The Coevolution of Relationship Dominant Logic and Supply Risk Mitigation Strategies

Published date01 June 2016
Date01 June 2016
DOIhttp://doi.org/10.1111/jbl.12126
The Coevolution of Relationship Dominant Logic and Supply Risk
Mitigation Strategies
Lutz Kaufmann
1
, Craig R. Carter
2
, and Johan Rauer
1
1
WHU Otto Beisheim School of Management
2
W.P. Carey School of Business, Arizona State University
How and why do risk mitigation strategies evolve? And which resources are needed for engaging in such changes? This paper contributes
to the understanding of risk management in supply chains by developing theory about the interplay between supply risk mitigation strate-
gies and the purchasing teams relationship dominant logic (RDL), which we dene as the purchasing teams orientation toward and shared cog-
nitive map of the management of its supply chain relationships. Specically, we propose that RDL and supply risk mitigation strategies are
fundamentally intertwined. Following a Straussian approach to grounded theory, this study analyzes data generated from the purchasing teams
of Western green-tech rms trying to mitigate supply risk for technically indispensable rare earth metals from China. Our ndings from this
context that is heavily shaped by state-inuenced supply chain members show that the rms chose their mitigation strategies in line with their
RDL. Human capital, social capital, and nancial capital seem to moderate the link between RDL and mitigation strategies. We link our nd-
ings with the strategic management literature in deriving theoretical propositions concerning these relationships.
Keywords: risk management; evolution; relationship dominant logic; resources; rare earth metals; grounded theory
INTRODUCTION
The supply chain management (SCM) literature has identied
myriad supply risk mitigation strategies (e.g., Zsidisin and Hart-
ley 2012a,b). Further, the SCM literature has extended its focus
from studying single companies (buyer or supplier) to investigat-
ing dyads of buyers and suppliers, and further, to more recently
investigating SCM in networks of buyers and suppliers (Choi
and Wu 2009; Mena et al. 2013; Carter et al. 2015). However,
the extant literature has remained relatively silent about how and
why supply risk mitigation strategies evolve over time from uni-
lateral actions taken by single supply chain members (buyers or
suppliers) to combined supply risk mitigation strategies which
involve relationship dynamics in dyads or networks of buyers
and suppliers (risk mitigation dynamics). Finally, the SCM litera-
ture has largely ignored political supply risk, which is surprising,
given that supply chain members are increasingly either state-
owned or signicantly inuenced by national policy agendas
(The Economist 2012; Whittington 2012). These omissions in
the literature provide an important opportunity to better under-
stand how managers can develop more effective supply risk
strategies from a temporal rather than a static context.
We address this opportunity by using a grounded theory
approachfollowing the Straussian school of thoughtas miti-
gating risk in a supply chain context can be considered a phe-
nomenon with complex attitudinal and behavioral dimensions
(Fugate et al. 2006, 2008; Flint and Golicic 2009; Mello and
Flint 2009; Nilsson and Gammelgaard 2012; Wesley and Mello
2012). In particular, we followed Strauss (1987) and entered the
eld with (1) the predened research question of how and why
risk mitigation strategies in a supply chain context might evolve,
(2) the initial idea that rms might need to move beyond unilat-
eral action to address these risks, and (3) the goal of developing
theoretical propositions that guide further SCM research to study
the evolution of supply risk mitigation strategies.
The unit of analysis is the mitigation strategy (or strategies)
that Western green-tech companies use to address supply risk
related to heavy rare earth metals (HREMs). Our sample includes
six Western green-tech product manufacturers producing electric/
hybrid vehicles, solar collectors, and wind turbines, as well as
six Western green-tech component suppliers that supply batteries,
catalysts, glass and ceramics, luminaries, and magnets to the
manufacturers in our sample. We base our investigation on inter-
views with 31 supply chain/purchasing managers from these 12
Western green-tech companies, which source technically indis-
pensable HREMs from Chinese sole suppliers (U.S. DOE 2011).
Given their ongoing dependence on Chinese HREM suppliers,
these companies are forced to rene and possibly expand their
existing repertoire of supply risk mitigation strategies to achieve
a lasting, viable HREM supply situation. In particular, the speed
of development from a nonthreatening to a tense supply situation
makes the HREM case an appropriate research context because it
allows us to examine the evolution of mitigation strategies within
a narrow time frame.
We nd that in these companies, the supply risk mitigation
strategies coevolve with what we conceptualize as the relation-
ship dominant logic (RDL), which is the purchasing teams ori-
entation toward and shared cognitive map for managing its
supply chain relationships. This coevolution emerges as the
main themeor core category based on our Straussian approach
to grounded theory (Strauss 1987; Fugate et al. 2006, 2008; Flint
and Golicic 2009; Mello and Flint 2009; Nilsson and Gammel-
gaard 2012; Wesley and Mello 2012). Specically, we identify
three types of RDLs: company-centric, in which the purchasing
team conceptualizes a sourcing context as one requiring unilat-
eral attempts to mitigate risk; dyad-centric, in which the purchas-
ing team views attempts to engage and collaborate with its rst-
tier suppliers as being necessary; and network-centric, where the
Corresponding author:
Lutz Kaufmann, Professor of Supply Management, WHU Otto
Beisheim School of Management, Burgplatz 2, 56179 Vallendar,
Germany; E-mail: kaufmann@whu.edu
Journal of Business Logistics, 2016, 37(2): 87106 doi: 10.1111/jbl.12126
© Council of Supply Chain Management Professionals
purchasing team interprets the context as requiring engagements
with supply chain members beyond the buyersupplier dyad.
These RDLs coevolve with the companiessupply risk mitigation
strategies.
Given this research focus, our contribution is threefold. First,
and as noted previously, the extant literature has not yet pro-
vided insights about how and why supply risk mitigation strate-
gies change over time, so a key contribution to the SCM
literature is our investigation of the evolution of supply risk
mitigation strategies.
Second, this study extends the focus of the extant research by
investigating the evolution-critical resources that rms use to
mitigate supply risk (Defee and Fugate 2010; Beske 2012; Paul-
raj et al. 2012; Crook and Esper 2014; Esper and Crook 2014).
According to Esper and Crook (2014), the concept of re-
sourceshas emerged as a foundational aspect of [SCM] knowl-
edge and research inquiry(p. 3). However, the extant SCM
research that encompasses resources has generally applied the
resource-based view (RBV) (Wernerfelt 1984; Barney 1991) to
study the role of resources in achieving competitive advantages
for supply chain operations, logistics, and procurement (Crook
and Esper 2014). Thus, little research has focused specically on
studying the role of the resources that rms or dynamic networks
of rms apply to mitigate supply risk (Defee and Fugate 2010;
Beske 2012; Paulraj et al. 2012). This research gap seems all the
more surprising, given current supply chain complexities and the
increasingly relevant theme of boundary-spanning networks
among supply chain actors (Choi and Wu 2009; Mena et al.
2013; Carter et al. 2015). We advance the knowledge in this area
by identifying evolution-critical resources that rms might need
to deploy to effectively mitigate supply risk (Defee and Fugate
2010; Beske 2012; Paulraj et al. 2012; Crook and Esper 2014;
Esper and Crook 2014).
Third, we open up a discussion on the locus of deployment of
supply risk mitigation strategies, based on our nding that the
responsibility for selecting and implementing supply risk mitiga-
tion strategies undergoes a rm-internal shiftfrom the SCM/
purchasing functions to the general management and strategy
functions.
We now turn to introducing the theoretical foundation,
describing the study, and then synthesizing and discussing the
results before concluding with suggestions for prospective
research and implications for managers.
THEORETICAL FOUNDATION
Supply risk mitigation strategies
Supply risk is a supply side-related and therefore specic cate-
gory of supply chain risk. It can be dened as the possibility that
an event associated with inbound supply might lead to the inabil-
ity of the buying rm to meet its customer demand within antici-
pated costs (Zsidisin et al. 2004; Manuj and Mentzer 2008). For
example, supply risk, or supply side-related supply chain risk,
refers to a rms dependence on single supply chain partners
(e.g., Spekman and Davis 2004; Hendricks and Singhal 2005),
exposure to upstream suppliersnancial instabilities (e.g., Bode
et al. 2011, 2014; Zsidisin and Hartley 2012b), and potential
opportunistic supplier behavior (e.g., Giunipero and Eltantawy
2004). It includes both availability risk and price risk. In addi-
tion, policy risks that have their origin in actions of national gov-
ernments, such as quota restrictions, can manifest themselves as
supply risks (Manuj and Mentzer 2008).
A supply risk mitigation strategy is the action of dealing with
an identied and assessed supply risk event to lessen its impact
if it occurs (e.g., Zsidisin and Hartley 2012a,b). Prior research
has found that rmsstrategies of using multiple suppliers or
switching suppliers (e.g., Knemeyer et al. 2009; Wang et al.
2010) are effective in mitigating supply side-related supply chain
risks. Furthermore, Bode et al. (2011) identify rmsbuffering
and bridging strategies as effective mitigation strategies. By
applying buffering strategies, such as building up inventory,
rms can reduce exposure to a current exchange partner. By
using bridging strategies, such as investing in collaborative struc-
tures through intensied information exchange with suppliers,
rms can enhance the degree of trust, mutual control, and joint
collaboration underlying their buyersupplier relationships (Bode
et al. 2011; Zsidisin and Hartley 2012a).
Relationship dominant logic
The concept of dominant logic was developed in the strategic
management discipline by Prahalad and Bettis (1986). A domi-
nant general management logic is dened as the way in which
managers conceptualize the business and make critical resource
allocation decisionsbe it in technologies, product development,
distribution, advertising, or in human resource management
(Prahalad and Bettis 1986, 490). In other words, the mindset or
world view or conceptualization of the businessis stored as a
shared cognitive map (or set of schemas)(Prahalad and Bettis
1986, 491). It encompasses key assumptions and heuristics that
managers use to perceive, interpret, and evaluate a particular
business environment (Kor and Mesko 2013, 235). Therefore,
resource deployment decisions in the rm are shaped by man-
agersdominant logic.
Dominant logics can extend to all functions of the rmfor
example, the dominant logic of solutions selling (Tuli et al.
2007) and the service-dominant logic in marketing (Vargo and
Lusch 2004; Ng et al. 2012; Osborne and Ballantyne 2012). We
conceptualize the dominant logic in the purchasing function,
which represents the key interface with upstream members of the
supply chain, as focusing both internally and externally on sup-
plier relationships. Consequently, we dene a purchasing teams
RDL as its orientation toward and shared cognitive map for
managing its supply chain relationships. It is the way in which
purchasing managers conceptualize a sourcing context and make
critical decisions about the allocation of resourceshuman capi-
tal, social capital, and nancial capitalin managing their supply
chain relationships. As such, the concept of RDL differs from
relationship norms, which are shared expectations about the
behavior of other supply chain member(s) (Heide and John
1992). The dominant logic of a purchasing team, for example, an
HREM task force, will therefore also guide its decision making
on risk mitigation strategies. For example, if a team conceptual-
izes a supply disruption as a temporary event, this will lead to
different mitigation strategies, such as supplier switching, in con-
trast to the team perceiving the disruption as part of a structural
88 L. Kaufmann et al.

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