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Der Open-Access-Publikationsserver der ZBW – Leibniz-Informationszentrum Wirtschaft

The Open Access Publication Server of the ZBW – Leibniz Information Centre for Economics

Stoetzer, Matthias-Wolfgang; Pfeil, Silko; Kaps, Katharina; Sauer, Thomas

Working Paper

Regional dispersion of cooperation activities as

success factor of innovation oriented SME

Jenaer Beiträge zur Wirtschaftsforschung, No. 2011,4

Provided in Cooperation with:

University of Applied Sciences Jena, Department of Business Administration Suggested Citation: Stoetzer, Matthias-Wolfgang; Pfeil, Silko; Kaps, Katharina; Sauer, Thomas (2011) : Regional dispersion of cooperation activities as success factor of innovation oriented SME, Jenaer Beiträge zur Wirtschaftsforschung, No. 2011,4, ISBN 393904623X, http://nbnresolving.de/urn:nbn:de:gbv:27-20111020-094416-3

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zbw Leibniz-Informationszentrum Wirtschaft Leibniz Information Centre for Economics


Fachbereich Betriebswirtschaft Departement of Business Administration

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KompNet2011 - Erfolgsfaktoren regionaler Innovationsnetze Herausgeber: Thomas Sauer, Matthias-Wolfgang Stoetzer


Katharina Kaps Fachhochschule Jena, Fachbereich Betriebswirtschaft Carl-Zeiss-Promenade 2, 07745 Jena Tel.: 03641.205 941, Fax: 03641.205 942


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Abstract In this paper, we analyze the relationships between different types of innovation and collaboration, given the varying geographical distance of the latter. The study is based on the data of the research project “KompNet 2011 – Factors determining the success of regional innovation networks”, which examines the innovation activities of small and medium-sized enterprises (SME) in and closely around Jena (Thuringia).

The aim of this paper is to explore to what extent spatial reach of collaboration linkages determines innovation orientation and innovative behavior. That means: Innovation performance could be positively related to (a) to a high intensity of local collaboration, (b) the intensity of international collaboration or (c) neither regional nor (inter)national collaborations.

In a first step we summarize the relevant literature which comprises aspects of our central subject under investigation. We additionally discuss the necessity of keeping in mind several control variables for theoretical and empirical reasons. In the following we present descriptive analyses relating to the regional reach of collaboration in general, the impact of collaboration on innovation and the links between the regional reach of cooperation and different forms of innovation, i.e. product, process, marketing and organizational innovation. In a final step we discuss the results of several regression models.

We observe that there is no significant influence of the geographical variables on the innovative performance of SME. Therefore our findings suggest that innovative firms rely on collaboration partners at a variety of spatial distances. The results also show a significant and positive influence of the intensity of competition on the innovativeness of firms in all models. Furthermore product- and process innovations are created by firms with intensive cooperative activities to scientific institutions, while a wide variety of cooperation partners and a strong focus on quality leadership turns out to be important for the development of marketing- and organizational innovations.

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Index of contents 1 Introduction

2 The spatial dimension of innovation collaboration

3 Control variables

4 Hypotheses and data set

5 Descriptive findings and econometric results

6 Conclusions


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Table of figures Chart 1 The holy trinity of regional innovation

Chart 2 Research model of control variables

Chart 3 Spatial patterns of collaboration

Table 1 Industry dummies and classification

Table 2 Descriptive statistics of dependent and independent variables................. 27 Table 3 Geographical reach of transfer channels (by transfer channel)................. 29 Table 4 Geographical reach of transfer activities (by industry sector)

Table 5 Innovation and the reach of collaboration

Table 6 Determinants of different innovation types

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The paper deals with the question how the innovation performance of small and medium enterprises (SME) is influenced by the regional localization of their cooperative activities. So far it is concerned with the interdependencies of firm organization and market structure as well as of size and spatial distributions of cooperation activity with the processes governing innovation behavior of SME.

The uneven spatial distribution of innovative behavior is a widely observed phenomenon. According to Gordon and McCann (2005a, 2005b) and Iammarino and McCann (2006) it is possible to distinguish between four alternative hypotheses explaining this finding.

1. The first one is the well known cluster approach of Michael Porter (2003). According to it the uneven spatial distribution of innovative behavior is the result of clusters of the currently more innovative sectors of the economy.

2. The second one is more concerned with the dynamics of industrial clusters in comparison to Porter‟s approach, such that the different phases of the product and profit cycles are reflected in terms of emergence, evolution and decline of innovative clusters (Vernon 1966; Markusen 1985). The focus here is on the relationship between space, value added, and production cost conditions at different stages in the product cycle (Gordon & McCann 2005a, 2005b; Iammarino & McCann 2006).

3. The third approach is concerned with the characteristics of different places. These could be the so called soft factors of regional economic performance (Kitson et al.

2004), as well as the regional university-industry linkages as the very core of regional innovation systems (Audretsch et al. 2003; Arvanitis et al. 2005; D'Este et al. 2005;

Florax & Folmer 1992; Fritsch & Schwirten 1999; Frye 1993; Goldstein et al. 1995;

Goldstein & Renault 2004; Lüder 1988; Peters & Becker 1999; Schamp & Spengler 1985; Smith 2003; Thanki 1999; Zucker et al. 1998).

4. The fourth hypothesis assumes that innovation is most likely to occur in clusters of small and medium-sized enterprises, whose spatial patterns happen to be uneven.

From this point of view geographical proximity of SME is the key for the development of

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mutual trust relations (Granovetter 1973) between them. These trust relations could be the result of shared experience of interaction with decision-making agents in different firms as well as of joint development of tacit knowledge in the course of cooperative innovation processes. The so-called „new industrial districts‟ such as Silicon Valley (Saxenian 1996), and traditional industrial districts such as the Emilia-Romagna region in Italy (among others Brusco 1982; Castells & Hall 1994) have highlighted the role which social as well as purely instrumental business links may play in fostering localized growth.

Our own research combines elements of these hypotheses, starting with the observation that only little is known about how knowledge is actually transmitted, at what distance, and how this relates to the innovation outcome (Breschi & Lissoni 2001;

Fritsch 2005; Döring & Schnellenbach 2006).

The remainder of the paper is organized as follows. Section 2 discusses the spatial dimension of innovation collaboration of SME. Section 3 presents the existing empirical literature on the influence of other control variables in the collaboration context. Section 4 summarizes the hypotheses and describes the data set. The descriptive and econometric results are presented in section 5 and section 6 concludes.

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2 The spatial dimension of innovation collaboration The analysis tries to shed light on the relationships between innovation and collaboration, given the varying geographical distance of the latter.

The relationship between innovation and location is one of the most influential ideas of the last twenty years. The inherent local concentration of innovation and thus a flourishing regional development is at the heart of a broad range of theoretical concepts from Porters´ famous clusters, the new industrial districts and the “innovative milieu” to the idea of regional learning or regional innovation systems (Moulaert & Sekia 2003).

The relationship is often expressed as a paradox: Globalization and the accompanying strengthening of competitive pressures leads to innovation as the basis of economic success at all levels (from supra-national and regional to firm levels). But at the same time innovation processes tend to be locally concentrated and even to root in local innovation systems. This is illustrated by a lot of case studies and examples. The most prominent are Saxenians´ Silicon valley (Saxenian 1996) and the chapter 4 of Porters´ Competitive Advantage of Nations (1990, see also Porter 2003). In this vein geographical proximity is a necessary condition for innovation. Therefore, the spatial distribution of innovation and collaboration is an important part of empirical research and public regional development policy.

Two levels of innovation analyses are prevailing in the literature: First the macro-level, that is the regional level and second, the micro-level that is the firm level.

At the regional level many empirical studies estimate knowledge production functions (i.e. innovation production functions) using a diversity of inputs and outputs (Jaffe 1989, Audretsch & Feldman 2004; Lee et al. 2010). Here, the generation of innovation is seen as a black box because the process by which new knowledge is created at the local or regional level is left out of consideration. The interpretation of the findings grounds on “knowledge spillovers”, “creative atmosphere” and “local buzz”. These ideas tend to be vague or difficult to measure. In order to put these ideas into concrete terms the identification and separation of different forms of collaboration of firms (and public research institutions) at the regional level are necessary.

Projekt KompNet2011 Erfolgsfaktoren regionaler Innovationsnetze This leads to the idea that the key to understand local innovation systems has to found on a microeconomic approach. Innovation is not emerging out of an opaque regional bubble. Instead, firms innovate (not a region) and therefore the behavior of firms provides the explanation of the spatial concentration of innovation. Notwithstanding that the firms´ decisions depend on internal and external factors.

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