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Entrepreneurial opportunity (EO) identification pertains to the core processes of entrepreneurship and innovation. The initial phase of this process starts with individual cognition, which is why cognition has been established as a critical theoretical perspective.

Knowledge and new information have been confirmed as essential cognitive impact factors. However, it is not understood well, how individuals apply those factors and how they actually identify innovative and economically viable EOs. To address the limitations of current research, this chapter investigates the current literature on underlying cognitive processes of opportunity identification.

The literature analysis demonstrates that there is not a single cognitive process but rather a magnitude of different micro-mechanisms that are necessary for the successful identification of EOs. The findings are grouped to four categories of cognitive processes and entail their micro-mechanisms: pattern recognition, information processing, and creative thinking. Furthermore, the analysis reveals that those micro-mechanisms have seldom been related to each other within the scope of opportunity identification. This chapter closes this gap by discussing and contrasting and the different process categories and respective micro-mechanisms and suggests an integrative theory development and avenues for future research.

The purpose of this paper is twofold: first, to present a bibliometric analysis and systematic literature review of industry convergence and value innovation to understand the current research status; second, to provide a coherent theoretical research framework for future research.

This study adopts a two-step analysis approach by combining bibliometric analysis and systematic literature review to explore the research topic of industry convergence and value innovation. Besides, two bibliometric tools, HistCite and VOSviewer, were applied to this study.

This study found that Stefanie Bröring and Fredrik Hacklin are the top two most influential authors among all authors in the sample publications. Technological Forecasting and Social Change is one of the top-ranking journal that often publishes this topic of articles. Germany and the University of Munster are the most influential country and institutions, respectively. Besides, five core research themes were identified based on keywords co-occurrence map, theoretical lenses, factors promoting industry convergence, indicators of industry convergence, the impact of industry convergence and emerging research directions. Based on the above analysis, this paper constructed a theoretical research framework of industry convergence and value innovation.

This paper only draw data from one database – Web of Science – which cannot provide broad coverage of the research topic. Besides, the bibliometric method of this paper is based on high local citation score and high-frequency words, articles in the skirting subjects’ area may not be analyzed.

With the rapid development of technology, such as nanotechnology, radio - frequency identification (RFID), etc., the iterative upgrading of products also comes. As a result, the boundary between industries is gradually blurred, and the phenomenon of industry convergence appears. Therefore, managerial decision-makers are facing challenges of how to respond to the convergence phenomena. From the firm level, firms are facing the problem of value innovation of the existing product, new product development and core competence improvement. Industries are facing the problem of transformation and upgrading. This paper provides certain theoretical insights for both firms and industries to guide the practice accordingly.

This paper is the first to use a bibliometric method to examine the topic of industry convergence and value innovation. In addition, this paper presents an in-depth analysis of this topic and provides a comprehensive theoretical research framework for future study.