Mapping an innovation ecosystem using network clustering and community identification: a multi-layered framework

Assessing university-business collaborations for moderate innovators: Implications for university-led innovation policy evaluation

The growing literature on University-Industry Collaborations (UICs) highlights how learning processes get unevenly located in space, within centers of innovative activity, where the local presence of research-oriented universities plays a crucial role. Through a mixed-methods approach, this article explores the firm-level drivers of innovation and the interactions between a sample of companies and the local university in a moderate innovation EU region. Findings highlight that firms' size, sector, leadership's commitment to digitalization, and collaborations with the university explain companies' innovative performance. The article contributes to the university's societal impact assessment and discusses the implications for university-led innovation for Smart Specialization.

A Systematic Review of Enterprise Innovation Ecosystems

With rapid changes and increasing uncertainty in the market environment, enterprise innovation ecosystems (EIEs) have increasingly been promoted in the past decade. Nevertheless, research on EIEs has fallen into a fuzzy state. Scholars have scattered views on the subject and have not systematically classified it, leading to a discussion regarding its conceptual rigor and comprehensive analysis. The purpose of this article is to conduct integrative research on EIEs and to examine all the relevant issues of existing views. This study screened all relevant topics in the past decade through the WOS database and identified significant journal articles. By reviewing and sorting out the relevant thematic literature from 2011 to 2020 and performing keyword cluster analysis, the research focus and hot spots of EIEs are determined. The entity structure, main types, dynamic mechanism, and evolution mechanism of EIEs were elaborated, and the definition of an EIE is finally determined. Through an analysis of the emerging viewpoints of EIEs, the hot spots of this topic are discussed. These streams provide opportunities for further research to consolidate the concepts of EIEs.

Mapping the technology evolution path: a novel model for dynamic topic detection and tracking

Identifying the evolution path of a research field is essential to scientific and technological innovation. There have been many attempts to identify the technology evolution path based on the topic model or social networks analysis, but many of them had deficiencies in methodology. First, many studies have only considered a single type of information (text or citation information) in scientific literature, which may lead to incomplete technology path mapping. Second, the number of topics in each period cannot be determined automatically, making dynamic topic tracking difficult. Third, data mining methods fail to be effectively combined with visual analysis, which will affect the efficiency and flexibility of mapping. In this study, we developed a method for mapping the technology evolution path using a novel non-parametric topic model, the citation involved Hierarchical Dirichlet Process (CIHDP), to achieve better topic detection and tracking of scientific literature. To better present and analyze the path, D3.js is used to visualize the splitting and fusion of the evolutionary path. We used this novel model to mapping the artificial intelligence research domain, through a successful mapping of the evolution path, the proposed method’s validity and merits are shown. After incorporating the citation information, we found that the CIHDP can be mapping a complete path evolution process and had better performance than the Hierarchical Dirichlet Process and LDA. This method can be helpful for understanding and analyzing the development of technical topics. Moreover, it can be well used to map the science or technology of the innovation ecosystem. It may also arouse the interest of technology evolution path researchers or policymakers.