Reviewing the intellectual structure and evolution of the innovation systems approach: A social network analysis

Dahesh, Mehran Badin; Tabarsa, Gholamali; Zandieh, M.; Hamidizadeh, Mohammad Reza

doi:10.1016/j.techsoc.2020.101399

Cited by 68 publications

(35 citation statements)

References 85 publications

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“…Within this approach, the funded H2020 consortia develop, on the one hand, networks of partnersin which those entities collaborating in the same project are linked-and, on the other hand, networks of projects-in which those projects sharing partners are connected. Social network analysis has recently emerged as a powerful technique to evaluate innovation systems, which has the unexploited potential to study the consistency between smart specialization policies and innovation systems [32].…”

Section: Regional Innovation Systemsmentioning

confidence: 99%

Contribution of the Horizon2020 Program to the Research and Innovation Strategies for Smart Specialization in Coal Regions in Transition: The Spanish Case

2022

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This work aims to assess how regional innovation systems support research and innovation smart specialization strategies (RIS3) in coal intensive regions. Although many authors have analyzed energy transition paths for the European coal regions, no study has assessed how the network properties of their innovation systems are aligned with the priorities identified in their RIS3. This work fills this gap, relying on social network analysis (SNA) to assess innovation systems’ underlying networks, considering the active role of their nodes, thus, contributing to the innovation systems literature in the areas of modelling, simulation and performance evaluation. Within this work, regional innovation systems are modelled as research networks. These networks are promoted by the consortia funded by the European H2020 program. The assessment of the topology and properties of these networks enables the evaluation of the functioning of the innovation system, its technological strengths, as well as the key players involved. Based on these results, the characteristics of the innovation systems are compared to the priorities established by the RIS3. Three Spanish coal intensive regions (Aragón, Asturias and Castilla y León) are considered as use cases in this study. The obtained results indicate that, in some cases, the technological strengths of the regional innovation systems are not considered in the identification of the RIS3 priorities, while some RIS3 priorities are not supported by the innovation system. Considering these results, this paper proposes recommendations for regional and European policymakers, as well as for participants in the European research programs.

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Section: Regional Innovation Systemsmentioning

confidence: 99%

Contribution of the Horizon2020 Program to the Research and Innovation Strategies for Smart Specialization in Coal Regions in Transition: The Spanish Case

2022

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“…A comprehensive review of innovation studies showed that the discipline with the most variety in innovation research is geography. Other disciplines are economics, environmental studies, urban and regional planning, and management (Dahesh, Tabarsa, Zandieh, & Hamidizadeh, 2020). This research focused on urban and regional planning and geography.…”

Section: Related Research On Global Innovation Networkmentioning

confidence: 99%

National borders transcended: the impact of geographical proximity on the growth of global innovation networks among cities in East Asia

Lim

Han

2021

International Journal of Urban Sciences

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Recently, the concept of the global innovation network (GIN) has been emphasized in view of increasing joint international research within regional economies as enabled by drastic changes in technology. However, insights gained from quantitative analysis of GINs are lacking. This study empirically investigated the GINs among major cities in East Asia by using data on patented co-inventions. This included an analysis of the factors that influence networks in the formation of international research collaborations in East Asia, and its interplay with geographical proximity. The results of the analysis suggest that there is a system of mesoscale international networks such as those in East Asia between GINs and national innovation systems. Our findings suggest that future policy should be more supportive of international innovation networks, especially in East Asia. Highlights. This study traces the evolution of global innovation networks among major East Asian cities over time. . China, South Korea, and Taiwan are increasing their share in the network. . Geographical proximity has the greatest influence on global innovation network. . Networks formed by transnational geographic proximity are found between major cities.

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“…First, this paper constructed the EIE model from three parts: innovation subject, innovation resource, and innovation environment. Existing researches pay close attention to the system boundary difference between IE and EIE [54]. is paper further focuses on the characteristic of innovation elements within the system.…”

Section: Eoretical and Empirical Implicationsmentioning

confidence: 99%

Increment of Heterogeneous Knowledge in Enterprise Innovation Ecosystem: An Agent‐Based Simulation Framework

Wang

Shi

2021

Complexity

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How can enterprises acquire knowledge resources quickly to maintain a competitive advantage in the market has become the focus of attention among academic circles and enterprises in the era of the knowledge economy. Based on the ecology theory, this paper analyzed the characteristics of the innovation subject and the rules of the heterogeneous knowledge interaction between innovation subjects. Then, this paper proposed a multiagent-based model of EIE (enterprise innovation ecosystem) heterogeneous knowledge increment to simulate the interactions between innovation subjects. By combining the biotic factors (government and service institutions) and abiotic factors (economical, social, and cultural), this paper designs eight different innovation environment scenarios to explore the dynamic impacts of these factors on EIE heterogeneous knowledge increment. The research findings were as follows: (1) In the introduction stage of innovation collaboration between innovation subjects, the same investment of the innovation elements in academic institutes is more beneficial to increasing system heterogeneous knowledge than investment in enterprises. (2) The cultivation of innovative biotic factors in service institutions is conducive to the rapid interaction of heterogeneous knowledge among the innovation subjects. Still, it is not suitable for areas with higher homogeneous knowledge because high homogeneous environment can easily lead to intensified market competition. (3) The cultivation of the abiotic innovation environment is conducive to maintain stable high-speed growth of EIE heterogeneous knowledge increment over a long period. (4) Without considering the cost of environmental cultivation, cultivating biotic and abiotic environments at the same time is the most beneficial choice to EIE heterogeneous knowledge increment.

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Reviewing the intellectual structure and evolution of the innovation systems approach: A social network analysis

Cited by 68 publications

References 85 publications

Contribution of the Horizon2020 Program to the Research and Innovation Strategies for Smart Specialization in Coal Regions in Transition: The Spanish Case

Contribution of the Horizon2020 Program to the Research and Innovation Strategies for Smart Specialization in Coal Regions in Transition: The Spanish Case

National borders transcended: the impact of geographical proximity on the growth of global innovation networks among cities in East Asia

Increment of Heterogeneous Knowledge in Enterprise Innovation Ecosystem: An Agent‐Based Simulation Framework

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