Spatial cooperation patterns and their impact on innovation outcomes: lessons from firms in a low-technology region

ABSTRACT

This paper examines cooperation patterns of firms in the German low-technology region of Lower Bavaria. Particular emphasis is placed on the interplay among the spatial scale of cooperation, the form of cooperation and the type of innovation. Generic results show that overall, firms with a spatially more diverse set of cooperation linkages have a higher likelihood of innovating. However, the innovation outcomes differ depending on the spatial scale of cooperation. While cooperation with regional partners positively correlates with low-threshold innovations, cooperation with spatially distant partners positively correlates with product innovations. Surprisingly, it is application-oriented cooperation that channels the relation in both cases. The findings support the view that innovation of firms in low-technology regions is driven by ‘development’ rather than ‘research’. It also suggests that innovation-driven growth may even be possible in regions with limited values on the traditional innovation-supporting factors.

KEYWORDS:

• Innovation
• connectivity
• low-tech industries
• rural regions
• R&D
• Germany

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. This sector-based distinction is not indisputable (see, e.g. Kirner, Kinkel, and Jaeger, 2009).

2. As we do not have any information on the population of regional service firms and construction firms, we cannot test the representativeness of the firms in the final sample for firms in these sectors.

3. Admittedly, cooperation with competitors seems strange at first, but empirical evidence has shown that firms frequently cooperate with competitors to form strategic alliances and gain access to knowledge resources and capabilities (e.g. Haeussler, Patzelt, and Zahra, 2012). One of the reasons why firms may choose competitors as cooperation partners is that by cooperating with local or regional competitors, they can establish and exploit cluster effects, i.e. a combination of cooperation and competition (Porter, 2000).

4. The literature suggests that the size of a firm and firms' R&D expenditure both have a positive effect; regarding the sector, export-oriented industries and high-technology industries in particular positively affect firms' likelihood of innovating (Barge-gil, 2010). A further variable frequently mentioned is the presence of a distinct R&D department. However, as this variable highly correlates with R&D expenditure, it is not included in the analysis.

5. In our analysis, we apply the following thresholds: (0) 0 employees, (1) 1–9 employees, (2) 10–49 employees, (3) 50–99 employees, (4) 100–249 employees, (5) 250–999 employees, (6) more than 1000 employees.

6. Here, the sector is based on self-indication of firms and may deviate from the classification reported in the official statistics.

7. Marginal effects are calculated with the statistical software package Stata.