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A Configurational Approach RELATIONSHIP DETERMINANTS OF PERFORMANCE IN SERVICE TRIADS: A CONFIGURATIONAL APPROACH ANTONIOS KARATZAS University of Warwick MARK JOHNSON University of Warwick MARKO BASTL Marquette University The increasing popularity of service-based strategies among manufacturers, such as solution provision, makes service triads commonplace within busi- ness. While there is some consensus that “relational” (i.e., close or collabo- rative) relationships are beneficial for the performance of individual actors and the triad as a whole, there is little known about what exactly affects the service performance of an actor in these triads. In this study, we inves- tigate the influence of the manufacturer–service supplier relationship on the performance of the service supplier toward the manufacturer’s cus- tomers. As this phenomenon is causally complex and context dependent, we assume that there will be alternative configurations of relationship characteristics and contingent factors that lead to high service perfor- mance. To uncover potential configurations, we deployed fuzzy-set qualita- tive comparative analysis, on data collected from 38 triads within the network of a large Anglo-German commercial vehicle manufacturer. Our research shows that—in this context—superior service performance cannot be generalized to one relationship configuration and is also contingent upon exogenous factors—that is, contract support and service site size. We uncovered four “core” configurations of relationship dimensions and two exogenous factors. Three of the configurations exhibited relational proper- ties, while the fourth configuration had transactional properties. This is counter to extant research findings. We extend the perspective that within triads, service performance is not an outcome of a single “close,” or “col- laborative” relationship and is a combination of multiple configurations consisting of varying relationship dimensions and exogenous factors. Keywords: service triads; relationship determinants; service performance; fuzzy-set qualitative comparative analysis Acknowledgments: This work was funded under the auspices of the Engineering and Physical Sciences Research Council (EPSRC) INTRODUCTION —Innovative Manufacturing Research Centre (IMRC) Initiative, Services for equipment are frequently outsourced to grant number IMRC151. We would also like to thank the partic- third parties. These services are accessed either on an ipants of the 2013 International QCA expert workshop in Zurich ad hoc basis, using a maintenance contract, or as part for their valuable input. We are particularly indebted to Dr. of a “solution” where the customer pays for the use of Johannes Meuer from ETH Zurich, Dr. Santi Furnari from CAAS —or access to—equipment (Johnson, Christensen & Business School London, Prof. Leroy White from Warwick Busi- Kagermann, 2008; Visnjic-Kastalli & Van Looy, 2013). ness School, and Prof. Alex Stewart from Marquette University In the case of maintenance, repair, and overhaul for their advice on earlier versions of the paper, as well as dur- (MRO) contracts and solutions delivered by third ing the review process. 28 Volume 52, Number 3 Relationship Determinants of Performance in Service Triads parties, the customer has a contract with the equip- supply chain performance (Gartner, 2015). These ment manufacturer for both equipment and services, observations agree with empirical research that has with services delivered by a third party. This creates a found that superior firm performance can be an out- service triad (Wynstra, Spring & Schoenherr, 2015). come of different relationship types (Cannon & Per- Service triads have become a prominent topic in the reault, 1999; Vesalainen & Kohtamaki, 2015). While supply chain management discipline (Wynstra et al., these real-world examples and empirical research are 2015). The main pillar of triadic research, and the from dyads, we suggest that the outcomes also hold fundamental premise of this work, is that the perfor- within triads. We posit that the interplay between rela- mance of the three actors and the relationships tionship connectors and performance is causally com- between them are interdependent. In a triad, a dyadic plex and contingent upon contextual variables. Thus, relationship can affect another dyadic relationship we propose that there are multiple, alternative relation- and an actor can influence, or be influenced by, the ship profiles that equifinally (Doty, Glick & Huber, relationship between the other two actors (Choi, 1993) enhance performance. To investigate this, we Ellram & Koka, 2002; Havila, Johanson & Thilenius, adopt a configurational approach to identify configura- 2004; Lazzarini, Claro & Mesquita, 2008; Rossetti & tions of relationship connectors (i.e., information Choi, 2008; Wu & Choi, 2005). Thus, in service tri- exchange, cooperative norms, legal bonds, adaptations, ads, the customer’s ongoing satisfaction and their per- and operational linkages) and microlevel contingent ception of their relationship with the manufacturer is factors (i.e., supplier size and proportion of supplier dependent upon the performance of the service sup- overall revenues coming from supporting solutions) plier (Raassens, Wuyts & Geyskens, 2014; Tate & van that lead to the superior service performance of the der Valk, 2008). MRO supplier toward the customer. A configurational The focus of this study is to understand the role that approach is fully in line with contingency theory that the relationship between the manufacturer (or provi- looks for “ideal types” and “fit” between constellations der) and the service supplier (in this case MRO ser- of characteristics and the environment (cf. Fiss, 2011; vices) plays in the performance of the service supplier Meuer, 2014; Ragin, 2008). Here, we specifically toward the provider’s customers. Counter to existing employ fuzzy-set qualitative comparative analysis research that treats relationships within the triad as (fsQCA), a set-theoretic analytic technique whose aim monolithic (i.e., collaborative or competitive, positive is to uncover configurations of variables (in fsQCA ter- or negative; cf. Choi & Kim, 2008; Choi & Wu, minology: conditions) that bring about a given outcome 2009a; Lazzarini et al., 2008; Wu & Choi, 2005), we (Ragin, 2008). adopt Cannon and Perreault’s (1999) multidimen- The adoption of a multidimensional framework, in sional framework of relationship connectors. We adopt conjunction with a configurational approach, facili- this framework to create a more nuanced view of the tates the creation of a more nuanced view compared relationships between the provider and its service sup- with basic assertions such as that closer, collaborative pliers. This is in line with the wider buyer–supplier relationships in the triad lead to better outcomes relationship research that renders the distinction (Choi & Kim, 2008; Wu, Choi & Rungtusanatham, between cooperative and competitive relationships an 2010). We contribute to the study of service triads oversimplification (Cannon & Perreault, 1999; Kim & while elaborating theory about the effect of the Choi, 2015; Monczka, Petersen, Handfield & Ragatz, provider–service supplier relationship (a dyad within 1998; Morris, Brunyee & Page, 1998). a triad) on the service performance of the supplier In addition to assuming that the relationship is multi- toward the third actor (customers). Our first contribu- dimensional, and in line with previous triadic research, tion is to show that relationship influences on perfor- we adopt a contingency-theoretic approach (cf. Wu & mance are causally complex (cf. Ragin, 2008) and Choi, 2005). Therefore, there is no single manufac- contingent upon context. We identify a number of turer–service supplier relationship type that elicits supe- alternative configurations that equifinally enhance the rior service performance. Rather, performance is supplier’s service performance, indicating that there is dependent upon the relationship connectors as well as not one single, generalizable, “good” relationship external (contingent) factors. For example, considering type. Furthermore, we uncover that superior service dyadic relationships within the UK grocery sector, performance in service triads is not just a result of dif- Tesco has delisted some products from Coca-Cola ferent configurations of relationship dimensions but is (Telegraph, 2015) indicating the lack of a cooperative also contingent upon factors extraneous to the relationship, and a reliance upon formal governance. provider–service supplier relationship. This is where Despite their reliance on contracts, Tesco has main- we position our second contribution. These factors are tained a close and collaborative relationship with Proc- the size of the service supplier, and the proportion of ter and Gamble (Logistics Manager, 2013). However, its revenues that comes from supporting solutions both Coca-Cola and Procter and Gamble exhibit high contracts between the manufacturer and its customers July 2016 29 Journal of Supply Chain Management (termed here “contract support”). Experience of and negative, collaborative versus adversarial). This classifi- exposure to services as part of customer solutions, in cation is “blunt” (Mena et al., 2013, p. 73) and the form of contract support, has, to date, not been ignores the multidimensional nature of buyer–supplier considered in the study of service triads. Our third relationships (Monczka et al., 1998; Morris et al., and last contribution is to show that the absence of a 1998). To address this,
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