Relationship Determinants of Performance in Service Triads: A Configurational Approach

• Author: Marko Bastl,Antonios Karatzas,Mark Johnson
• Published date: 01 July 2016
• Date: 01 July 2016
• DOI: http://doi.org/10.1111/jscm.12109

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 bu si-

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

INTRODUCTION

Services for equipment are frequently outsourced to

third parties. These services are accessed either on an

ad hoc basis, using a maintenance contract, or as part

of a “solution” where the customer pays for the use of

—or access to—equipment (Johnson, Christensen &

Kagermann, 2008; Visnjic-Kastalli & Van Looy, 2013).

In the case of maintenance, repair, and overhaul

(MRO) contracts and solutions delivered by third

Acknowledgments: This work was funded under the auspices of

the Engineering and Physical Sciences Research Council (EPSRC)

—Innovative Manufacturing Research Centre (IMRC) Initiative,

grant number IMRC151. We would also like to thank the partic-

ipants of the 2013 International QCA expert workshop in Zurich

for their valuable input. We are particularly indebted to Dr.

Johannes Meuer from ETH Zurich, Dr. Santi Furnari from CAAS

Business School London, Prof. Leroy White from Warwick Busi-

ness School, and Prof. Alex Stewart from Marquette University

for their advice on earlier versions of the paper, as well as dur-

ing the review process.

Volume 52, Number 328

parties, the customer has a contract with the equip-

ment manufacturer for both equipment and services,

with services delivered by a third party. This creates a

service triad (Wynstra, Spring & Schoenherr, 2015).

Service triads have become a prominent topic in the

supply chain management discipline (Wynstra et al.,

2015). The main pillar of triadic research, and the

fundamental premise of this work, is that the perfor-

mance of the three actors and the relationships

between them are interdependent. In a triad, a dyadic

relationship can affect another dyadic relationship

and an actor can influence, or be influenced by, the

relationship between the other two actors (Choi,

Ellram & Koka, 2002; Havila, Johanson & Thilenius,

2004; Lazzarini, Claro & Mesquita, 2008; Rossetti &

Choi, 2008; Wu & Choi, 2005). Thus, in service tri-

ads, the customer’s ongoing satisfaction and their per-

ception of their relationship with the manufacturer is

dependent upon the performance of the service sup-

plier (Raassens, Wuyts & Geyskens, 2014; Tate & van

der Valk, 2008).

The focus of this study is to understand the role that

the relationship between the manufacturer (or provi-

der) and the service supplier (in this case MRO ser-

vices) plays in the performance of the service supplier

toward the provider’s customers. Counter to existing

research that treats relationships within the triad as

monolithic (i.e., collaborative or competitive, positive

or negative; cf. Choi & Kim, 2008; Choi & Wu,

2009a; Lazzarini et al., 2008; Wu & Choi, 2005), we

adopt Cannon and Perreault’s (1999) multidimen-

sional framework of relationship connectors. We adopt

this framework to create a more nuanced view of the

relationships between the provider and its service sup-

pliers. This is in line with the wider buyer–supplier

relationship research that renders the distinction

between cooperative and competitive relationships an

oversimplification (Cannon & Perreault, 1999; Kim &

Choi, 2015; Monczka, Petersen, Handfield & Ragatz,

1998; Morris, Brunyee & Page, 1998).

In addition to assuming that the relationship is multi-

dimensional, and in line with previous triadic research,

we adopt a contingency-theoretic approach (cf. Wu &

Choi, 2005). Therefore, there is no single manufac-

turer–service supplier relationship type that elicits supe-

rior service performance. Rather, performance is

dependent upon the relationship connectors as well as

external (contingent) factors. For example, considering

dyadic relationships within the UK grocery sector,

Tesco has delisted some products from Coca-Cola

(Telegraph, 2015) indicating the lack of a cooperative

relationship, and a reliance upon formal governance.

Despite their reliance on contracts, Tesco has main-

tained a close and collaborative relationship with Proc-

ter and Gamble (Logistics Manager, 2013). However,

both Coca-Cola and Procter and Gamble exhibit high

supply chain performance (Gartner, 2015). These

observations agree with empirical research that has

found that superior firm performance can be an out-

come of different relationship types (Cannon & Per-

reault, 1999; Vesalainen & Kohtamaki, 2015). While

these real-world examples and empirical research are

from dyads, we suggest that the outcomes also hold

within triads. We posit that the interplay between rela-

tionship connectors and performance is causally com-

plex and contingent upon contextual variables. Thus,

we propose that there are multiple, alternative relation-

ship profiles that equifinally (Doty, Glick & Huber,

1993) enhance performance. To investigate this, we

adopt a configurational approach to identify configura-

tions of relationship connectors (i.e., information

exchange, cooperative norms, legal bonds, adaptations,

and operational linkages) and microlevel contingent

factors (i.e., supplier size and proportion of supplier

overall revenues coming from supporting solutions)

that lead to the superior service performance of the

MRO supplier toward the customer. A configurational

approach is fully in line with contingency theory that

looks for “ideal types” and “fit” between constellations

of characteristics and the environment (cf. Fiss, 2011;

Meuer, 2014; Ragin, 2008). Here, we specifically

employ fuzzy-set qualitative comparative analysis

(fsQCA), a set-theoretic analytic technique whose aim

is to uncover configurations of variables (in fsQCA ter-

minology: conditions) that bring about a given outcome

(Ragin, 2008).

The adoption of a multidimensional framework, in

conjunction with a configurational approach, facili-

tates the creation of a more nuanced view compared

with basic assertions such as that closer, collaborative

relationships in the triad lead to better outcomes

(Choi & Kim, 2008; Wu, Choi & Rungtusanatham,

2010). We contribute to the study of service triads

while elaborating theory about the effect of the

provider–service supplier relationship (a dyad within

a triad) on the service performance of the supplier

toward the third actor (customers). Our first contribu-

tion is to show that relationship influences on perfor-

mance are causally complex (cf. Ragin, 2008) and

contingent upon context. We identify a number of

alternative configurations that equifinally enhance the

supplier’s service performance, indicating that there is

not one single, generalizable, “good” relationship

type. Furthermore, we uncover that superior service

performance in service triads is not just a result of dif-

ferent configurations of relationship dimensions but is

also contingent upon factors extraneous to the

provider–service supplier relationship. This is where

we position our second contribution. These factors are

the size of the service supplier, and the proportion of

its revenues that comes from supporting solutions

contracts between the manufacturer and its customers

July 2016

Relationship Determinants of Performance in Service Triads

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