(2017) The open innovation research landscape: established perspectives and emerging themes across different levels of analysis, Industry and Innovation, 24:1, 8-40, DOI: 10.1080/13662716.2016.1240068 To link to this article: https://doi.org/10. 1080/13662716.2016.1240068 Published online: 07 Nov 2016.Submit your article to this journal This paper provides an overview of the main perspectives and themes emerging in research on open innovation (OI). The paper is the result of a collaborative process among several OI scholarshaving a common basis in the recurrent Professional Development Workshop on 'Researching Open Innovation' at the Annual Meeting of the Academy of Management. In this paper, we present opportunities for future research on OI, organised at different levels of analysis. We discuss some of the contingencies at these different levels, and argue that future research needs to study OI -originally an organisationallevel phenomenon -across multiple levels of analysis. integrative framework allows comparing, contrasting and integrating various perspectives at different levels of analysis, further theorising will be needed to advance OI research. On this basis, we propose some new research categories as well as questions for future research -particularly those that span across research domains that have so far developed in isolation.

The traditional district literature tends to assume that: (1) the competitiveness of firms depends on external sources of knowledge; (2) all firms in a district benefit from knowledge externalities; (3) relying on external knowledge relationships necessarily means these are confined to the district area. Our case study of the Barletta footwear district in the South of Italy suggests otherwise. Based on social network analysis, we demonstrate that the local knowledge network is quite weak and unevenly distributed among the local firms. A strong local network position of a firm tended to increase their innovative performance, and so did their connectivity to extra-local firms. So, it mattered being connected either locally or non-locally: being co-located was surely not enough. Having a high absorptive capacity seemed to raise only indirectly, through non-local relationships, the innovative performance of firms.Knowledge networks, industrial districts, innovative performance, absorptive capacity, footwear industry,

T o develop innovations in large, mature organizations, individuals often have to resort to underground, "bootleg" research and development (R&D) activities that have no formal organizational support. In doing so, these individuals attempt to achieve greater autonomy over the direction of their R&D efforts and to escape the constraints of organizational accountability. Drawing on theories of proactive creativity and innovation, we argue that these underground R&D efforts help individuals to develop innovations based on the exploration of uncharted territory and delayed assessment of embryonic ideas. After carefully assessing the direction of causality, we find that individuals' bootleg efforts are associated with achievement of high levels of innovative performance. Furthermore, we show that the costs and benefits of bootlegging for innovation are contingent on the emphasis on the enforcement of organizational norms in the individual's work environment; we argue and demonstrate empirically that the benefits of an individual's bootlegging efforts are enhanced in work units with high levels of innovative performance and which include members who are also engaged in bootlegging. However, during periods of organizational change involving formalization of the R&D process, individuals who increase their bootlegging activities are less likely to innovate. We explore the implications of these findings for our understanding of proactive and deviant creativity.

Social network analysis attracts increasing attention in economic geography. We claim social network analysis is a promising tool for empirically investigating the structure and evolution of inter-organizational interaction and knowledge flows within and across regions. However, the potential of the application of network methodology to regional issues is far from exhausted. The aim of our paper is twofold. The first objective is to shed light on the untapped potential of social network analysis techniques in economic geography: we set out some theoretical challenges concerning the static and dynamic analysis of networks in geography. Basically, we claim that network analysis has a huge potential to enrich the literature on clusters, regional innovation systems and knowledge spillovers. The second objective is to describe how these challenges can be met through the application of network analysis techniques, using primary (survey) and secondary (patent) data. We argue that the choice between these two types of data has strong implications for the type of research questions that can be dealt with in economic geography, such as the feasibility of dynamic network analysis.