Clusters as Innovation Engines: The Accelerating Strengths of Proximity

• DOI: http://doi.org/10.1111/emre.12330
• Date: 01 March 2019
• Published date: 01 March 2019

Clusters as Innovation Engines: The

Accelerating Strengths of Proximity

XAVIER FERRAS-HERNANDEZ

1

and PETRA A. NYLUND

2

1

Department of Operations, Innovation and Data Sciences, ESADE, Sant Cugat, Spain

2

Faculty of Business and Communication Studies, University of Vic, Vic, Spain

As economic competition is becoming global,innovation clusters emergeas a salient level of competitive analysis.

Wehence study when and how innovationclusters strengthen innovation at firm level.We review insightsin this topic

from different theoretical perspectives, for example, neoclassical economics, evolutionary economics, behavioral

economics, strategic management and open innovation, in search of a comprehensive theoretical framework that

explains the relationship between firm innovation and the concentration of innovative activities in the proximity.

We then deduce five strengths which drive technological change in innovation clusters, namely attraction,

information, interaction, anticipation, and rivalry. The model has implications for researchers, managers, and

policymakers and contributes to our understanding of the acceleration of innovation within clusters.

Keywords: innovation clusters; innovation ecosystems; proximity; attraction; interaction; anticipation

Introduction

Globalization is bringing a flat world in whichgeography

is of little importance (Freidman, 2005). Yet parado-

xically, local concentrations of firms are gaining

importance in the global context. Innovation clusters, that

is, spatial concentrations of innovative activity, emerge

everywhere,and modern nations compete to develop such

innovative concentrations of firmsat national, regional, or

even urban scale (Tracey and Clar k, 2003; Tan, 2006;

Cooke, 2007). Major corporations, SMEs, entrepreneurs,

leading research centers, universities, venture capitalists,

and government institutions thrive and interact within

these clusters, which collectively design, produce, and

export successful products and services with a global

scope. The phenomenon of innovation clusters has been

approached from different theoretical perspectives. We

find their antecedents in neoclassical industrial districts

(Marshall, 1920), or in cluster theory (Porter, 1990,

1998). Similar phenomena have been studied from an

evolutionary point of view under the labels innovation

ecosystems (Edquist, 2005; Adner and Kapoor, 2010;

Mercan and Göktaş, 2011), sectoral innovation systems

(Malerba, 2002), local innovation systems (Breschi and

Lissoni, 2001; De la Mothe and Paquet, 2012) and

innovation districts (Clark et al., 2010; Katz and Wagner,

2014). These concepts constitute some of the building

blocks of global competitiveness. It is not Apple, Google,

or Hewlett Packard, but Silicon Valley as a whole that

competes with other innovation ecosystems in the global

arena. It is not Baidu or Xiaomi who invade the global

market, but the Chinese system of innovation, with its

epicenter in Beijingor Shenzhen. It is not BMW, Daimler,

Mercedes,or Robert Bosch who try to lead theautomotive

sector, but the innovative clusters of Bavaria and Baden-

Württemberg in South Germany. As globalization

standardize the international trade rules, extends the

symmetric provision of information, and forces the

economic barriers to dissolve, nations and regions are

under more pressure to differentiateand specialize to gain

comparative advantage (Hunt and Morgan, 1995; Cooke

and Leydesdorff, 2006). Creating technology hot spots,

and understanding the positive dynamics of innovation

inside them, is a key success factor for national

competitiveness. Furthermore, the dynamics of creation

and growth of innovation clusters appear to be

accelerating.According to the World IntellectualProperty

Organization some of the most powerful innovation

clusters in the world, in terms of technological inventive

activity, such as Shenzhen-Hong Kong (2ndin the world,

behind Tokyo-Yokohama), Seoul (4th), Beijing (7th),

Shanghai (19th), Tel-Aviv (22nd), Helsinki-Espoo

Correspondence: Petra A. Nylund, Faculty of Business and

Communication Studies, University of Vic, Sagrada Família 7, 08500

Vic, Spain. E-mail petra.nylund@uvic.cat

European Management Review, Vol. 16, 37–53, (2019)

DOI: 10.1111/emre.12330

©2018 European Academy of Management

(34th), and Singapore (35th), are relatively young

(Bergquist et al., 2017), and their originscannot be traced

to historical reasons, as implied by neoclassical economy

or cluster theory. Today, nations are involved in a fierce

race to develop their national or regional innovation

systems as a base of their economic competitiveness and

sustainedwelfare (Cooke, 2001; Lundvall,2010; McCann

and Ortega-Argi lés, 2013).

Beyond classic economic or cluster theory, there is

evidence of the rapid emergence of innovation clusters in

specific locations. We propose that innovation itself is

strengthened within an innovation cluster, which may be

the origin of a further positive feedback effect: more

innovative firms increase the innovativeness of the cluster,

which in turn enhances the innovativeness of the

individual firm. This effect may, at least partially, explain

the fast growth of innovation clusters. Boschma (2005)

performed a comprehensive assessment about the critical

role of proximity in innovation across five dimensions,

namely, cognitive, organizational, social, institutional and

geographical proximity. We build on this approach to

formulate a comprehensive theoretical framework that

explains under which circumstances the spatial concen-

tration of innovative activities enhances innovation. We

ground our study in five different theories, thus reviewing

the insights regarding innovation and proximity found in

neoclassical economics, strategic management, evolutio-

nary economics, behavioral economics, and open

innovation in search of this integrative framework.

The paper is structured as follows: First, the methodology

of the review is outlined. Second, a review of the positive

effects of clustering will be presented, divided in economic,

evolutionary, strategic, social and technological perspec-

tives with respective roots in neoclassical economics,

evolutionary economics, strategic management, behavioral

economics and open innovation in order to determine the

mechanisms that lay behind the emergence of innovation

clusters. Third, a new theoretical framework is proposed

in order to describe the very strengths of innovation in

innovation clusters. The objective is to understand when

and why innovation clusters strengthen firm innovation.

Five strengths are detected and described: attraction,

information,interaction,anticipation and rivalry.These

strengths are characterized as capacity-building,

knowledge-creating,opportunity-generating,market-

developing and strategy-enhancing respectively. Fourth,

conclusions and implications for research, management,

andpolicymakingarediscussed.

Methodology: Design-oriented research

synthesis

The purpose of this paper is to build theory around the

emergent concept of innovation clusters and design a

grounded theoretical framework that is use to researchers,

managers and policy makers. Our study is thus a design-

oriented research synthesis with focus on mechanisms

and their outcomes (Denyer et al., 2008). The design

mode of research complement positivist and narrative

modes (Burg and Romme, 2014). We intend not to

average and merge thematically similar studies, as do

systematic reviewsor meta analyses, but to link dissimilar

strands into one framework (Sandelowski et al., 2012).

We thus interpret the literature in order understand and

link different theories (Noblit and Hare, 1988). Whereas

integrative reviews aggregate and summarize data,

interpretive syntheses aggregate theory, and are thus

conceptual in both the process and output of the review

(Dixon-Woods et al., 2005). Hence, we define a number

of theories that may contribute to understanding our

research question and review representative publications

of each strand. Our main selection criteria for included

work are first, the extent to which each publication

contribute to our understanding of each mechanism and

secondly, the impact of the publication on subsequent

research. The second selection criterion requires a

demonstrated impact and therefore causes a selection bias

towards older work. To mitigate this bias, we have

complementedthe design-orientedresearch synthesis with

a systematicreview (Tranfield et al., 2003) with the search

term ‘innovationcluster’for articles in theWeb of Science

Core Collection. The search yielded 46 articles, of which

seven were exclude d since the clusters s tudied are not

location dependen t, and two were excluded for discussing

an innovation in a cluster with focus on that single

innovation and noton the cluster itself. Whereas the roots

of innovation clusters can be traced to the 1920s as, the

precise concept is recent. Hence, out of the resulting 37

articles, 31 were published from 2011 onwards, and 17

from 2015 on. Out of the 169 contributions referenced in

this review, 29 were published during or after 2015. A

wider search for ‘innovation’AND ‘cluster’yields over

4000 articles, many of which ar e unrelated to our topic

as they do not treat innovation clusters, but use cluster

analysis of data. This disparity further supports the need

for a design-oriented research synthesis.

Beyond cluster theory: The rapid

emergence of clusters

Innovation is the key driver of economic performance

(Schumpeter, 1942; Porter, 1998). For firms, innovation

is a strategic choice. However, the geographical location

of innovation appears to be of crucial importance for

innovative performance. Specific clusters of innovation,

global economic hot spots with outstanding innovation

dynamics, have recently, and sometimes suddenly,

appeared in several places in the world (Engel, 2015).

38 X. Ferras-Hernandez and P.A. Nylund

©2018 European Academy of Management