creating com-
patibility problems. Survey research is recommended to
understand the effects of this lack of standardisation on
SC relationships and whether or not this blocks the entry
of new potential partners.
Attaran (2007) asserted that restricting traceability sys-
tems to regulatory requirements (compliance) because of
the cost of technology may hinder the returns on invest-
ment (ROI) expected, suggesting a linkage between finan-
cial constraints and the level of traceability adopted.
Further empirical investigation is needed to assess this
assertion along with the severity of the other challenges
identified in the literature. For example, case study
research is recommended to investigate how an aware-
ness of the challenges expected in the deployment of
traceability systems can facilitate strategic decisions and
subsequently determine the level of traceability to adopt.
6.4. Limitations
Despite rigorous efforts to ensure the validity of our findings,
the study has some limitations. Firstly, there is potential for
bias and subjectivity, as commonly attributed to literature
reviews (Durach, Kembro, and Wieland 2017). This study relied
on papers published in ABS recognized journals compiled
from the OneSearch Library and Scopus with a predefined
search string. Hence, there is a possibility that some relevant
articles were omitted because of the specified scope of the
search strategy. However, the authors attempted to neutralize
this limitation by adopting a comprehensive, transparent and
systematic process, as described in Section 2, where the
bounds placed on the sources of literature was justified as
being necessary to ensure that only high quality articles were
screened for inclusion. Secondly, this study was based on the
viewpoints of other researchers, and hence the conclusions are
limited to the scope of knowledge presented in the literature.
This hindered the exploration of SC traceability as an enabler
of SCRes because empirical investigation was beyond the
scope of this study. However, the framework and conclusions
lay the conceptual foundations for future empirical studies
that develop this promising line of enquiry further.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes on contributors
Ghadafi M. Razak is a PhD Candidate in the
Department of Management Science at Lancaster
University Management School, UK. His research inter-
ests include supply chain traceability, risk management
and resilience, and agri-food supply chain dynamics.
Ghadafi is a student member of the European
Operations Management Association (EurOMA). He has
presented his research at the EurOMA Doctoral
Seminar and also attended the EurOMA Conference.
Linda C. Hendry is a Professor of Operations
Management at Lancaster University Management
School, UK. Her research interests include: (i) global
supply chain management, including sustainable
sourcing and supply chain responses to modern slav-
ery legislation (ii) manufacturing strategy, planning &
control for product customisation contexts; and (iii)
process improvement approaches, such as Six Sigma.
Linda is a member of the European Operations
Management Association (and was on the Board as a member of the
Finance Team from 2011-2014). She has published extensively in a wide
variety of journals, including those that focus on Operations
Management, Production and Operational Research.
Mark Stevenson is a Professor of Operations
Management at Lancaster University in the UK. His
research interests currently include sustainable sup-
ply chain management, supply chain risk and resili-
ence, supply chain flexibility and uncertainty,
production planning and control in high-variety
manufacturing companies and reshoring and the
manufacturing location decision. His work has
appeared in several operations and supply chain
journals, including Production Planning & Control, International Journal
of Operations & Production Management, Journal of Operations
Management, Production and Operations Management, and Supply
Chain Management: An International Journal.
Ghadafi M. Razak
Linda C. Hendry
Mark Stevenson
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