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Innovation and Employment Growth in Industrial Clusters: Evidence from Aeronautical Firms in Germany

  • Werner Bönte

    ()

In recent years we can observe a surge of interest among academics as well as regional policy makers in the phenomenon of geographical clustering of high-technology firms. In this study, we investigate whether agglomeration forces do have an impact on the innovative performance of a collection of spatially concentrated aeronautic firms in Northern Germany which is claimed to be the third largest aeronautic ?Standort?. This alleged cluster comprises a group of co-located aeronautic (supplying) firms. We analyze three forces, namely knowledge flows, demanding customers and rivalry that may have a direct impact on the innovative performance of firms. Specifically, this paper sets out to investigate three interrelated questions. 1) What agglomeration forces are relevant as measured by a significant impact on the innovative performance of firms? 2) Do firms in clusters benefit from spatially proximate inter-firm linkages, that may generate agglomerative advantages, more strongly than from distant linkages? 3) Are these forces operating exclusively in clusters, while such effects are not relevant for spatially dispersed firms? We make use of own survey data of 111 firms within and 68 outside the supposed cluster grouped around the cities of Hamburg and Bremen. A survey has been specifically designed to collect data on firms' innovation activities as well as a set of indicators for the agglomeration forces which may be operating in clusters. The latter consist of the perceived importance (6-point scale) of the various spatially inter-firm linkages that may generate agglomeration advantages. The questions are systematically asked for linkages in proximity as well as for linkages to distant firms and institutions. The basic idea underlying this concept is that it is the firms themselves that can best evaluate the relevance of such forces. The firms outside the cluster form a control group so that the effects of clustering can be identified by looking at the differences between the two groups. We have estimated a probit model of whether the firms have introduced product (process) innovations or not. The estimations provide the following results: First, for the group of cluster firms we have found that linkages to geographic proximate firms and institutions do have an impact on product innovations (process innovations are not affected). Firms that rate knowledge flows from proximate scientific institutions (e.g. universities) and proximate public information sources (e.g. trade shows) as more important are more likely to introduce product innovations. Moreover, motivational effects that stem from local rivalry have a negative effect whereas demanding customers have a positive impact on innovative performance. Second, geography seems to be relevant because only proximate firms and institutions do have a statistically significant impact. The estimated coefficients of the variables that reflect knowledge flows and motivational effects that stem from distant firms and institutions are statistically insignificant. Third, differences between the cluster and the control group exist. While demanding customers in geographical proximity do have a positive impact on innovative performance of cluster firms this effect is statistically insignificant for the firms of the control group.

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Paper provided by European Regional Science Association in its series ERSA conference papers with number ersa03p284.

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Date of creation: Aug 2003
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Handle: RePEc:wiw:wiwrsa:ersa03p284
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  1. Griliches, Zvi, 1990. "Patent Statistics as Economic Indicators: A Survey," Journal of Economic Literature, American Economic Association, vol. 28(4), pages 1661-1707, December.
  2. Baptista, Rui & Swann, Peter, 1998. "Do firms in clusters innovate more?," Research Policy, Elsevier, vol. 27(5), pages 525-540, September.
  3. repec:fth:harver:1473 is not listed on IDEAS
  4. Swann, Peter & Prevezer, Martha, 1996. "A comparison of the dynamics of industrial clustering in computing and biotechnology," Research Policy, Elsevier, vol. 25(7), pages 1139-1157, October.
  5. Catherine Beaudry, 2001. "Entry, Growth and Patenting in Industrial Clusters: A Study of the Aerospace Industry in the UK," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 8(3), pages 405-436.
  6. Fujita, Masahisa & Thisse, Jacques-François, 1996. "Economics of Agglomeration," CEPR Discussion Papers 1344, C.E.P.R. Discussion Papers.
  7. Jaffe, Adam B & Trajtenberg, Manuel & Henderson, Rebecca, 1993. "Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations," The Quarterly Journal of Economics, MIT Press, vol. 108(3), pages 577-98, August.
  8. Oerlemans, Leon A.G. & Meeus, Marius T.H., 2002. "Spatial embeddedness and firm performance: an empirical exploration of the effects of proximity on innovative and economic performance," ERSA conference papers ersa02p054, European Regional Science Association.
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