Configurations of social media-enabled strategies for open innovation,firm performance,and their barriers to adoption

The use of social media offers tremendous innovation potential. Yet, while current research emphasizes success stories, little is known about how firms can leverage the full potential of their social media use for open innovation. In this paper, the authors address this gap by conducting a configurational analysis to develop an integrative taxonomy of social media-enabled strategies for open innovation. This analysis stems from the integration of internal and external variables such as social media communication activities, organizational innovation seekers, potential innovation providers, the stages of the open innovation process, and their relationship with different performance outcomes and barriers to social media adoption for open innovation. Through an empirical study of 337 firms based in eight countries, four clusters have been identified that are characterized as distinct strategies: “marketing semi-open innovators,” “cross-department semi-open innovators,” “cross-department full process semi-open innovators” and “broad adopters open innovators.” The findings reveal the trade-offs associated with different strategies for implementing social media for open innovation and provide insights of the use of these strategies. By doing so, they suggest a more nuanced approach that contrasts with the traditionally positive (or even rosy) depiction of the effects of social media on open innovation. Accordingly, managers are encouraged to contemplate their organizational competencies, capabilities, and their strategic intent when drafting social media strategies for open innovation. Selective approaches, along with greater adoption leading to greater benefits, are shown to be more rewarding than a middle way that spreads things too thin. Avenues for further research include qualitative explorations of the trajectories unfolding through implementing social media strategies for innovation activities and the use of objective performance measures rather than subjective perceptions from informants to understand the complex relationships between social media adoption and performance.