Using action research and action learning for entrepreneurial network capability development

Helen McGrath and Thomas O’Toole

Action Learning: Research and Practice, 2016, vol. 13, issue 2, 118-138

Abstract: This paper applies an action research (AR) design and action learning (AL) approach to network capability development in an entrepreneurial context. Recent research suggests that networks are a viable strategy for the entrepreneurial firm to overcome the liabilities associated with newness and smallness. However, a gap emerges as few, if any, studies have examined the process and challenges in developing and using network capability to generate advantage through collaboration with network actors. In recognising that capabilities are developed rather than acquired, this paper address this theoretical gap and contributes to literature by tracing the development of network capability in an entrepreneurial context. A further contribution of the paper is in applying an AR design and AL sets as a method for capability development for the entrepreneurial firm. Findings suggest that, although network capability is of use, to develop the ability to use it requires a change in the market making perceptions of the entrepreneur from an independence mind-set to a more collaborative, interdependent one. Our research also supports the applicability of AL as an intervention strategy to promote action and learning among entrepreneurs for capability development, fitting the learning preferences of the nascent venture. For practitioners, evolving towards an interdependent mind-set facilitates network capability use and has the potential to relieve some of the resource pressure on entrepreneurs by providing them with strategic routes through their existing and potential network ties. For the entrepreneurship literature, a benefit stemming from this study is in introducing AR in its design and AL sets as an invention strategy in addition to developing theory in relation to network capability development.

Date: 2016
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DOI: 10.1080/14767333.2016.1162136

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