Exploring the processing of product returns from a complex adaptive system perspective

AuthorJennifer A. Espinosa, Donna Davis, James Stock, Lisa Monahan
Publication Date12 Aug 2019
Exploring the processing of
product returns from a complex
adaptive system perspective
Jennifer A. Espinosa
Department of Marketing and Business Information Systems,
Rowan University, Glassboro, New Jersey, USA
Donna Davis and James Stock
Department of Marketing,
University of South Florida, Tampa, Florida, USA, and
Lisa Monahan
Department of Marketing, Meredith College, Raleigh, North Carolina, USA
Purpose The purpose of this paper is to explore the processing of product returns at five case companies
using a complex adaptive systems (CAS) logic to identify agent interactions, organization, schema, learning
and the emergence of adaptations in the reverse supply chain.
Design/methodology/approach Using a multiple-case study design, this research applies abductive
reasoning to examine data from in-depth, semi-structured interviews and direct researcher observations
collected during site visits at case companies.
Findings Costly or high-risk returns may require agents to specialize the depth of their mental schema.
Processing agents need freedom to interact, self-organize and learn from other agents to generate emergent
ideas and adapt.
Practical implications Limiting the depth of individual agent schema allows managers to better allocate
labor to processing product returns during peak volume. To boost adaptability, managers need to craft a
dynamic environment that encourages agents with diverse schema to interact, anticipate, and self-organize to
brainstorm new ideas. Managers need to resist the urge to controlthe dynamic environment that ensues.
Originality/value This paperbuilds on existing researchthat studies the key decisionpoints in the analysis
of product returnsby exploring how processing-agent behaviors can create adaptabilityin the reverse supply
chain. Additionally, this research follows in the tradition of Choi et al.(2001)andSuranaet al.(2005)and
proposes the application of CAS to a specificpart of the supply chain the processing of productreturns.
Keywords North America, Case study, Reverse logistics, Supply chain processes
Paper type Research paper
1. Introduction
Customers today expect more than ever before when shopping (e.g. instantaneous access to
products, seamless shopping experiences), and forward supply chains have begun to
respond to these demands by developing fast moving r etail supply chains and
omnichannels ( Jones, 2018; Petro, 2018). Increasingly, customers are assimilating desires
for accessibility and convenience into their expectations for returning products. So far, few
supply chains have made modifications to their product return strategies to offset the costs
associated with these evolving expectations (Dennis, 2018; Lindsey, 2016). However, the
crucial role that product returns play in forging productive and sustainable consumer
relationships is undeniable (Hjort et al., 2013). While every consumer/firm transaction
The International Journal of
Logistics Management
Vol. 30 No. 3, 2019
pp. 699-722
© Emerald PublishingLimited
DOI 10.1108/IJLM-08-2018-0216
Received 28 August 2018
Revised 23 January 2019
Accepted 4 March 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
The authors gratefully acknowledge and thank the anonymous reviewers and editor Gammelgaard for
their helpful comments during the review process. The authors gratefully thank the University of
South Floridas L. Rene Gaiennie Endowment and the University of South Floridas Center for Supply
Chain Management and Sustainability for funding travel to collect data and the NVivo 10 software
necessary to complete this research.
Exploring the
of product
provides an opportunity to create consumer value (Kumar et al., 2010), returns are unique in
that they begin with a negative experience that precipitates the return. When a firm acts to
turn a negative experience into a positive one, consumers are often motivated to purchase
again from the same firm and spread the word to others about the turnaround experience
(Gesenhues, 2017).
Product returnsrequire companies to perform a balancingact between setting policiesthat
are simple enough to encourage repeat shopping, yet strict enough to prevent return abuse,
while also maintaining an effective process to dispose of returned products (Goldman, 2016;
Jack et al., 2010). Traditional product return strategies have focused on optimizing return
policies to minimize returns as much as possible and/or identifying characteristics of serial
returners (Daunt and Harris, 2012; Davis et al., 1998; Janakiraman and Ordonez, 2012).
However, this optimization approach significantly downplays the importance of human
behavior in product returns and largely ignores insights generated from the processing of
returns. Returning a product involvesthe interaction of at least two people (e.g. the customer
and the employee accepting the return) but typically more, all of whom have different
motivations, power, and information-processing capabilities. Companies have traditionally
assumed customersbehave rationally when returning products(i.e. return a product because
it is defective).However, shopping trendsindicate customers areincreasingly prioritizingtheir
needs at the expense of the sellers (e.g. buying multiple sizes of the same product with
the intention of returning the sizes that do not fit; Welson-Rossman, 2018). Furthermore, the
employees who evaluate and process returned products are not immune to decision-making
errors. Thus, in comparison to return behaviors by customers, behaviors of employees
processing product returns have received little attention in the literature, despite their
substantial impact on a firms profitability.
Embracing and leveraging employee behaviors during the returns process represents
one relatively untapped, alternative approach to the optimization of customer behaviors,
with the potential to reveal product quality issues and suggest solutions to those issues in
real time (Storer et al., 2014). This research applies complex adaptive systems (CAS) theory
(Holland, 1995) to explore the different parts of the system that interact during the
processing of product returns. More specifically, we will closely examine how employee
behaviors can benefit or harm the system. Unlike an optimization strategy that assumes
customer and employee behaviors do no harm, CAS theory studies both the benefits
(e.g. creativity) and drawbacks (e.g. conflict) of human behavior on the system (Nilsson and
Gammelgaard, 2012). One important research question that arises is:
RQ1. How can employee behaviors during the processing of product returns increase the
reverse supply chains adaptability?
The objective of this paperis to explore the product returns process from a CAS perspective.
Specifically, thisresearch examines how interactions, learning, and adaptationsoccur during
the processing of product returns. To achieve this purpose, we examine the product returns
process at five different case companies to develop an in-depth understanding of the roles
employee behaviors play. In the next section, we review the relevant literature, and offer a
brief description of our abductive case study methodology. Next, detailed descriptions of the
product return processes observed at each of the five case companies are provided, followed
by a discussion of CAS-grounded patterns that emerged across the cases. The paper closes
with a discussionof the implications of the current researchand directions for future research.
2. Literature review
The conceptualresearch framework (seeFigure 1) for this researchis based on the intersection
of the product returnsprocess and CAS theory, and is grounded in researchinsights from the
reverse logistics, supply chain management, natural and social sciences literatures.

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