Tracing Bad Products in Supply Chains: The Roles of Temporality, Supply Chain Permeation, and Product Information Ambiguity

Published date01 June 2016
DOIhttp://doi.org/10.1111/jbl.12125
Date01 June 2016
Tracing Bad Products in Supply Chains: The Roles of Temporality,
Supply Chain Permeation, and Product Information Ambiguity
Kaitlin D. Wowak
1
, Christopher W. Craighead
2
, and David J. Ketchen Jr.
3
1
University of Notre Dame
2
University of Tennessee
3
Auburn University
To minimize negative consequences, bad products must be removed quickly once found within supply chains. This makes traceabilitythe
ability to track the ow of a producta key issue. Unfortunately, rms struggle to create traceability and little interdisciplinary research
has been conducted in this area. Accordingly, we conducted a grounded theory investigation that transcends functional and organizational
boundaries. Although past literature tends to consider a rms ability to trace products as one-dimensional and inherently good or bad, we nd
that a rms ability to trace products varies based on contextual factors. Specically, our study reveals that traceability is hindered by temporal-
ity (i.e., time pressures that strain a rms ability to track products), supply chain permeation (i.e., supply chain ow characteristics that repre-
sent the degree of bad product inltration), and product information ambiguity (i.e., product characteristics that create vagueness about what to
trace). We provide prescriptive advice about how rms can overcome these traceability barriers and thus enhance their ability to identify and
recall tainted products. Broadly, our ndings support the need to manage traceability from a nuanced approach and to seek boundary-spanning
supply chain solutions.
Keywords: supply chain disruptions; traceability; product recalls; grounded theory
INTRODUCTION
When rms discover that bad productsitems that are tainted,
spoiled, or counterfeithave breached their supply chains, the
bad products must be quickly disentangled from good products,
especially when consumer well-being is at risk. Central to this
task is traceability,
1
which we dene as the ability to identify
and verify the components and chronology of events surrounding
a product at all stages of the supply chain (cf., Skilton and
Robinson 2009). Traceability enables rms to know which path
a product has taken to reach its current location, which is critical
for determining the causes of failures and discerning which
products need to be removed.
In February 2013, for example, some beefin Europe was
found to be horsemeat originating from Romania. Because com-
panies did not have rigorous traceability systems, they had no
idea which products were affected. As such, rms ended up
recalling all potentially contaminated food products, which
resulted in an extremely large and costly recall (Lawless and
Hinnant 2013). The recall affected so many companies that Euro-
pean Union ministers desperately sought better ways to trace
food as it crosses rm, country, and national borders (Associated
Press 2013). Many other organizations also struggle with estab-
lishing and maintaining traceability. Within the U.S. food indus-
try, for example, government investigators were only able to
trace ve of 40 products throughout the entire supply chain
(Levinson 2009). Additionally, nearly 60%of facilities did not
maintain accurate records about their suppliers, recipients, and
transportation providers.
Although information technology (IT) and supply chain schol-
ars have examined certain aspects of traceability, they have done
so from largely siloedperspectives (Sanders et al. 2013, 413).
This has resulted in fragmented insights rather than a holistic
understanding of how rms can better track the ow of products.
Indeed, key questions about traceability in supply chains remain
unanswered, which has resulted in calls for more research. Opara
(2003), for example, notes that traceability is an interdisciplinary
issue (i.e., IT and supply chain) and calls for more research
focusing on strategies that help companies streamline traceability
across supply chain partners. Similarly, Malhotra et al. (2007)
call for more research adopting a comprehensive (i.e., source-to-
consumer) perspective of traceability in order to fully understand
the dynamics of information processing and sharing among sup-
ply chain partners. Grover and Saeed (2007) also note the lack
of research on information ows across supply chain partners,
while Marucheck et al. (2011) highlight the need for more
research on the ow of products as they are distributed through
the supply chain. Last, Alfaro and Rabade (2009) specically
call for more qualitative research investigating traceability in
companies, including topics such as how rms overcome the
challenges involved with implementing traceability systems.
In response to these calls, our study is aimed at helping close
the gap between what we know and what we need to know
Corresponding author:
Kaitlin D. Wowak, Department of Management, Mendoza College
of Business, Suite 326, University of Notre Dame, Notre Dame, IN
46556, USA; E-mail: katie.wowak@nd.edu
1
Traceability is similar to, yet distinct from, quality assurance
(QA) points (i.e., process-oriented activities that prevent defects
from occurring) and quality control (QC) points (i.e., product-
oriented activities that focus on identifying defects after the pro-
duct is manufactured) (Liva 2009). QA and QC points help rms
identify defective products during and after production, but do
not necessarily help rms determine the path a product has taken
through the supply chain and therefore does not provide informa-
tion about the products origin or the potential source(s) of
contamination.
Journal of Business Logistics, 2016, 37(2): 132151 doi: 10.1111/jbl.12125
© Council of Supply Chain Management Professionals
about traceability in supply chains from both academic and man-
agerial perspectives. Given the struggles that many rms have
with traceability, our research question is: What supply chain
characteristics hinder traceability? We address this question using
a grounded theory (GT) approach, which involves inductively
building theory based on analysis of qualitative data. GT is a
particularly appropriate and valuable approach when investigat-
ing topics for which there is little preexisting theory (Gioia et al.
2013). To account for the interdisciplinary nature of traceability,
we: (1) designed the study in a manner that transcended func-
tional and organizational boundaries; and (2) adopted a broad
view of supply chain to include product ow, processes, and
supply chain design (Mentzer et al. 2001).
Our ndings contribute to the literature on traceability and
offer important insights for both research and practice. For schol-
ars, our study unpacks a rich, multidimensional conceptualization
of traceability that has yet to be set forth in the literature. In
doing so, our study builds theory on traceability, furthering the
related body of knowledge and thus should serve as a lynchpin
for future theory building/testing research efforts. From a man-
agerial perspective, our research provides guidance relative to
key traceability barriers that rms may be able to mitigate, thus
enhancing capabilities to trace product ow. More broadly, our
study can provide managers with a keen understanding of supply
chain design choices that affect traceability. This, in turn, should
drive better-informed design decisionsparticularly when
product safety/security is paramount.
LITERATURE REVIEW
As noted above, traceability plays a critical role during product
recalls by enabling rms to determine which path a product has
taken to reach its current location. This information provides
guidance about potential causes of failures (e.g., ingredient
issues, manufacturing issues, transportation issues) and allows
companies to determine which products need to be removed
from circulation. In other words, traceability can facilitate a
rms product recall efforts by enabling rms to target tainted
products. Thus, in order to identify gaps in the understanding of
traceability, it is important to review the extant literature in two
areas: product recalls and traceability.
Product recalls
Product recalls occur when tainted products are discovered and
need to be removed from the market (Roth et al. 2008). Due to
the increasing frequency and potential impact of recalls, there
has been a surge in product recall-focused publications from aca-
demics and practitioners alike (Wowak and Boone 2015).
Research in this area has focused on three key aspects of product
recalls: recall antecedents, recall processes, and recall conse-
quences.
Several studies have examined the antecedents of product
recalls, with most focusing on operational issues. Steven et al.
(2014), for example, nd that global outsourcing (as opposed to
offshoring) leads to more recalls while outsourcing domestically
leads to fewer recalls. Other studies have examined
nonoperational antecedents. For instance, Wowak et al. (2015)
nd that chief executive ofcer stock option pay is positively
associated with the likelihood of subsequent recalls. The authors
theorized that higher stock option pay promotes a lack of caution
that manifests in an increased prevalence of product safety
issues.
The second areathe product recall processis the lynchpin
to success during product recalls. Ketchen et al. (2014b) take an
in-depth look at the role of resource endowments and resource
orchestration capabilities at play during the product recall pro-
cess. Although the existing literature tends to treat recalls as
monolithic, Ketchen et al. (2014b, 12) identify four different
types of recalls, suggesting that recalls should not be managed
using a one size ts allapproach. Similarly, Chen et al.s
(2009) investigation of proactive versus reactive recall strategies
nds that the former may have a more negative impact on rm
value.
Within the third areathe effects of product recallsThiru-
malai and Sinha (2011) nd that the nancial impact a rm
endures during and after a product recall depends on several fac-
tors: product scope, sales, growth prospective, and capital struc-
ture (e.g., debt-to-equity ratio). Although most of the research in
this area has focused on the nancial consequences of recalls,
there is a growing amount of research on other impacts as well.
Van Heerde et al. (2007), for instance, examine marketing effec-
tiveness after rms experience a product recall. The authors
found that rms often experience a decrease in marketing effec-
tiveness following product recalls, which in turn hinders their
ability to recover lost market share.
In sum, important strides have been made toward understand-
ing what causes product recalls, how rms manage the recall
process, and how recalls affect various stakeholders, but little is
known about traceability in the recall process. Given that trace-
ability can facilitate a rms product recall efforts, it is surprising
that scholars have not yet examined traceability within this
context.
Traceability
IT scholars have examined various aspects of traceability, but
have focused primarily on data management within the supply
chain as opposed to traceability during product recalls. Bechini
et al. (2008), for example, propose a data model for traceability
along with a set of patterns to enhance generic traceability
semantics. The authors implemented their system in a company
and discovered that the benets of increased traceability include
superior data quality and reduced cost in the adoption of e-busi-
ness processes. Alfaro and Rabade (2009) also investigate the
benets of adopting traceability systems, nding that rms real-
ize several advantages such as lower levels of spoiled inventory,
enhanced operational efciency, fewer stock-outs, and shorter
lead-times.
Regattieri et al. (2007) investigate traceability from a slightly
different perspective. They analyzed legal and regulatory aspects
of food traceability and presented a model of the fundamental
elements of effective traceability systems, including product iden-
tication, data to trace, and product routing. They found that
traceability systems using bar codes and alphanumerical codes
Traceability in Supply Chains 133

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