Reconciling Perspectives on Clusters: An Integrative Review and Research Agenda

Published date01 January 2020
DOIhttp://doi.org/10.1111/ijmr.12216
Date01 January 2020
International Journal of Management Reviews, Vol. 22, 75–98 (2020)
DOI: 10.1111/ijmr.12216
Reconciling Perspectives on Clusters: An
Integrative Review and Research Agenda
Dani¨
el Speldekamp , Ayse Saka-Helmhout and Joris Knoben
Institute for Management Research, Radboud University, PO Box 9108, 6500 HK, Nijmegen, The Netherlands
Corresponding author email: d.speldekamp@fm.ru.nl
Although our understanding of clustersand their contribution to economic performance
has improvedover the last three decades, the literature has become host to a wide array
of divergent empirical and theoretical claims. We systematically review cluster studies
published in top journals, highlighting the lack of integration among prior work.We fo-
cus on the waysin which Porter’s threecluster dimensions, namely geography,networks,
and institutions, have been utilized. None of the studies reviewed fully captured their
complex interrelationships, which we argue is an important cause of the key disagree-
ments in the literature. Configurational theorizing and analysis are presentedas means
by which the different approaches to cluster studies could be reconciled. We discuss
how the application of a configurational approachcan help explore new scholarly direc-
tions that can deepen our understanding of clusters and their performance-enhancing
potential. In doing so, we can move beyond an understanding of independent effects to
emphasizing combinations of attributes that can generate multiple pathways to cluster
performance outcomes.
Introduction
Since Porter’s (1990a, 1990b, 1998) cluster concept
surfaced almost three decades ago, it has assumed a
central role in both the academic and policy discourse
on regional economic development (Lazzeretti et al.
2014; Martin and Sunley 2003; Wolmanand Hincapie
2014). The concept has become a core research topic
not only in management (e.g. Arikan 2009) and eco-
nomics (Golman and Klepper 2016), but also in dis-
ciplines such as economic geography (Asheim et al.
2008), urban planning (Turok and Bailey2004), soci-
ology (Jonas and Berner 2010), and political science
(den Hertog et al. 2001). Although our understanding
of clusters and their contribution to economic per-
formance has improved over the last three decades,
the literature has become fragmented and confused,
with contrasting theoretical claims and contradictory
empirical results describing how clusters generate in-
novation and economic growth (Martin and Sunley
2003; Wolman and Hincapie 2014).
Drawing on the definition of clusters as ‘geo-
graphic concentrations of interconnected companies
and institutions in a particular field’ (Porter 1998,
p. 78) we delineated three central dimensions: geog-
raphy, networks, and institutions. Geographic prox-
imity reduces input costs and may lead to knowl-
edge spillovers and productivity gains (Arikan and
Schilling 2011; Krugman 1991; McCann and Folta
2008). Furthermore, knowledge can be transmitted
between network partners, spurring innovation (Gor-
don and McCann 2000; Huggins and Thompson
2013; Knoben and Oerlemans 2012). The cluster
concept also incorporates the role of institutions
in recognition of the influence that institutional
regimes and structures have on organizational ca-
pabilities and innovation strategies (Allen 2013;
Casper and Whitley 2004; Hotho 2014; Whitley
2007).
Although Porter’s (1998) work continues to be
influential in shaping cluster research, it is well
documented that the research trajectories on clusters
are divergent (Cruz and Teixeira 2010; Hervas-Oliver
et al. 2015; Lazzeretti et al. 2014; Martin and
Sunley 2003). First, economic geography studies
continue to debate whether diverse or specialized
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C2019 The Authors. International Journal of Management Reviews publishedby British Academy of Management and John
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76 D. Speldekamp et al.
agglomerations drive innovation and economic per-
formance (Beaudry and Schiffauerova 2009). Second,
there is contention in the literature on whether sparse
or dense interconnectedness supports the innovation
efforts of firms (Alguezaui and Filieri 2010). Third,
at the intersection between geography and networks,
it is uncertain whether value is derived from being
located in a cluster (Bathelt et al. 2004) or being
embedded in extra-local (often global) networks
(Fitjar and Rodriguez-Pose 2011). Fourth, in cluster
studies focusing on institutions, there is considerable
uncertainty regarding whether it is optimal to coor-
dinate clusters through associational communities
or formal societal institutions (Rodr´
ıguez-Pose and
Storper 2006). Although various studies have pro-
posed new contingencies (e.g. Ter Wal et al. 2016)
and complex interrelationships to address these
contentions (Rodr´
ıguez-Pose and Storper 2006),
the reported findings remain disparate (Funk 2014).
For instance, a new line of research is investigating
how firm endowments such as the level of internal
knowledge impact the effects of agglomeration
economies (Hervas-Oliver et al. 2018; Knoben et al.
2016). However, even here there are considerable
disagreements about which types of firms benefit
from particular externalities (Frenken et al. 2015;
Grillitsch and Nilsson 2017, 2019; Rigby and Brown
2015).
Our integrative review beginswith a description of
our methods, where we outline how we used Porter’s
(1998) three cluster dimensions as a frameworkfor se-
lecting and analyzing papers. We then systematically
unpack the literature and its distinct perspectives, ad-
dressing the commonalities and differences between
studies. We identify that the long-standing disagree-
ments in the literature are a consequence of the lim-
ited attention paid to the complementarity between
cluster dimensions, and discuss the reconciliatory po-
tential of a configurational approach. Configurational
theorizing emphasizes conjunction, equifinality, and
asymmetry. In other words,outcomes are likely to re-
sult from combinations of all three cluster dimensions
and their interrelations (Fiss 2011). These attributes
and their combinations can be either necessary or suf-
ficient for an outcome (Misangyi et al. 2017). More-
over, there may be multiple pathways to an outcome,
and the inverse of factors leading to its presence do
not necessarily cause its absence (Greckhamer et al.
2008). We demonstrate how such a theoretical ap-
proach can be combined with qualitative comparative
analysis (QCA).
Methodology
We adopted a systematic methodology to research
the performance implications of clusters found in the
literature, taking Porter’s (1998) conceptualization as
the starting point. Wethus followed a fixed framework
or ‘architecture’ with the three cluster dimensions
as the building blocks (Adams et al. 2016). In line
with procedures followedin prior work, we combined
methodological rigor and transparency with an in-
depth analysis (Boyd and Solarino 2016; Knoben and
Oerlemans 2006; Phelps et al. 2012; Tranfield et al.
2003). This systematic review procedure enabled us
to identify divergent empirical claims in the academic
literature and point to, what we believe to be, fruitful
lines of future research (Rousseau et al. 2008).
Figure 1 details our research approach, as well as
the number of papers excluded and remaining at every
stage. We started by selecting the literature database
and relevant archived journals, and then created key-
words based on the three cluster dimensions to con-
struct our search queries. Followingthis, we generated
a bibliometric overview of the literature and its use of
the different cluster dimensions. Wecoded papers on
whether they were empirical and relevant, and inves-
tigated their theoretical and empirical approaches to
clusters. This analysis is the foundation of our litera-
ture synthesis. In the sections below, our methodology
is described at length.
Database
As shown in Figure 1, an important tool for our sys-
tematic literature review was the Thomson Reuters
Web of Science (2018a) database, which provided us
with a wide range of searchable journals, as well as
a powerful search engine. Our use of this database is
consistent with other reviews on cluster research (e.g.
Hervas-Oliver et al. 2015; Lazzeretti et al. 2014).
To attain a detailed review of state-of-the-art clus-
ter research, we limited ourselves to journals with
an Article Influence Score (AIS) in the top 10% of
three research fields, grouped into the Web of Sci-
ence categories of: (1) business and management; (2)
economics; and (3) geography, planning & develop-
ment, public administration, and urban studies. The
AIS reflects both the number of citations that pa-
pers published in a journal received overa window of
5 years, as well as the prestige of these citations
(Westet al. 2006). Self-citations (within jour nals) are
not counted in this score. The AIS thus has marked
C2019 The Authors. International Journal of Management Reviews publishedby British Academy of Management and John
Wiley & Sons Ltd.

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