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Network Positioning, Co-Location or Both?

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Innovation Networks in the German Laser Industry

Part of the book series: Economic Complexity and Evolution ((ECAE))

Abstract

Previous research indicates that firm innovativeness can either be determined by a firm’s position within the network dimension or by its position within the geographical dimension. Integrative studies addressing both distinct and combined proximity effects remains rare (cf. Whittington et al. 2009). Thus, we address in this Chapter the following research question: Are firm-level innovation outcomes positively or negatively related to network positioning effects, geographical co-location effects or combined proximity effects; and if the latter case is true, are the combined effects substitutional or complementary in nature? Panel data count models with fixed and random effects were used to analyze a firm’s innovative performance as measured by patent application counts. This last empirical analysis is organized as follows: We start with a short introduction in Sect. 12.1. Next, we provide a brief discussion of theoretical background in Sect. 12.2. In Sect. 12.3 we introduce our conceptual framework and derive our hypotheses. In Sect. 12.4 we introduce the data and methods used. Next, we outline the estimation strategy and report our empirical results in Sect. 12.5. Finally, we discuss our findings and conclude with a number of critical remarks in Sect. 12.6.

An invention is a major one if it provides the basis for extensive applications and improvements […]

(Simon Kuznetz 1971)

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Notes

  1. 1.

    This section is based on a joint research project conducted together with Dr. Peter Boenisch, chair for Statistics and Econometrics at Martin Luther University in Halle and Dr. Iciar Dominguez Lacasa, Department of Structural Economics at the Halle Institute for Economics (Kudic et al. 2010). Moreover we thank Dr. Michael Schwartz and Dr. Marco Sunder for reviewing the paper and providing critical comments and helpful suggestions. We have benefited from comments from the audience at the 13th International Schumpeter Society Conference in 2010 in Aalborg, Denmark and the 36th EIBA Annual Conference in 2010 in Porto, Portugal. I take full responsibility for the content or any errors in this completely revised version of the initial paper.

  2. 2.

    We are not the first to use data on nationally or supra-nationally R&D cooperation projects to construct knowledge-related innovation networks (cf. Broekel and Graf 2011; Fornahl et al. 2011; Scherngell and Barber 2009, 2011; Cassi et al. 2008).

  3. 3.

    By now, both theoretical (Burt 2000, 2005) and empirical studies (Rowley et al. 2000) accept the partial compatibility of both theories (cf. Sect. 2.5.4).

  4. 4.

    For a description of patent data sources and data gathering procedures, see Sect. 4.2.

  5. 5.

    For a detailed description of industry data, see Sect. 4.2.1.

  6. 6.

    This measure was originally proposed by Sorenson and Audia (2000) and applied by Whittington et al. (2009) in order to quantify distinct and combined geographical proximity measures.

  7. 7.

    For a detailed description of cooperation and network data see Sect. 4.2.3.

  8. 8.

    We used STATA 10.1 (Stata 2007), a standard software package for statistical data analysis.

  9. 9.

    To substantiate this finding we repeated the estimations with a 1-year time lag. It turned out that coefficient estimates for PRO clustering were highly significant; all other coefficient estimates, including LSM clustering, showed no significant effects. Additional results are available upon request.

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  1. Stifterverband, Essen, Germany

    Muhamed Kudic

  2. Halle Institute for Economic Research, Halle (Saale), Germany

    Muhamed Kudic

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Kudic, M. (2015). Network Positioning, Co-Location or Both?. In: Innovation Networks in the German Laser Industry. Economic Complexity and Evolution. Springer, Cham. https://doi.org/10.1007/978-3-319-07935-6_12

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