What's Next in Researching Cluster Policy: Place-Based Governance for Effective Cluster Policy

Abstract

Despite their immense popularity and rapid proliferation and development, local cluster policies have met mixed results, and often suffer from limited effectiveness. In this paper, we argue that an important reason for the limited success can be found in the way policies have been grafted onto a particular policy rationale, namely of “cluster building”. Responding to this critique, we propose an alternative rationale, that of “policy leverage”, and a governance model which, in the pursuit of “policy leverage”, presents a new approach to intelligence gathering and to collective strategy-making. The model assigns a key role to “civic entrepreneurs” who operate at the interfaces of public and private spheres, and, of endogenous and exogenous drives, in line with “place-based” approaches.

Acknowledgements

The authors are grateful for the generous substantive and financial support from the NICIS institute, The Hague, as well as from the municipalities of Leeuwarden, Nijmegen, Enschede and Hengelo and the University of Twente and the Radboud University Nijmegen. The authors are also very grateful for the helpful and insightful referee comments.

Notes

We deliberately refrain from providing a definition of a cluster. Following its introduction, many authors have published articles or have written books that try to provide a clear understanding of the (what, how and why of the) cluster and its advantages for firms (e.g. Benneworth et al., 2003). This lively debate has not come to a unanimous or crystal clear conclusion about the workings and raison d’être of the cluster. As these critics say: “But the mere popularity of a construct is by no means a guarantee of its profundity. Our argument here is that seductive though the concept is, there is much about it that is problematic, in that the rush to employ ‘cluster ideas’ has run ahead of many fundamental conceptual, theoretical and empirical questions” (Martin & Sunley, 2003, p. 7). What is certain is that analytical cloudiness remains as cluster proponents fail to distinct the concept from other territorialized innovation theories (e.g. the Marshallian district, Italian industrial district, new industrial space, innovative milieu, regional innovation system, learning region, growth pole and creative field concepts) and continue to adopt these in an interchangeable and eclectic manner (Gordon & McCann, 2000; Newlands, 2003; Taylor, 2010). The cluster concept's chaotic character (Burfitt & Macneill, 2008), its lacunae and its eclectic nature (Taylor, 2010), produce a framework fraught with definitional elasticity or incompleteness. Due to its fuzziness, a precise definition of the cluster concept, therefore, is left out.

The boundaries of cluster policy are quite hazy. There is extreme heterogeneity in usage: a puzzling variety of initiatives labelled as cluster policy and divergence in policy forms exist. To some, the diversity is so great as to render cluster policy no more than: “a fairly imprecise and flexible label for differing combinations of measures” (Martin & Sunley, 2003, p. 28). Raines (2002c) describes how some see the “cluster as a fad—the belief that the cluster approach adds little to the existing policy framework and can be discounted as a short-term bandwagon effect” (p. 3). They question: “the extent to which the cluster policy represents a radical and substantive contribution to regional economic policy” (Burfitt & Macneill, 2008, p. 493). Concerns over the protean and arbitrary nature of cluster policy are accompanied by more fundamental concerns that it ultimately will be unable to deliver on its promises (Martin & Sunley, 2003; Palazuelos, 2005). However, an increasingly sophisticated argument has been developed with respect to the contribution and value of the cluster policy: “whilst there is acceptance in the academic sphere that cluster policy is not the magic bullet it is sometimes taken for in the policy world, there remains a widespread conviction that is has much to offer policy-makers” (Burfitt & Macneill, 2008, pp. 495–496). Cluster policy possesses the potential to facilitate cluster reinforcement (e.g. Benneworth, 2002; Carlsson & Mudambi, 2003). This paper focuses on cluster policy aimed at cluster reinforcement (synonyms are cluster development and cluster promotion). Porter (2000, p. 26) voices its crystal clear precept: “The process of cluster [reinforcement] involves recognition that a cluster is present and then removing obstacles, relaxing constraints and eliminating inefficiencies that impede productivity and innovation in the cluster”. In other words, the focus is on improving the business environment in clusters (Porter, 2000). Cluster formation is disregarded as a research subject. We will focus on the stage afterwards—the way in which “arisen” clusters can be reinforced through the policy. This is because cluster formation is deemed insensible for various reasons, as pointed out by many authors (amongst others Barkley & Henry, 2002; Feldman & Francis, 2004; Hospers et al., 2009).

Activating an existing cluster base is included in the rubric of “cluster building”.

Intelligence refers to the act of understanding or comprehension.

This implies that clustering synergies are nurtured and exploited, regardless of whether a discrete spatial cluster emerges as a result—something that might very well occur “naturally” (Feser, 2008).

A demand-“led” cluster policy is not to be preferred; the local government needs to ensure that matters of public concern are not ignored. In other words, a local government should not act as the infamous Genie of the Lamp who grants all of the clusters' wishes.

“Strategic intelligence” thus fundamentally differs from knowledge-based club goods used to achieve product and (business) process innovations.

Learning processes in CoPs are often referred to as “situated” learning processes. It is important to note here that the term “situated” should not be reduced to geographical proximity (Wolfe & Gertler, 2004). Amin and Roberts (2008, p. 365) contend that the nature and dynamic of space in situated learning needs to be rethought due to the fact that: “Proximity … comes in many forms, enabling ‘being there’ to draw on institutional, cultural, social, technological, cognitive, organizational, and geographical proximity”. Relational proximity is therefore crucial: “A knowledge network should be conceptualized as a continuous but contoured space in which location, proximity, and distance are relationally, rather than geographically, determined” (Amin and Roberts, 2008, p. 365). Atherton's (2003, p. 24) suggestion is to “extend the notion of proximity to incorporate relational as well as locational [i.e. physical] intimacy, suggesting that, although physical proximity may enhance prospects for relational intimacy, there is no inevitable formation of relationships solely as a result of location near to other businesses”.

Examples are regional innovation policies (e.g. co-operation programmes between university and industry), science policies, technology policies, marketing policies, fiscal policies (e.g. setting up of specialized risk capital funds), industrial policies (e.g. encouraging entrepreneurship and networking), competition policies, trade policies (e.g. FDI attraction), labour market policies (e.g. attraction/retention of human capital), education policies (e.g. support to training facilities and programmes and technology development) and land-use and infrastructure (i.e. public works) policies (e.g. creation of business parks and building of infrastructure).

Governance, as a way of acting (that is not institutional renewal nor institutional engineering are sought after), implies a more flexible multilateral process of negotiated economic development involving many parties (Wolfe & Creutzberg, 2005). Also, to prevent misunderstandings: the framework proposed in this research, i.e. the governance structure, is not about learning together to trigger innovation, as is frequently advocated in the literature, but about listening to develop better cluster policy.

“Strategic intelligence” can be on subjects or matters that lie outside the sphere of influence or reach of the localities and their local cluster policy.