Rethinking Clusters

Towards a New Research Agenda for Cluster Research

Luciana Lazzeretti, Francesco Capone, Annalisa Caloffi, Silvia Rita Sedita, Luciana Lazzeretti, Francesco Capone, Annalisa Caloffi, Silvia Rita Sedita

• Editorial: Routledge
• Año: 2021
• ISBN:
  9781000351408
• Edición: 1
• Categoría: Économie
• Categoría: Économie du développement

Research on the topic of clusters and industrial districts is very extensive. However, most of it has focused more on understanding the past than on trying to map out the future. The aim of this book is to fill this gap by identifying and discussing the main research topics that populate the current scientific debate and highlight the emergent lines of research that will constitute the future research agenda. It does so by drawing on the debate started with the "rethinking clusters" workshops, which in a short time have become a rich place for discussion among cluster scholars around the world.

Rethinking Clusters: Towards a New Research Agenda for Cluster Research collects contributions from authoritative colleagues, who cover a number of relevant and timely issues, such as the territorial roots of radical innovation processes, new ways of understanding and measuring the role of place in economic development, path renewal, internationalization and entrepreneurship. The final section is devoted to the critical analysis of policies that support smart specialization.

The chapters in this book were originally published as a special issue of the journal European Planning Studies.

Radical or not? The role of clusters in the emergence of radical innovations

Nils Grashof, Kolja Hesse and Dirk Fornahl

ABSTRACT

Recently, radical innovations have received increasing attention in order to achieve long-term economic success. Regional clusters, being frequently used as an innovation policy instrument, have been shown to have the potential to support innovations in general. However, it remains unclear whether clusters are really a beneficial environment for the generation of radical innovations. This study aims to shed light on the specific role clusters can play in radical innovation processes. In order to do this, we apply a quantitative approach on the firm-level and combine several data sources (e.g. AMADEUS, PATSTAT, German subsidy catalogue). Our results show that clusters indeed provide a suitable environment for radical innovations. Furthermore, we find that radical innovations rather occur in the periphery of the cluster, where actors tend to be more open to the exchange of external knowledge. This happens in general through linkages with other actors, which we also find to be beneficial for the emergence of radical innovations up to a certain degree. Our findings implicate that policy makers should continue to support clusters and further develop funding schemes. Moreover, managers should be open to collaborations with other actors for the cross-fertilization of knowledge to promote radical innovations.

1. Introduction

Innovations are commonly accepted to be a key factor for economic growth (e.g. Rosenberg, 2004; Verspagen, 2006). Recently, especially the outstanding opportunities arising from rather radical innovations have been highlighted (Castaldi, Frenken, & Los, 2015). These kinds of innovations combine knowledge pieces that have not been combined before and consequently create something radically new (Fleming, 2001; Nerkar, 2003; Weitzman, 1998). If successful, they can open up completely new markets and industries as well as provide the basis for a long-lasting competitive advantage (Castaldi et al., 2015; Henderson & Clark, 1990; Verhoeven, Bakker, & Veugelers, 2016). From a firm’s perspective, they are desirable to enhance their competitiveness (Zhang, Wei, Yang, & Zhu, 2018). Policy makers have also recognized this great economic potential of radical innovations. For instance, in 2019 the German government will establish a public agency for the promotion of radical innovations in Germany (BMBF, 2018).

An already prevalent instrument of innovation policy are regional clusters (Brown, Burgees, Festing, Royer, & Steffen, 2007; Cantner, Graf, & Rothgang, 2018; EFI, 2015; Festing, Royer, & Steffen, 2012), which have been shown to foster the innovativeness of firms (Baptista & Swann, 1998; Bell, 2005). Nevertheless, there also exist contradictory evidence about the effect of clusters on firm’s innovativeness (e.g. Pouder & St. John, 1996). It therefore still remains unclear whether clusters are a beneficial environment for innovations in general (Martin & Sunley, 2003) and the generation of radical innovations in particular (Hervás-Oliver, Albors-Garrigos, Estelles-Miguel, & Boronat-Moll, 2018a). In theory, there exist two opposing streams of reasoning in this context. On the one hand, the relatively fast and eased diffusion of knowledge (e.g. via labour mobility), particularly of tacit knowledge, can challenge current thinking, which may result in radical new ideas (Braunerhjelm, Ding, & Thulin, 2017; Mascitelli, 2000; Otto & Fornahl, 2010). On the other hand, firms located within clusters may also be confronted with an inertia regarding potential changes due to uniform thinking and a lack of new challenging external ideas (Boschma, 2005; Martin & Sunley, 2003; Pouder & St. John, 1996). In order to contribute to a clarification, the following research question shall be answered: Does being located in a cluster increase the likelihood to create radical innovations?

By answering this research question in a quantitative way, our study makes a so far pioneering step towards explaining empirically the relationship between clusters and radical innovations. Besides contributing to close a research gap, this paper also has a rather practical meaning for companies as well as policy makers. It does not only show evidence that being located in a cluster can contribute to the emergence of radical innovations, but also deals with the corresponding conditions necessary to generate radical innovations in clusters.

The remainder of this paper is structured in the following way: The subsequent chapter deals with the theoretical background on radical innovations and clusters and combines both strands of literature. Moreover, we embed our hypothesis based on an extensive literature review. In the third section, we describe our data and methodology. After that, the paper turns to the empirical analysis. First, we present some descriptive statistics on our sample and then, we discuss our econometrical results. Finally, the study draws conclusions from our results and points out possible future research endeavours.

2. Theory and hypotheses

During the last decades, it has become common sense that innovations are a core factor for economic growth (Cortright, 2001; Rosenberg, 2004; Verspagen, 2006). In addition, scholars have found evidence that new knowledge, which is transformed into innovations, builds on already existing knowledge pieces. For instance, Weitzman (1998) stated that existing knowledge is recombined in a new way to form new artefacts. Hence, innovative search processes have a cumulative nature (Arthur, 2007; Basalla, 1988).

We can distinguish between two types of new knowledge creation, namely incremental and radical innovations. Most innovations rely on well-defined knowledge pieces, which are recombined repeatedly and hence represent small improvements. These incremental innovations develop mostly alongside well-known knowledge trajectories (Dosi, 1982). On the other hand, search processes that are radical in nature combine knowledge pieces that have not been combined before (Fleming, 2001; Nerkar, 2003; Weitzman, 1998).New combinations then emerge when inventors discover a new purpose for their existing knowledge or they fuse together some external expertise with their own mind-set (Desrochers, 2001). A good example is, for instance, the new combination of the technological fields automotive, sensor-based safety systems, communication and high-resolution mapping which are combined for the first time in the self-driving car (Boschma, 2017). Radical innovations are more likely to fail and are accompanied with higher uncertainty in terms of their economic impact in the future (Strumsky & Lobo, 2015). However, if successful, these innovations can bring about a paradigm shift and thus radical change (Dosi, 1982; Verhoeven et al., 2016). This radical change can lead to the formation of new markets and entire industries thereby disrupting old ones (e.g. Henderson & Clark, 1990; Tushman & Anderson, 1986). Radical innovations can introduce a new set of performance features or have a higher functional quality and improve performance significantly (Bers, Dismukes, Miller, & Dubrovensky, 2009). Also, they may reduce cost compared to existing products and may alter the characteristics of the market, such as consumer expectations (Nagy, Schuessler, & Dubinsky, 2016). Hence, radical innovations can help to build a strong competitive advantage (Castaldi et al., 2015) and serve as the basis for future sustainable economic growth (Ahuja & Morris Lampert, 2001; Arthur, 2007).

Scientific literature has used several methodologies to analyse radical innovations empirically mainly based on indicators using forward (e.g. Albert, Avery, Narin, & McAllister, 1991 Trajtenberg, 1990;) and backward (e.g. Rosenkopf & Nerkar, 2001) citations on patents. Recently, approaches following the theoretical concept of recombinant innovation particularly focus on technology classes provided in patent documents to study the nature of radical innovations (e.g. Fleming, 2007; Strumsky & Lobo, 2015; Verhoeven et al., 2016). Our study follows this notion and defines radical innovations as the result of search processes that combine unconnected knowledge domains for the first time (Fleming, 2001, 2007; Rizzo, Barbieri, Ramaciotti, & Iannantuono, 2018). Thus, we focus especially on the emergence of radical innovations, instead of its diffusion. The high degree of radicalness is indicated by the new combination of knowledge. Despite the fact that we cannot predict if these new combinations will have a major impact in the future, we term them ‘radical’ since they introduce totally novel knowledge combinations (Rizzo et al., 2018; Verhoeven et al., 2016). In line with, e.g. Dahlin and Behrens (2005), we argue that radical innovations have two dimensions (emergence and impact) which are worth inspecting.¹

In the context of regional clusters, however, the concept of radical innovations has been under-researched (Hervás-Oliver et al., 2018a). This holds especially true for quantitative empirical studies. In light of the popularity and widespread application of the cluster concept, also in terms of policy funding measures, this research gap is particularly astonishing (Brown et al., 2007; EFI, 2015; Martin & Sunley, 2003). In line with Grashof and Fornahl (2017), clusters are here defined as: ‘[ … ] a geographical concentration of closely interconnected horizontal, vertical and lateral actors, such as universities, from the same industry that are related to each other in terms of a common resource and knowledge base, technologies and/or product-market’ (Grashof & Fornahl, 2017, p. 4).² It has been emphasized that clusters can be a preferable environment for fostering firm’s innovativeness (Baptista & Swann, 1998; Bell, 2005; Porter, 1998). Although, recently it has been argued that this rather positive relationship between clusters and firm performance also depends on the specific context (e.g. firm and cluster characteristics). Thus, contextual variables, such as cluster size and the industry characteristics, should additionally be considered when investigating firm-specific cluster effects (Frenken, Cefis, & Stam, 2013; Knoben, Arik...