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

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  • Werner Bönte

Abstract

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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  • Werner Bönte, 2003. "Innovation and Employment Growth in Industrial Clusters: Evidence from Aeronautical Firms in Germany," ERSA conference papers ersa03p284, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa03p284
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    Cited by:

    1. Delgado, Mercedes & Porter, Michael E. & Stern, Scott, 2014. "Clusters, convergence, and economic performance," Research Policy, Elsevier, vol. 43(10), pages 1785-1799.
    2. Justin Doran & Declan Jordan, 2016. "Cross-sectoral differences in the drivers of innovation," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 43(5), pages 719-748, October.
    3. David Smith & Gamal Ibrahim, 2006. "Cluster Dynamics: Corporate Strategy, Industry Evolution and Technology Trajectories - A Case Study of the East Midlands Aerospace Cluster," Local Economy, London South Bank University, vol. 21(4), pages 362-377, November.
    4. Ali, Hoda Abd El Hamid, 2011. "Universities, Industrial Clusters, and Economic Development in Egypt," MPRA Paper 60111, University Library of Munich, Germany, revised 2012.
    5. Anke Kutschke & Alexandra Rese & Daniel Baier, 2016. "The Effects of Locational Factors on the Performance of Innovation Networks in the German Energy Sector," Sustainability, MDPI, vol. 8(12), pages 1-18, December.
    6. Thomas Brenner & Andreas Gildner, 2006. "The long-term Implications of Local Industrial Clusters," European Planning Studies, Taylor & Francis Journals, vol. 14(9), pages 1315-1328, June.
    7. Richard Harris, 2011. "Models Of Regional Growth: Past, Present And Future," Journal of Economic Surveys, Wiley Blackwell, vol. 25(5), pages 913-951, December.
    8. Abdurrahman Mete Yazan, 2013. "Do Social Factors Matter for Innovation, and Do They Influence Innovation in Aeronautics Industry?," IET Working Papers Series 05/2013, Universidade Nova de Lisboa, IET/CICS.NOVA-Interdisciplinary Centre on Social Sciences, Faculty of Science and Technology.
    9. Thomas Brenner & André Mühlig, 2007. "Factors and Mechanisms Causing the Emergence of Local Industrial Clusters - A Meta-Study of 159 Cases," Papers on Economics and Evolution 2007-23, Philipps University Marburg, Department of Geography.
    10. Silviya Draganinska & Rudiger Wink, 2006. "Formal Knowledge Examination Institutions: Chance Or Threat to European Medium Tech-Nology SMEs? A Cognitive and Institutional Perspective," ERSA conference papers ersa06p404, European Regional Science Association.
    11. Fu, Xiaolan & Pietrobelli, Carlo & Soete, Luc, 2011. "The Role of Foreign Technology and Indigenous Innovation in the Emerging Economies: Technological Change and Catching-up," World Development, Elsevier, vol. 39(7), pages 1204-1212, July.

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    JEL classification:

    • L62 - Industrial Organization - - Industry Studies: Manufacturing - - - Automobiles; Other Transportation Equipment; Related Parts and Equipment

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