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Implementing corporate social responsibility (CSR) in supply chains is not a trivial task. In fact, many firms in recent years have publicly proclaimed that in order to keep their CSR commitments, they had to reduce reliance on external suppliers by vertically integrating their operations. Our aim in this article is to examine whether there is truly a relationship between a firm’s CSR performance and its level of vertical integration. Drawing on a multi-industry sample of 2,715 firm-year observations, and after addressing endogeneity concerns, we demonstrate that firms with higher CSR performance tend to vertically integrate more (or, outsource less). We also demonstrate that this tendency is weaker for firms that have higher degrees of asset specificity or international diversification. Our core conclusion is that CSR performance and outsourcing are at odds, but firms can reconcile this tension by deepening their collaborations with suppliers.
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https://doi.org/10.1177/0007650319898490
Business & Society
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DOI: 10.1177/0007650319898490
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Socially Responsible
Firms Outsource Less
Maria Jose Murcia1, Rajat Panwar2,
and Jorge Tarzijan3
Abstract
Implementing corporate social responsibility (CSR) in supply chains is not
a trivial task. In fact, many firms in recent years have publicly proclaimed
that in order to keep their CSR commitments, they had to reduce reliance
on external suppliers by vertically integrating their operations. Our aim in
this article is to examine whether there is truly a relationship between a
firm’s CSR performance and its level of vertical integration. Drawing on a
multi-industry sample of 2,715 firm-year observations, and after addressing
endogeneity concerns, we demonstrate that firms with higher CSR
performance tend to vertically integrate more (or, outsource less). We also
demonstrate that this tendency is weaker for firms that have higher degrees
of asset specificity or international diversification. Our core conclusion is
that CSR performance and outsourcing are at odds, but firms can reconcile
this tension by deepening their collaborations with suppliers.
Keywords
outsourcing, supply-chain CSR, sustainable supply chain, vertical integration
Outsourcing offers numerous economic benefits to global firms (Contractor
et al., 2010). At the same time, it also presents them with an onerous chal-
lenge to implement what is called supply-chain responsibility (Maloni &
1Universidad Austral, Buenos Aires, Argentina
2Appalachian State University, Boone, NC, USA
3Pontificia Universidad Católica de Chile, Santiago de Chile, Chile
Corresponding Author:
Maria Jose Murcia, IAE Business School and Facultad de Ciencias Empresariales, Universidad
Austral, Mariano Acosta s/n y RN 8. Pilar, Buenos Aires B1629WWA, Argentina.
Email: mmurcia@iae.edu.ar
Article
898490BASXXX10.1177/0007650319898490Business & SocietyMurcia et al.
research-article2020
2 Business & Society 00(0)
Brown, 2006; Spence & Bourlakis, 2009), value chain responsibility (Phillips
& Caldwell, 2005), upstream corporate social responsibility (Schrempf-
Stirling & Palazzo, 2016), logistic social responsibility (Carter & Jennings,
2002), and sustainable supply-chain management (Seuring & Müller, 2008).
These designations have a common argument at their core: a firm’s responsi-
bility toward society and the environment (corporate social responsibility or
CSR) is not limited within the traditionally defined boundaries of a firm;
indeed, it must encompass the firm’s complete supply chain (Matten & Crane,
2005; McGahan, 2019; Schrempf, 2012). Correspondingly, because contem-
porary firms are often part of a supply chain, their CSR performance is con-
tingent upon their ability to implement CSR throughout their supply chains.
Implementing supply-chain CSR is, however, riddled with myriad chal-
lenges (Lund-Thomsen & Lindgreen, 2014; Short et al., 2016), which pri-
marily emanate from the complex and multitiered nature of supply chains
(Wilhelm et al., 2016). In some cases, supply chains are not just complex but
they are intractable and obscure. For example, in analyzing the reports sub-
mitted to the Securities and Exchange Commission by 1,300 firms on whether
their products contain “conflict minerals,” Kim and Davis (2016) found that
80% of firms could not even determine the country of origin of their prod-
ucts, and just 1% could confidently certify themselves as conflict-free.
Similarly, in a survey of 1,700 global firms, only 19% reported confidence in
their knowledge of the actions of their supply-chain partners (The
Sustainability Consortium, 2016). Worse yet, many firms do not even know
who exactly their suppliers are because of the rampant unauthorized subcon-
tracting in many industries (Choi et al., 2001; Egels-Zandén, 2017a). Even
when supply chains are tractable and suppliers are easy to identify, imple-
mentation of supply-chain CSR can still be a challenging task due to mis-
alignment between a focal firm and its suppliers about the relevance of CSR
itself (Jamali et al., 2017; Wijen, 2014), discrepancies in their respective
intentions for implementing CSR (Soundararajan et al., 2019), differences in
CSR-related regulations across jurisdictional boundaries (Hörisch et al.,
2017), and the limited ability of a firm to influence on-the-ground actions of
its suppliers (Christmann & Taylor, 2006). Given such multifaceted chal-
lenges, undercompliance and noncompliance with a focal firm’s CSR stipula-
tions are not uncommon phenomena in contemporary supply chains
(Soundararajan & Brown, 2016; Soundararajan et al., 2018).
Confronted with these challenges, firms take a wide variety of steps to
implement supply-chain CSR that are already analyzed and surveyed in pre-
vious studies (Yawar & Seuring, 2017). Rather recently, a growing number of
firms have been proclaiming that their commitments to CSR have led them to
vertically integrate their operations. For example, Symrise, a major producer
Murcia et al. 3
of flavors and fragrances, claims that to be able to work directly with vanilla
bean producers in Madagascar to implement sustainability practices, the
company has been vertically integrating its operations (Symrise, 2017).
Similarly, Ferrero, a leading confectionery manufacturer, announces that to
meet an ambitious CSR target of 100% sustainability in its raw materials, it
had acquired Oltan Group, which was formerly its major supplier of hazel-
nuts (Kittilaksanawong & Curcuraci, 2017). Taylor Guitars, a well-recog-
nized manufacturer of acoustic and electric guitars, credits its purchase of an
ebony sawmill in Cameroon to its commitment to ensuring that all its prod-
ucts are free of endangered wood species (McDonnell, 2019). IKEA ascribes
its purchase of a large area of forestland in Romania to its commitment to
implement sustainable forest management practices at the origin of its prod-
ucts’ supply chains (Chaudhuri, 2015). While these anecdotes suggest that
concerns for CSR performance may lead firms to vertically integrate as Van
Buren and colleagues (2019) recognize in their conceptual analysis of human
trafficking in global supply chains, it is also possible that these anecdotes are
misleading corporate announcements, simply meant to give a positive CSR-
spin to an otherwise motivated vertical integration (VI). Moreover, even if
these corporate claims were proven true, one could conjecture that the posi-
tive relationship between CSR performance and VI might only occur within
the idiosyncrasies of particular firms or industries. Our motivation in this
article is to dispel these ambiguities by conducting a panel study of a large,
multi-industry sample of firms. Our primary research question is as follows:
“Is there a relationship between CSR performance and the level of vertical
integration?”
We integrate core tenets of transaction cost economics (TCE) with litera-
ture in supply-chain CSR to theorize the relationship between CSR perfor-
mance and VI. According to TCE, a firm pursues VI when the total cost of
performing an activity in-house is likely to be lower than the cost of the activ-
ity done by external suppliers. Thus, costs and risks associated with monitor-
ing its suppliers are integral to the calculus that a firm uses to determine the
extent to which it vertically integrates or outsources its activities (Acquier
et al., 2017; Shelanski & Klein, 1995). Using this as a core basis for our ana-
lytical framework, we consider the costs and risks of supplier monitoring as
primary factors to explain the relationship between CSR performance and VI.
We introduce two moderating variables, namely, the firm’s asset specificity
and the level of international diversification, which are central to TCE. Asset
specificity denotes the extent to which a firm engages with suppliers
(Williamson, 1975), which can engender mutual trust and collaboration and
reduces the need for supplier monitoring (Bird & Soundararajan, 2018). In
contrast, international diversification, which denotes a firm’s expansion
4 Business & Society 00(0)
beyond its domestic market (Kang, 2013), may impede a firm’s ability to
develop trust-based relationships with suppliers because such firms typically
source from a much wider set of suppliers (Kotabe & Mudambi, 2009). Mutual
trust and collaborations may not be easy to develop with a large number of
suppliers and hence may necessitate a firm to emphasize supplier monitoring.
The two moderating variables, therefore, allow us to produce variation in a
firm’s need to monitor suppliers’ actions vis-à-vis its ability to develop col-
laborative partnerships with them. As such, in answering our primary research
question, “is there a relationship between CSR performance and the level of
VI,” we also address how this relationship would change for firms with differ-
ent levels of (a) asset specificity and (b) international diversification.
We exploit multiple data sets to execute this study empirically. The firm
sample was drawn from U.S.-based firms listed in the S&P 500 index. CSR
performance was operationalized as firm performance on environmental,
social, and governance (ESG) issues, measurement of which was drawn from
a well-regarded Thomson Reuters ASSET4 database. Global Compustat was
used to extract input data for computing VI, asset specificity, international
diversification, and control variables. Overall, 2,715 firm-year observations
were included in our analyses. To foreshadow our results, we find a positive
relationship between a firm’s CSR performance and the level of VI. We also
find that this relationship is weaker for firms that have higher levels of either
asset specificity or international diversification.
This article advances business and society literature as follows. Our pri-
mary contributions are in the area of supply-chain CSR. We empirically dem-
onstrate that even though VI may seem to be an “extreme solution” to the
challenges of implementing supply-chain CSR (Van Buren et al., 2019, p. 19),
it is a widely adopted approach among firms with high CSR performance.
Also, we lend empirical support to previous proposals that monitoring and
trust-building are not mutually exclusive approaches (Andersen & Skjoett-
Larsen, 2009). Rather, they can co-occur and allow firms to continue with
similar levels of CSR performance and outsourcing by deepening engagement
with their suppliers and developing trust-based relationships. As such, our
results provide a multiwin prescription such that enhanced engagement with
suppliers can help firms achieve high CSR performance without having to
reduce the level of their outsourced activities. Conversely, failing to build
trust-based relationships with suppliers may require firms to reduce the level
of outsourced activities to maintain high CSR performance. The novelty of the
article, therefore, is an empirical demonstration of a dynamic relationship
between three core variables: CSR performance, VI/outsourcing, and trust and
mutual dependence between a firm and its suppliers. The article also contrib-
utes to the literature at the intersection of CSR and strategic management. By
Murcia et al. 5
showing that CSR can influence a firm’s fundamental strategic decisions, such
as VI and outsourcing, the article bolsters the observation that a firm’s strate-
gic choices and CSR performance are closely related (Panwar et al., 2016).
The article also responds to the call for improving methodological sophistica-
tion in business and society research (Crane et al., 2017), specifically by
addressing endogeneity concerns.
The rest of this article is organized as follows. Below, we first outline how
outsourcing, which is a common strategy for contemporary firms, presents
them with unique CSR challenges. At the end of this section, we speculate
that firms might find these challenges so onerous that they might decide to
reduce outsourcing and, instead, increase the level of VI. Subsequently, we
consider this speculation from a TCE viewpoint in the “Hypotheses” section,
where we propose a core hypothesis and two moderation effect hypotheses.
We then proceed to describe our empirical analysis in the “Methods and
Results” section, which is followed by a discussion wherein we describe the
theoretical implications of the article, highlight its limitations, and outline a
future research agenda. The article concludes with a brief summary note.
Literature Review
Outsourcing is a strategic alternative to insourcing. It essentially denotes a
vertical disintegration strategy, wherein a firm transfers to an external party
the activities and processes that it determines not to conduct internally (Gilley
& Rasheed, 2000). Although originally viewed as a tactical procurement
plan, outsourcing has now become a competitive strategy for contemporary
firms (Contractor et al., 2010). Its appeal is so high that it has become a
mega-trend in many industries, even those—such as automobiles—that were
once considered “the textbook example of [vertical] integration” (Jacobides,
2005, p. 465). Supply-chain management literature shows that outsourcing
can help firms access cutting-edge technologies (Li et al., 2008), skilled
workforce (Lewin et al., 2009), high-end services (Bunyaratavej et al., 2007),
the newest software applications (Verwaal et al., 2009), and superior product
designs (Ettlie & Sethuraman, 2002)—all at a lower cost than the costs
involved in developing such capabilities in-house (Gunasekaran et al., 2015).
In addition, outsourcing allows firms to better leverage their core competen-
cies (Prahalad & Hamel, 1990) and develop distributed production-based
business models to gain competitive advantage (Hätönen & Eriksson, 2009).
Such multifaceted advantages have made outsourcing a ubiquitous phenom-
enon (Lahiri, 2016).
Outsourcing also presents firms with multiple challenges that are mainly
related to supplier selection, coordination, and relationship management
6 Business & Society 00(0)
(Holcomb & Hitt, 2007; Metters & Verma, 2008). A more profound challenge,
however, and the one that is of interest to us in this article, is that outsourcing
subjects a firm to the forces of global production networks (Egels-Zandén,
2017b; Lund-Thomsen, 2013). These networks comprise not only the firms’
suppliers but also other entities such as labor organizations, trade associations,
government agencies, nongovernmental organizations, and consumers, each
with their own social and political interests (Barrientos, 2013; Levy, 2008). As
a result, a firm, even though it may have adopted outsourcing for simple eco-
nomic reasons, quickly finds itself surrounded by a complex set of social and
political stakes to which it must respond. Whether it is the unsafe working
conditions in manufacturing plants of Asian suppliers of major apparel and
footwear brands (Reinecke & Donaghey, 2015), unfair prices paid to coffee
growers in South America by large coffee companies (Kolk, 2005), use of
child labor in Africa by major electronic corporations (Cuthbertson, 2016), or
ecological crises in the tropics attributed to the destructive practices of com-
modity suppliers of well-known consumer brands (Dauvergne, 2017), it is
ultimately the outsourcing firms that are held responsible for all such upstream
wrongdoings (Schrempf-Stirling & Palazzo, 2016).
Firms adopt a variety of initiatives to ensure that their supply chains are
governed responsibly and remain free of any wrongdoing. The most popular
among these initiatives is the adoption of CSR standards (Potoski & Prakash,
2005; Waddock, 2008) which can either be industry-wide (Mena & Waeger,
2014) or specific to individual firms (Perez-Batres et al., 2012). The use of
standards has become so common that there are often multiple, competing
standards within the same industry (Husted et al., 2016; Reinecke et al.,
2012). While standards help a firm communicate CSR goals to its suppliers,
their effective implementation remains a critical challenge (Pagell &
Shevchenko, 2014; Soundararajan & Brown, 2016). Are these challenges so
profound or so costly to address that they might compel firms to reduce their
dependence on suppliers as Symrise, IKEA, and others proclaim? Do firms
that emphasize CSR performance end up reducing their levels of outsourcing
and instead increasing the levels of VI? Below we explore these issues in the
“Hypotheses” section.
Hypotheses
CSR implementation in supply chains can be considered a transaction between
a focal firm and its suppliers to whom the firm stipulates general guidelines and
specific expectations related to CSR (Cruz & Wakolbinger, 2008). This trans-
action, however, often takes place within an opaque field (Wijen, 2014),
because firms have limited access to on-the-ground information about
Murcia et al. 7
suppliers’ actions and commitments toward CSR and the steps they take—or
fail to take—to implement it (Letizia & Hendrikse, 2016). This limited access
gives rise to information asymmetries, which would increase the likelihood of
opportunistic behavior or moral hazard (Husted, 2007). To avoid these possi-
bilities, a focal firm would initiate monitoring mechanisms that allow oversight
of CSR implementation in its supply chain (Alchian & Demsetz, 1972;
O’Connell et al., 2005).
However, monitoring is a complex issue in the context of supply-chain CSR.
Foremost, it has a significant cost implication because monitoring often entails
adding new entities such as third-party certification bodies and auditors (Busse,
2016; Montiel et al., 2012; Pedersen & Andersen, 2006). These new entities add
costs for a firm not just due to the fees they charge (Dogui et al., 2014), but also
because they require a firm to develop an elaborate infrastructure so it can screen
suppliers, craft contracts, improve surveillance, develop compliance mecha-
nisms, and introduce rigorous reporting (Acquier et al., 2017; Fortanier et al.,
2011). Because a firm would then impose these requirements on suppliers, its
pool of eligible suppliers will shrink as potential suppliers might not be able to
meet CSR standards.
Even after developing such extensive infrastructure and incurring signifi-
cant monitoring costs, a firm rarely has complete, accurate, and verifiable
information about its suppliers’ actions (Heras-Saizarbitoria & Boiral, 2013)
for two reasons: a large number of suppliers typically remain unaudited
(Egels-Zandén, 2017a; Heide et al., 2007) and audit reports are not usually
that reliable. For example, Short et al. (2016) highlight that audit reports are
influenced by factors such as the gender composition of the auditing team
members, their levels of training, prior auditing experience, prior experience
with the firm being audited, and, more strikingly, whether the payments were
made by a focal firm or a supplier. The reliability of audit reports remains so
questionable that monitoring the monitors in itself has become a critical prob-
lem in supply-chain CSR management (O’Rourke, 2003). In such situations,
frictions and disputes between a focal firm and its suppliers frequently
emerge, giving rise to transactional inefficiencies due to haggling, renegotia-
tion, and adaptation (Gibbons, 2005; Williamson, 1975), and, in some cases,
due to arbitration and litigation (Ketokivi & Mahoney, 2016).
In summary, supply-chain CSR constitutes a complex transaction that
involves significant costs and uncertain outcomes. Firms that are able to
achieve high CSR performance might find it necessary to restrict the extent
of their outsourcing so they can not only reduce monitoring costs but also
ensure that their entire value chain is socially responsible. Where possible,
such firms would consider increasing their levels of VI, which would enable
them to have tighter control over their operations and leverage their internal
8 Business & Society 00(0)
hierarchies to coordinate the myriad actions that supply-chain CSR requires.
Therefore, we propose the following hypothesis:
Hypothesis 1 (H1): The higher a firm’s CSR performance, the higher its
level of VI.
While firms with high CSR performance would increase their levels of VI
to avert the challenges of implementing supply-chain CSR, they also may
seek to overcome these challenges by developing strategic partnerships with
their suppliers. The importance of such partnerships in implementing supply-
chain CSR is extensively emphasized in supply-chain CSR literature (Gold
et al., 2010; Pagell & Wu, 2009). While different studies take a somewhat
different approach to analyze these partnerships, there is a common under-
standing that in developing these partnerships, firms first identify suitable
suppliers and then engage with them in setting joint goals, adopting mutually
acceptable CSR standards, training their personnel, and developing logistical
processes (Foerstl et al., 2010; Joshi & Stump, 1999; Lim & Phillips, 2008;
Lu et al., 2012). This deep level of engagement with suppliers increases the
level of asset specificity in the relationship such that both parties—a firm and
its suppliers—can obtain higher value within the relationship than outside it
(Thauer, 2014).
Through the investment in specific assets, a firm can deepen social rela-
tions across its supply chain, promote information exchange and commit-
ment to mutual problem-solving, and facilitate adaptation for sustained and
effective exchange (Elfenbein & Zenger, 2014; Poppo & Zenger, 2002). As
supply-chain partners accumulate a common history, they codevelop rela-
tional capital with each other that builds mutual trust (Kale et al., 2000),
cooperative routines (Chassang, 2010), and an overall expectation of a con-
tinued relationship which further reinforces mutual trust (Brahm & Tarzijan,
2016).
Thus, trust breeds trust, and hence, asset specificity over time becomes a
source of collaborative advantage for firms. Firms that emphasize CSR per-
formance would be able to leverage this advantage to implement CSR within
their supply chains. Therefore, we predict that as firms’ asset specificity
increases, they would rely less on monitoring, and more on collaboration
with suppliers, which would improve their odds to effectively implement
supply-chain CSR without having to increase their levels of VI. Therefore,
we advance our second hypothesis:
Hypothesis 2 (H2): The positive relationship between CSR performance
and the level of VI would be weaker for firms with higher asset specificity.
Murcia et al. 9
A firm can develop relational capital only with a limited number of suppli-
ers. The challenges to developing relational capital are most evident in the
case of internationally diversified firms, which sell their products or services
into multiple markets that are often institutionally and culturally distinct from
one another (Marano et al., 2016). This market multiplicity complicates a
firm’s task environment, compelling it to find efficient ways to reach its dis-
persed customers (Lafontaine & Slade, 2007). Efficiency concerns lead a
firm to alter its supply-chain configurations so that it can source material and
products from multiple, specialized suppliers to cater to the needs of its mul-
tiple distinct market segments (Buckley & Ghauri, 2004; Levina & Su, 2008).
Therefore, internationally diversified firms source from a greater number of
geographically dispersed specialized suppliers, which allow a firm to reap
economies-of-specialization benefits (Kotabe & Mudambi, 2009; Mauri &
de Figueiredo, 2012).
Geographically dispersed suppliers, however, complicate the implementa-
tion of supply-chain CSR in multiple ways. First, they restrict a firm’s ability
to use a one-size-fits-all approach in developing its supply-chain CSR poli-
cies and procedures, as institutional, cultural, and normative expectations of
propriety vary across countries (Hamann et al., 2005; Jamali, 2010; Matten &
Moon, 2008). In some cases, a firm can localize its CSR policies and tools
through minor adaptation, but at times, geographically dispersed suppliers
may expose a firm to completely new CSR issues that may be challenging to
handle (Hillman & Keim, 2001; Zyglidopoulos, 2002). Firms located in the
West, for example, would struggle to effectively deal with indigenous com-
munities when they source from suppliers located in the Chilean Andes, or
issues of caste-based discrimination when they source from suppliers located
in India. Developing a comprehensive understanding of such localized issues
may require hiring specialized staff or consulting firms that would entail sig-
nificant resources. In addition, when a firm’s suppliers are geographically
spread out, a firm becomes more visible to international media and organiza-
tions, which subject the firm to a stricter scrutiny for its CSR-related actions
(Rehbein et al., 2004; Shiu & Yang, 2017; Symeou et al., 2018). As a result,
the firm faces greater pressure to effectively implement supply-chain CSR
and communicate its actions to a much wider range of audiences than a firm
that has a presence in less diversified markets.
Thus, we argue that as a firm’s international diversification increases, its
need to implement CSR increases but its ability to codevelop relational capi-
tal with suppliers decreases due to an increase in the number of suppliers. In
the absence of trust-based relationships with suppliers, diversified firms
would tend to rely on monitoring mechanisms, which, as discussed in H1,
will be riddled with significant cost implications and uncertain results.
10 Business & Society 00(0)
Therefore, we predict that firms, which emphasize CSR would be even more
likely to increase VI if they are internationally diversified. Accordingly, we
advance our third hypothesis as follows:
Hypothesis 3 (H3): The positive relationship between CSR performance
and the level of VI would be stronger for more internationally diversified
firms.
Methods and Results
Sample and Data Sources
We aggregated three separate data sets to execute this study empirically. The
first data set, Mergent Online©, was used to draw an initial sample of U.S.-
headquartered global firms listed in the S&P 500 Index. We restricted this
sample by excluding firms from financial services, insurance, real estate
trust, and media sectors because VI and outsourcing in these sectors cannot
be concretely identified and measured (Jacobides & Hitt, 2005; Morris et al.,
2016). Our final sample consisted of a panel of 278 firms representing a wide
range of industries (Table 1). The data were collected for the period 2002 to
2014, yielding 2,715 total firm-year observations.
Financial and market data—which we used to compute the dependent
variable (VI), moderating variables (firms’ asset specificity and international
diversification), and control variables (outlined later)—were retrieved from
Global Compustat. We used Thomson Reuters ASSET4 ESG scores to mea-
sure CSR performance.1
Variable Definition
CSR performance. CSR performance can be measured in multiple ways. We
used annual ESG scores from ASSET4 to construct a composite CSR index.
This data set has been used extensively to measure CSR performance in a
number of previous studies. In this data set, the environmental performance
score is based on resource-use reduction (e.g., water or energy usage), emis-
sions reduction, and product innovation; the social performance score is
based on community contributions, health and safety concerns, employee
training and development, human rights, and product responsibility; and the
governance score is based on board structure and functions, compensation
policy, protection of shareholder rights, vision and strategy, among others
(see Note 1). Consistent with previous studies (e.g., Cheng et al., 2014;
Shahzad & Sharfman, 2017), ESG scores were given equal weight in com-
puting the composite CSR performance index.
Murcia et al. 11
VI. VI is a complex construct that is conceptualized and measured both quali-
tatively and quantitatively. We chose to adopt a quantitative measure that is
better suited for cross-industry samples (Mauri & de Figueiredo, 2012). Spe-
cifically, we identified the firm’s value-added to sales ratio (VA/S), one of the
most commonly used quantitative measures of VI (e.g., Barney et al., 1992;
Lajili et al., 2007; H.-L. Li & Tang, 2010), and one especially suitable for
firms that engage in multiple cross-sector transactions (which is typically the
case for S&P 500 firms). Our choice of VA/S as a measure of VI is also
appropriate because it does not view VI (or outsourcing) as a binary construct
but rather considers it as a continuum that represents the relative level of VI
versus outsourcing (Lieberman & Dhawan, 2005).
A firm’s value-added is computed as the difference between its sales rev-
enue and the purchasing costs paid to external suppliers of products or ser-
vices (Tucker & Wilder, 1977). Sales include the value-added created by the
focal firm and all of its upstream suppliers, whereas purchases represent the
aggregated value-added created by all upstream suppliers. Following previ-
ous studies (e.g., Chen, 2017; Hutzschenreuter & Groene, 2009; Lieberman
& Dhawan, 2005), we included the sum of the following items in our calcula-
tion of the value-added: depreciation and amortization, interest expense,
labor and related expense, pension and retirement expense, incentive com-
pensation expense, income taxes, net income, and rental expense. VA/S ratios
have one main limitation: they may be distorted by changes in profitability,
or due to taxes and depreciation. To correct for such distortions, we followed
Hutzschenreuter and Groene (2009) and calculated the VA/S ratio as
follows:
Table 1. Industry Composition of Study Sample.
SIC codes Industry No. of firms
0100–1999 Mining, construction 23
2000–2390 Food, textiles, apparel 20
2391–2780 Forest products, paper, publishing 6
2781–2890 Chemicals, pharmaceuticals 26
2891–3199 Refining, rubber, plastic 7
3200–3569 Containers, steel, heavy manufacturing 17
3570–3990 Computers, autos, aerospace 66
3991–4731 Transportation 13
4732–4991 Telephone, utilities 32
4992–5990 Wholesale, retail 43
6800–8051 Hotel, entertainment 25
Total 278
12 Business & Society 00(0)
VA
S
=
VA netincomeincometaxes
salesnet income income ta
+
+
()
xxes
()
Asset specificity. Following Berrone et al. (2013), asset specificity was mea-
sured as the natural logarithm of the ratio of the book value of a buying firm’s
property, plant, and equipment to the number of employees. This ratio is con-
sidered a reliable measure of asset specificity because investments in prop-
erty, plant, and equipment are usually difficult to re-deploy and are less likely
to be valuable for other firms if the company needs to liquidate assets (De
Vita et al., 2011).
International diversification. International diversification refers to a firm’s
expansion beyond its domestic market into other regions or countries (Kang,
2013). Specifically, we measure this variable using the ratio of nondomestic
sales to total sales to capture a firm’s level of exposure to international mar-
kets (e.g., Alessandri et al., 2018; Hitt et al., 2006; Hult et al., 2008).
Control variables. We controlled for the following firm-level variables that
previous literature has identified as antecedents to VI. Financial slack, mea-
sured as a ratio of account receivables to sales, was included as a control
variable because firms with higher financial slack tend to be more vertically
integrated (Schilling & Steensma, 2002). Firm size, measured as the natural
logarithm of the firm’s assets, was included as a control variable because
larger firms tend to be more integrated (Villalonga & McGahan, 2005). We
also included as an additional control variable a firm’s degree of business
diversification because it influences a firm’s level of VI as well (Brahm &
Tarzijan, 2013). Business diversification was measured as the logarithm of
the number of business segments in which a firm operates (Hutzschenreuter
& Groene, 2009).
In addition to firm-level variables, we also included industry-fixed effects
and year-fixed effects to control for the industry and period-specific varia-
tions in the levels of VI.
Analyses
All analyses were conducted using STATA SE 12 software. Table 2 depicts
descriptive statistics and pairwise correlations among study variables.
Prior to testing our hypotheses, we first conducted a modified Wald test to
test for group-wise heteroscedasticity. Results suggested that standard errors
Murcia et al. 13
may provide biased estimates. To address this concern, we used panel-cor-
rected standard errors clustered by the firm for all our analyses. In addition,
we tested for autocorrelation using the Wooldridge (2010) test and ruled out
first-order autocorrelation among variables (p < .001). Hypotheses were
tested using ordinary least squares (OLS) regression. Results are presented in
Table 3.
Model 1 contains CSR performance, asset specificity, international diver-
sification, industry- and year-fixed effects, and firm-level control variables.
Model 2 is the full model, which also includes interaction effect variables.
Model 2 shows that the coefficient of CSR performance is positive and sig-
nificant (β = 0.1205, p < .01), providing support for H1 and suggesting that
higher CSR performance is associated with higher levels of VI.
We assessed the economic effect of CSR on VI, which is graphically rep-
resented in Figure 1. It can be seen in the figure that one standard deviation
increase in CSR performance (i.e., the mean plus one standard deviation) is
associated with a 3% increase in the level of VI. In a similar fashion, the
effect of one standard deviation decrease in CSR performance (i.e., the mean
minus one standard deviation) is associated with a 3% decrease in the level of
VI.
In testing for interaction effects, the coefficient of the interaction between
CSR and asset specificity (CSR × AS) in Model 2 is negative and significant
(β = −0.0636, p < .01), which supports H2, and suggests that the positive
Table 2. Descriptive Statistics and Pairwise Correlations.
VI CSR AS INTL Slack Size
Business
diversification
Vertical Integration
(VI)
1
CSR performance .1209** 1
Asset Specificity (AS) .3894** .1388** 1
International
diversification
(INTL)
−.1513** .236** −.1548** 1
Financial slack −.0425** .0691** .0489** .1762** 1
Firm size .2391** .5383** .3984** .1001** .1662** 1
Business
diversification
.1141** .2645** .0416** .1197** .1401** .3635** 1
Mean 0.711 0.648 9.308 0.322 0.153 9.159 2.151
Standard Deviation 0.256 0.222 1.597 0.253 0.159 1.354 0.755
Note. N = 2,715. CSR = corporate social responsibility.
**Correlations significant at p < .05.
14 Business & Society 00(0)
relationship between CSR performance and VI becomes weaker for firms with
higher levels of asset specificity. The coefficient of the interaction between
CSR performance and international diversification (CSR × INTL) is also neg-
ative and significant (β = −0.3769, p < .01). Thus, H3 was not supported and
we found that the positive relationship between CSR performance and VI
becomes weaker for firms that are more internationally diversified.
The graphs in Figures 2 and 3 provide visual supplements to the above
results. Figure 2 shows that the slope of the line illustrating the relationship
between CSR performance and VI trends downward for firms with higher
Table 3. OLS Regression Results.
Dependent variable = VI
Model 1 Model 2
Main variables
CSR performance (CSR) 0.1310***
(0.0268)
0.8332***
(0.1528)
Asset specificity (AS) 0.0528***
(0.0069)
0.0908***
(0.0129)
International diversification (INTL) −0.0300
(0.0297)
0.2145**
(0.0880)
CSR × AS −0.0636***
(0.0139)
CSR × INTL −0.3769***
(0.1013)
Controls
Financial slack −0.0696***
(0.0190)
−0.0722***
(0.0185)
Firm size 0.0083*
(0.0047)
0.0111**
(0.0048)
Business diversification 0.0229***
(−0.0079)
0.0269***
(0.0082)
Constant 0.0480
(0.0861)
0.3963***
(0.1485)
Industry-fixed effects Yes Yes
Year-fixed effects Yes Yes
No. of observations (N) 2,715 2,715
Wald χ22,306.34*** 2,327.74***
R2.2699 .2802
Note. Standard errors in parentheses. OLS = ordinary least squares; VI = vertical integration;
CSR = corporate social responsibility.
*p < .10. **p < .05. ***p < .01.
Murcia et al. 15
levels of asset specificity. Similarly, Figure 3 shows the relationship between
CSR performance and VI for firms with higher levels of international diver-
sification as a downward-trending slope.
Endogeneity Tests
To strengthen the validity of our results, we tested for endogeneity, which can
occur due to the following three main reasons: measurement error, omitted
Figure 1. Economic effect of corporate social responsibility on vertical integration.
Note. VI = vertical integration; CSR = corporate social responsibility.
Figure 2. The moderating effect of asset specificity on the level of vertical integration.
Note. VI = vertical integration; CSR = corporate social responsibility; AS = asset specificity.
16 Business & Society 00(0)
variables, and reverse causality (Wooldridge, 2010). We tested measurement
error and omitted variable bias using instrumental variables analysis and
reverse causality using simultaneous equations regression as follows.
Instrumental variables analysis. OLS regression analyses may produce biased
estimates due to measurement errors and/or omitted variables bias (Hamilton
& Nickerson, 2003), both leading to endogeneity concerns. For instance,
CSR performance may be affected by unobservable variables, which may
also affect the level of VI. To test whether endogeneity is a concern in this
study, we conducted instrumental variables analysis by using two separate
instruments for measuring CSR performance that we expect to be related to a
firm’s CSR performance but not to a firm’s level of VI.
We deployed two instruments for deducing robust inference (Garcia-
Castro et al., 2010). Our first instrument for measuring CSR performance is
lagged CSR performance (LCSR) which essentially denotes a firm’s CSR
performance in the previous year. The choice of this variable is based on the
understanding that while LCSR is expected to be related to current CSR per-
formance, it should not affect current levels of VI (Boulouta & Pitelis, 2014;
Zhao & Murrell, 2016).
Our second instrument for measuring CSR performance is the average
CSR performance for each industry-year pair, excluding the contribution of
the focal firm (INDCSR). The choice of this variable is based on previous
Figure 3. The moderating effect of international diversification on the level of
vertical integration.
Note. VI = vertical integration; CSR = corporate social responsibility; INTL = international
diversification.
Murcia et al. 17
studies which show that CSR performance is determined by industry charac-
teristics and hence industry average is a predictor of a firm’s CSR perfor-
mance (Cheng et al., 2014), but cannot be assumed to be related to the firm’s
level of VI as our measure purposively excludes the focal firm’s contribution
to the industry average.
We conducted two tests to assess whether our instruments satisfy the con-
ditions of relevance and exogeneity. The F statistic of Kleibergen–Paap rk
Wald is higher than the critical value of 12.20, suggesting that instruments are
relevant. The overidentification test (Hansen J Statistic, robust under het-
eroscedasticity) assesses whether instruments comply with the exogeneity
condition. The value obtained for the p value of the Hansen test (p = .1935)
indicates that our instruments are exogenous. These results are reported in the
lower section of Table 4.
Following Bascle (2008), we used a two-stage least squares estimation.
The first stage is meant to provide input for the second stage. Model 3 com-
prises only instruments, and Model 4 comprises interaction terms. We also
tested whether our instrumental variables model is identified. The null
hypothesis of the underidentification test (Kleibergen–Paap LM statistic) was
rejected, indicating that the model is identified for our data. IV estimation
results are presented in Table 4.
The information reported in Table 4 indicates that the instrumental vari-
ables results are consistent with the results obtained in our OLS specification.
Specifically, Model 4 (the full model) shows that, after accounting for endo-
geneity, the coefficient for CSR performance is positive and significant (β =
0.1564, p < .01), bolstering support to Hypothesis 1. The interaction term
CSR × AS is negative and significant (β = −0.0773, p < .01), bolstering
support for H2. The interaction term CSR × INTL is negative and significant
too (β = −0.4598, p < .01), bolstering rejection of H3.
We also examined whether the results obtained through two instrumental
variables we used were sensitive to our choice of instruments. To do so, we
followed Flammer and Kacperczyk (2016) and created yet another instru-
ment for evaluating CSR performance using the location of a firm’s incorpo-
ration. Some U.S. states have enacted constituency statutes (CS) providing
firms with a regulatory impetus to include social, environmental, and corpo-
rate governance objectives that go beyond financial objectives in their corpo-
rate policy (Bisconti, 2009). We extracted firm incorporation data from
Global Compustat and used the list provided by Bisconti (2009) to measure
the “constituency statute” as a dummy variable that equals “one” if the firm
is incorporated in a state that passed a CS before the study period, and “zero”
otherwise. We then replaced the previously-used instrument INDCSR with
the new instrument CS.
18
Table 4. Instrumental Variables Regression Results.
Model 3 Model 4
First stage
Second stage;
DV = VI First stage
Second stage;
DV = VI
Main variables
CSR performance 0.1629***
(0.0449)
0.1564***
(0.0447)
LCSR (Instrument 1 for CSR: lagged CSR) 0.8402***
(0.0113)
0.8381***
(0.0113)
INDCSR (Instrument 2 for CSR: industry mean of CSR) −0.0015*
(0.0008)
0.0020
(0.0073)
Asset specificity −0.0011
(0.0018)
0.0549***
(0.0090)
−0.0019
(0.0018)
0.0521***
(0.0085)
International diversification 0.0274***
(0.0093)
−0.0214
(0.0431)
0.0285***
(0.0096)
−0.0159
(0.0442)
CSR × AS −0.0773***
(0.0188)
LCSR × AS (Instrument 1 for CSR × AS) −0.0114*
(0.0054)
INDCSR × AS (Instrument 2 for CSR × AS) 0.0081
(0.0104)
CSR × INTL −0.4598***
(0.1749)
LCSR × INTL (Instrument 1 for CSR × INTL) −0.0416
(0.0365)
INDCSR × INTL (Instrument 2 for CSR × INTL) −0.0532
(0.0541)
(continued)
19
Model 3 Model 4
First stage
Second stage;
DV = VI First stage
Second stage;
DV = VI
Controls
Financial slack −0.0198**
(0.0091)
−0.0791***
(0.0196)
−0.0206**
(0.0092)
−0.0805***
(0.0193)
Firm size 0.0122***
(0.0019)
0.0072
(0.0061)
0.0129***
(0.0019)
0.0104*
(0.0061)
Business diversification 0.0005
(0.0028)
0.0203*
(0.0119)
0.0008
(0.0028)
0.0253**
(0.0122)
Industry-fixed effects Yes Yes Yes Yes
Year-fixed effects Yes Yes Yes Yes
No. of obs. (N) 2,454 2,454 2,454 2,454
F test 1653.09*** 16.97*** 1070.19*** 13.65***
(Centered) R2.8094 .0988 .8099 .1156
Kleibergen–Paap rk LM statistic
(Underidentification test)
491,355
(p = .0000)
395,111
(p = .0000)
Kleibergen–Paap rk Wald F statistic
(Weak identification test)
2,769,516
(Critical value
5% = 19.93)
661,756
(Critical value
5% = 12.20)
Hansen J statistic 0.273 4.72
(Overidentification test) (p = .6015) (p = .1935)
Note. Standard errors in parentheses. DV = dependent variable; VI = vertical integration; CSR = corporate social responsibility; AS = asset
specificity; INTL = international diversification.
*p < .10. **p < .05. ***p < .01.
Table 4. (continued)
20 Business & Society 00(0)
We conducted relevance (weak identification test) and exogeneity (overi-
dentification test) tests for this combination of instrumental variables, which
showed positive results. We also found that the model is identified (underi-
dentification test). Test results are reported toward the bottom of Table 5.
Again, results bolster support for H1 and H2 and rejection for H3.
Reverse causality/directionality test. We used simultaneous equations regres-
sion to test for potential reverse causality. To do so, we estimated a system of
two equations, one for each plausible causal direction. We instrumented VI
using the average VA/S score for each industry-year pair, excluding the focal
firm’s contribution. For CSR performance, we used average-industry CSR
performance and lagged CSR, as we did in the instrumental variables analy-
sis. We used three-stage least squares regression (3SLS) to produce consis-
tent estimates (Wooldridge, 2010). Results are reported in Table 6.
Model 8 results (i.e., the full model) suggest that CSR performance is
positively associated with higher levels of VI (β = 0.1459, p <.01); however,
VI shows no significant association with CSR performance (β = .0201,
p > .10). Hence, we find no evidence of reverse causality.
Overall, the foregoing analyses provide multiple evidence that H1 and H2
are supported, whereas H3 is not supported, and that our results are largely
free from endogeneity concerns.
Discussion
We conducted this study to examine the relationship between CSR perfor-
mance and the level of VI. Our analytical framework comprised a core
hypothesis and two moderation effect hypotheses. The results of the three
hypotheses shed new light on supply-chain CSR and strategy literature.
Our core hypothesis—predicting a positive relationship between CSR per-
formance and the level of VI—was empirically supported. This finding adds a
novel dimension to the supply-chain CSR literature where the need for supply-
chain monitoring is already recognized as a critical issue (Klassen & Vereecke,
2012), but the implications of related monitoring costs have not been consid-
ered before. Our empirical findings—that firms with higher CSR performance
tend to pursue higher levels of VI (or lower levels of outsourcing)—bolster
our underlying arguments that supply-chain monitoring costs and risks can
become so profound that firms which emphasize CSR performance may
decide to increase the proportion of the activities they conduct in-house and
decrease the proportion that they outsource. Thus, our findings not only bring
to light a neglected phenomenon in the area of supply-chain CSR, but they
also challenge the long-established notion in the strategy literature that a
21
Table 5. Regression Results With New Instrumental Variables.
Model 5 Model 6
First stage
Second stage;
DV = VI First stage
Second stage;
DV = VI
Main variables
CSR performance 0.1629***
(0.0441)
0.1556***
(0.0434)
LCSR (Instrument 1 for CSR: lagged CSR) 0.8370***
(0.0112)
0.8326***
(0.0114)
CS (Instrument 2 for CSR: constituency statute dummy) 0.0093**
(0.0040)
0.0106***
(0.0040)
Asset specificity −0.0011
(0.0018)
0.0545***
(0.0089)
−0.0015
(0.0017)
0.0518***
(0.0084)
International diversification 0.0268***
(0.0094)
−0.0206
(0.0426)
0.0271***
(0.0094)
−0.0147
(0.0437)
CSR × AS −0.0750***
(0.0185)
LCSR × AS (Instrument 1 for CSR × AS) −0.0135**
(0.0054)
CS × AS (Instrument 2 for CSR × AS) 0.0050*
(0.0027)
CSR × INTL −0.4512***
(0.1683)
LCSR × INTL (Instrument 1 for CSR × INTL) −0.0414
(0.0361)
CS × INTL (Instrument 2 for CSR × INTL) −0.0118
(0.0153)
(continued)
22
Model 5 Model 6
First stage
Second stage;
DV = VI First stage
Second stage;
DV = VI
Controls
Financial slack −0.0202**
(0.0085)
−0.0710***
(0.0202)
−0.0213**
(0.0084)
−0.0723***
(0.0195)
Firm size 0.0125***
(0.0019)
0.0070
(0.0061)
0.0134***
(0.0019)
0.0099*
(0.0061)
Business diversification 0.0002
(0.0028)
0.0204*
(0.0120)
0.0005
(0.0028)
0.0254**
(0.0121)
Industry-fixed effects Yes Yes Yes Yes
Year-fixed effects Yes Yes Yes Yes
No. of obs. (N) 2,499 2,499 2,499 2,499
F test 1,589.67*** 17.36*** 1,041.42*** 13.89***
(Centered) R2.8070 .0988 .8078 .1151
Kleibergen–Paap rk LM statistic
(Underidentification test)
504,471
(p = .0000)
432,895
(p = .0000)
Kleibergen–Paap rk Wald F statistic
(Weak identification test)
2,834,782
(Critical value
5% = 19.93)
787,842
(Critical value
5% = 12.20)
Hansen J statistic
(Overidentification test)
0.039
(p = .8432)
0.396
(p = .9411)
Note. Standard errors in parentheses. DV = dependent variable; VI = vertical integration; CSR = CSR performance; AS = asset specificity; INTL = international
diversification.
*p < .10. **p < .05. ***p < .01.
Table 5. (continued)
23
Table 6. Simultaneous Equations Regression Results.
Model 7 Model 8
DV = CSR
performance DV = VI
DV = CSR
performance DV = VI
Main variables
VI 0.0195
(0.0208)
0.0201
(0.0208)
INDVI (Instrument for VI: industry mean of VI) 0.6992***
(0.0334)
0.6902***
(0.0336)
CSR performance 0.1532***
(0.0287)
0.1459***
(0.0287)
LESG (Instrument 1 for CSR: lagged CSR) 0.8379***
(0.0108)
0.8359***
(0.0108)
INDESG (Instrument 1 for CSR: industry mean of CSR) −0.0018
(0.0032)
−0.0001
(0.0087)
Asset specificity −0.0020
(0.0022)
0.0328***
(0.0044)
−0.0028
(0.0021)
0.0307***
(0.0044)
International diversification 0.0268***
(0.0096)
−0.0241
(0.0223)
0.0278***
(0.0097)
−0.0219
(0.0222)
CSR × AS −0.0721***
(0.0137)
LCSR × AS (Instrument 1 for CSR × AS) −0.0104*
(0.0061)
INDCSR × AS (Instrument 2 for CSR × AS) 0.0058
(0.0112)
CSR × INTL −0.3395***
(0.0835)
LCSR × INTL (Instrument 1 for CSR × INTL) −0.0350
(0.0367)
INDCSR × INTL (Instrument 2 for CSR × INTL) −0.0580
(0.0605)
(continued)
24
Model 7 Model 8
DV = CSR
performance DV = VI
DV = CSR
performance DV = VI
Controls
Financial slack −0.0184
(0.0120)
−0.0782***
(0.0276)
−0.0190
(0.0120)
−0.0787***
(0.0274)
Firm size 0.0119***
(0.0021)
0.0079
(0.0051)
0.0125***
(0.0022)
0.0107**
(0.0050)
Business diversification −0.0002
(0.0029)
0.0058
(0.0068)
−0.0000
(0.0030)
0.0096
(0.0068)
Constant 0.5932***
(0.0265)
−0.3113***
(0.0581)
0.6036***
(0.0267)
−0.2937***
(0.0584)
Industry-fixed effects Yes Yes Yes Yes
Year-fixed effects Yes Yes Yes Yes
No. of obs. (N) 2,427 2,427 2,427 2,427
χ211,902.20*** 1,453.67*** 11,929.70*** 1,519.19***
R2.8306 .3743 .8309 .3844
Note. Standard errors in parentheses. DV = dependent variable; CSR = corporate social responsibility; VI = vertical integration; AS = asset specificity; INTL =
international diversification.
*p < .10. **p < .05. ***p < .01.
Table 6. (continued)
Murcia et al. 25
firm’s VI decisions are determined by economic criteria alone. Here, we show
that a firm’s concern for broader societal issues, reflected in its CSR perfor-
mance, is also an important determinant of VI. Previous literature has ana-
lyzed how CSR performance affects a firm’s strategic decisions (McWilliams
et al., 2006), but most of these studies are limited to analyzing the effect of
CSR either on a firm’s choice of competitive strategies (Panwar et al., 2016)
or on the firm’s strategic orientation (e.g., Flammer & Bansal, 2017; Flammer
& Kacperczyk, 2016; Maignan & Ferrell, 2004). We take this literature further
by demonstrating that CSR affects one of the firm’s most fundamental strate-
gic decisions, that is, the level of VI. Thus, the article integrates CSR and
strategic management at a much deeper level and suggests that CSR concerns
have grown so profound for contemporary firms that they can alter a firm’s
business model in the most fundamental way.
Our second hypothesis—predicting a negative moderation effect of asset
specificity on the relationship between CSR performance and the level of
VI—was empirically supported too. This finding has multiple implications.
First, it reinforces the importance of developing trust-based partnerships with
suppliers, which has long been emphasized in supply-chain CSR literature
(Gimenez & Tachizawa, 2012). Second, and more importantly, this finding
brings forth the fact that monitoring and collaboration-based approaches are
not mutually exclusive, but that they co-occur. In fact, the negative modera-
tion effect of asset specificity on the CSR-VI relationship explains that by
developing trust-based partnerships with some suppliers, firms can achieve
high CSR performance without having to reduce their levels of outsourcing.
In this sense, asset specificity allows a firm to balance its twin needs to
achieve high CSR performance and reap the benefits of outsourcing. The
more trust-based partnerships a firm can cultivate with its suppliers, the more
it can continue to outsource without compromising its CSR performance.
Third, while the negative moderation effect of asset specificity on the CSR-VI
relationship is reconciliatory for CSR scholars, it is rather provocative for
strategy scholars. Since Williamson’s seminal work in the 1970s, strategy
scholars have predominantly viewed asset specificity as a source of opportu-
nistic behavior by a firm’s suppliers. Their argument is that by heavily invest-
ing in fewer suppliers, a firm loses its bargaining power, which its suppliers
exploit opportunistically to their own benefit (Grover & Malhotra, 2003).
Our findings call into question this adversarial view of asset specificity
because, as we argued and empirically demonstrated, it can actually offer
firms a collaborative advantage. This collaborative view of asset specificity
also resonates with more recent supply-chain literature which depicts supply
chains as fundamentally collaborative arenas where supply-chain partners
safeguard their collective interests (Bird & Soundararajan, 2018; Ketchen &
26 Business & Society 00(0)
Hult, 2007; Krause et al., 2007). Fourth, our results show that trust-building
is a time-dependent phenomenon and hence our finding situates well with the
emerging notion of historic CSR (Schrempf, 2012; Schrempf-Stirling et al.,
2016), which explains how CSR manifests in a temporally integrated manner.
In fact, our results in H2 would suggest that this temporal integration occurs
not just within a firm as these authors argue, but it can also happen at the
supply-chain level. Repeated CSR transactions among supply-chain partners
may make CSR a routine, and hence shape future CSR practices in supply
chains.
We did not find support for our third hypothesis, which predicted a posi-
tive moderation effect of international diversification on the relationship
between CSR performance and the level of VI. Our prediction was in line
with the existing literature on multinational CSR and hence this empirical
finding is rather surprising. In deducing this hypothesis, we presupposed that
diversified suppliers would enhance the need for monitoring, but perhaps
internationally diversified firms find monitoring an unwieldy activity, espe-
cially when pursuing the multidomestic CSR strategy typical of internation-
ally diversified firms. Rather than relying on hired expertise—internally or
through external consultants—it seems that internationally diversified firms
find more feasible to develop collaborative relationships with suppliers and
rely on them to develop and implement contextually relevant CSR practices.
Our speculation is aligned with emergent literature in operations and supply
chain management which argues that supply chains are so complex that firms
have no choice but to form relational ties with their suppliers and manage
supply chains as social networks (Borgatti & Li, 2009; Lomi & Pattison,
2006). In fact, some scholars have argued that supply chains are complex
adaptive systems that constantly learn from, and adapt to, their environments
(Bode & Wagner, 2015; Choi & Krause, 2006). This would require a firm to
engage heavily with its suppliers, who better understand their context and can
provide firms with the necessary input for understanding its audience and
their CSR-related expectations, thus allowing the firm to more effectively
tailor its CSR policy to different cultural contexts.
Limitations and Future Research
The results of this study offer important insight into supply-chain CSR, but
there remain a few limitations that future studies may overcome. First, while
we tested for bidirectionality and found that the relationship in our data set is
unidirectional (from CSR to VI; not from VI to CSR), it may simply be a reflec-
tion of the research design of this study. For example, we cannot negate the
possibility of a virtuous circle such that high CSR performance necessitates
Murcia et al. 27
higher levels of VI and then higher levels of VI lead to high CSR performance
in the future. In fact, we took a preliminary step by conducting a time-lagged
regression analysis and found that a 1-year time-lagged CSR performance is a
predictor of VI. However, truly establishing a time-lagged relationship will
require a cross-lagged panel analysis (Kearney, 2017), which will constitute a
separate study altogether. We hope future research can provide a finer-grained
understanding of the time-lagged nature of the relationship between CSR per-
formance and VI. Second, it is also important to note that we propose two
interwoven factors—monitoring costs and a true concern for responsible sourc-
ing—as the key drivers of a positive relationship between CSR and the level of
VI. But, our study design does not allow us to tease apart whether the relation-
ship between CSR performance and VI is governed by cost consideration or
outcome consideration or a combination of both. In other words, our study does
not explain whether the firms with high CSR performance increase their levels
of VI due to monitoring costs or inability to effectively implement CSR initia-
tives through suppliers or both. We call supply-chain CSR scholars to conduct
follow-up studies to shed light on this ambiguity, ideally by focusing on spe-
cific corporations to conduct in-depth case studies (Goldstein & Newell, 2019).
Third, due to data set limitations, we could not consider the location of suppli-
ers as a variable in determining the CSR-VI relationship but would expect it to
influence the CSR-VI relationship. A supplier located where there are stringent
and effective social and environmental regulations will not pose the same level
of threat to the implementation of supply-chain CSR as a supplier located
where regulations are weak or poorly enforced. Similarly, a supplier located
within a cluster of socially and environmentally progressive firms will be more
inclined to implement supply-chain CSR initiatives relative to a supplier
located where social and environmental issues are not important considerations
(DeBoer et al., 2017). Therefore, future studies should consider suppliers’ loca-
tions while examining the relationship between CSR performance and VI.
Fourth, we used a composite CSR index that bundles together a number of
social and environmental issues that can, in fact, be characteristically different.
For example, firms’ response to tackle human trafficking in its supply chain
would be very different from making their supply chains deforestation-free,
even though both issues share a commonality that they are inherently systemic
in nature. Thus, while our study provides an overarching framework to exam-
ine the link between CSR and VI, future studies could examine this link sepa-
rately for specific social and environmental problems. Finally, it is also worth
noting that higher levels of VI are not a panacea for overcoming supply-chain
CSR challenges. In fact, higher levels of VI create distinct problems for a firm
because monitoring internal activities can also become a complex and tedious
task; one which a firm might simply not perform on its own due to financial or
28 Business & Society 00(0)
technical limitations. Moreover, VI can lead to new societal problems such as
corporate takeover of small businesses and displacement of disadvantaged
communities. Future studies may consider such trade-offs.
Conclusion
We initiated this study to examine the effect of CSR performance on VI. We
find that firms with high CSR performance tend to vertically integrate more
and reduce the proportion of their outsourced activities. However, the extent to
which they increase their level of VI (or, reduce outsourcing) depends on their
ability to foster collaborative, trust-based relationships with their suppliers.
Therefore, CSR and outsourcing do not manifest as an either-or scenario;
instead, they can coexist as a dynamic triad comprising CSR performance, VI/
outsourcing, and mutual trust and dependence among a firm and its suppliers.
While our study establishes that in their quest to be socially responsible,
firms tend to vertically integrate their operations, this study is simply an
important first step toward building a comprehensive understanding about
the effect of CSR on firms’ decisions related to VI and outsourcing. Our hope
is that this study will stimulate future research at the intersection of strategy
and supply-chain CSR literature, where a dovetail can provide a “win-win”
between firms’ societal obligations and their strategic priorities to leverage
the expertise of external suppliers.
Acknowledgments
The authors sincerely thank Associate Editor, Dr. Judith Schrempf-Stirling, for her
precise guidance through the review process and the three anonymous reviewers for
their valuable feedback. The authors are also thankful to Eric Hansen and Martin
Meznar for their insightful comments on the initial draft of this article.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research,
authorship, and/or publication of this article.
Funding
The authors received no financial support for the research, authorship, and/or publica-
tion of this article.
ORCID iD
Maria Jose Murcia https://orcid.org/0000-0001-8609-5634
Murcia et al. 29
Note
1. Refinitiv (formerly Thomson Reuters), ESG Data Fact-sheet. Available at:
https://www.refinitiv.com/en/financial-data/company-data/esg-research-data
(accessed February 4, 2019).
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Author Biographies
Maria Jose Murcia (PhD, University of British Columbia, Canada) is an assistant
professor at IAE Business School and Facultad de Ciencias Empresariales, Universidad
Austral, Argentina. She conducts research in the broad fields of corporate sustainabil-
ity and strategy, which she has published in such journals as Business & Society,
Journal of Business Ethics, and Management Learning, among others.
Murcia et al. 39
Rajat Panwar (PhD, Oregon State University; DBA, Grenoble Ecole de Management,
France) is an associate professor in the Walker College of Business, Appalachian
State University, Boone, NC, USA. He conducts firm and industry level research in
broad fields of corporate social responsibility and corporate sustainability, which he
has published in such journals as Business & Society, Business Strategy &
Environment, Journal of Business Ethics, Journal of Public Affairs, and Organization
& Environment, among others.
Jorge Tarzijan (PhD in Managerial Economics & Strategy, Kellogg Graduate School
of Management, Northwestern University) is a full professor at the School of
Management, Pontificia Universidad Católica de Chile, Santiago, Chile. He conducts
research in corporate strategy, firm boundaries, and business models and has pub-
lished several articles in Strategic Management Journal. He has also published in
Harvard Business Review, Industrial and Corporate Change, Journal of Business
Research, Journal of Economic Behavior and Organization, Journal of Supply Chain
Management, and Long Range Planning, among others.
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