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Collaborative Regional Innovation Initiatives: A Booster for Local Company Innovation Processes?

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Abstract

It is widely acknowledged that the rate of innovations can be enhanced through interaction between new constellations of actors, crossing borderlines between different mindsets, knowledge and skill bases (e.g. Brown and Duguid, Org Sci 2(1):40–57, 1991; Cooke and Morgan, The associational economy: firms, regions, and innovation, 1998; Leonard-Barton, Wellsprings of knowledge: building and sustaining the sources of innovation, 1995, p. 64; Stamm, Managing innovation, design and creativity, 2008, p. 335). Studies of economic prosperity have also pointed to cooperation and competition between neighboring actors as a driver for competitiveness and innovativeness, be it for a company, a business area or a region (e.g. Piore and Sabel, The second industrial divide: possibilities for prosperity, 1984; Porter, The competitive advantage of nations, 1990). The hypothesis behind the geographical focus is that geographical proximity between actors promotes interaction and hence innovation. In EU, and also in Norway, this has been used actively as guidance in national and regional policy, where construction of innovation systems such as clusters and interorganizational networks are promoted and funded. To get organizations and institutions in a region to collaborate more is seen as the panacea for innovation, transformation and prosperity. However, companies often treat such constructed initiatives as an add-on to their ordinary, often long-lasting, business relationships between customers and suppliers (Håkansson et al., Business in networks, 2009, p. 13). This could imply that the necessary anchoring of such new innovation system initiatives with the companies’ own innovation processes is weak or missing. The terminology system points to the importance of the different elements (actors) in the system, their interrelatedness and their impact on each other (Meadows, Thinking in systems. A primer, 2009). An innovation system, like a network, cannot deliver innovation if the elements (i.e. the companies) of the systems don’t respond with related actions to the common endeavor. However, the different actors’ intraorganizational innovation processes are hardly mentioned in the innovation systems theories, thus lacking the important system feedback link between the intraorganizational innovation processes within the single company and the interorganizational innovation processes which are taking place in the collaborative initiative. In this article it is argued, supported by a case story, that attention to both of these processes and the nexus between them is needed in order to construct sustainable interorganizational innovation system initiatives. A model for this is proposed, based on a dual organization development process, encouraging system feedback loops and thereby bridging the single participating organization and the interorganizational collaborative initiative.

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Notes

  1. Innovation can be defined to encompass a wide range of topics, such as new products or process technologies, new markets, and new organizational arrangements or administrative systems (Fagerberg 2005, p. 6). A more simple division is between “product innovation” and “process innovation” (Lam 2005, p. 116). However, technological innovations can lead to organizational innovation (and vice versa), and thus organizational and technological innovations are intertwined (Brown and Duguid 1991, p. 51; Lam 2005, p. 115). The main concern in this article is however organizational/process innovation.

  2. For products: production and use (Håkansson et al. 2009, p. 256).

  3. The interplay between development–production–use (Håkansson et al. 2009, p. 254).

  4. More extensive documentation can to be found in Rubach (2011).

  5. See for instance http://ec.europa.eu/regional_policy/cooperate/regions_for_economic_change/doc/proj_samples.pdf.

  6. On request, the author is happy to provide further information on the data generation and the data analysis.

  7. Coghlan and Brannick (2005, p. 99) argue that it is more appropriate to speak of data generation than data gathering or collection. This is because in action research data comes through engagement with others in the action research cycles. Actions including data collections are themselves interventions. Data collection is also generating learning data, both for the researcher and the individual concerned. In short, in AR, data generation comes from active involvement.

  8. This is a fictitious name of the town where the companies are situated.

  9. Lean can be thought of as a methodological effort to improve the quality in production based on removing waste (in a broad understanding) and optimizing flow of goods and information (Andersson 2011, p. 1).

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Rubach, S. Collaborative Regional Innovation Initiatives: A Booster for Local Company Innovation Processes?. Syst Pract Action Res 26, 3–21 (2013). https://doi.org/10.1007/s11213-012-9270-8

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