Abstract:The strategies of the European Union and its Member States suppose that intellectual property (IP) created as a result of R&D is the engine of economic growth and welfare in society. Studies based on the European Regional Innovation Scoreboard (RIS) have demonstrated that R&D investments, support to the high technology industry and patenting intensity of the public sector differ in high-and low-income European countries. This fact refers to the need for adequate IP strategic indicators' system facilitating inn… Show more
“…Intellectual property (47.87%) and spin-offs (45.75%) stood out from the rest of the dominant mechanisms. The relevance of intellectual property has been noted by Perkmann et al [33], Mets et al [39], Jones and De Zubielqui [40], and Secundo et al [41]. Licensing intellectual property provides legal rights that give companies access to technological solutions in the universities' intellectual property [9].…”
University–industry collaborations create socioeconomic impacts for the areas where they are undertaken. Although these collaborations have recognized importance and a high potential to generate economic and social benefits, there is no consensus in the literature on a consolidated conceptual model for assessing their socioeconomic impacts. Given this scenario, this study reviews 94 studies on the socioeconomic impact of university–industry collaborations using a context–intervention–mechanism–outcomes configuration. The impacts identified in the systematic literature review are classified into: (1) economic, (2) social, and (3) financial. The systematic literature review also indicates that the impact of collaborations can change the context and enhance the mechanisms of technology transfer. From a theoretical viewpoint, this work contributes to the structuring of a conceptual model for assessing the socioeconomic impacts of university–industry collaborations. In addition, the results have contributions for management in each strand of the triple helix: they may be useful to guide universities and companies on how to assess the socioeconomic impacts of each collaboration, direct public agents in the evaluation of results of investments, and support the development of policies for innovation and technology management.
“…Intellectual property (47.87%) and spin-offs (45.75%) stood out from the rest of the dominant mechanisms. The relevance of intellectual property has been noted by Perkmann et al [33], Mets et al [39], Jones and De Zubielqui [40], and Secundo et al [41]. Licensing intellectual property provides legal rights that give companies access to technological solutions in the universities' intellectual property [9].…”
University–industry collaborations create socioeconomic impacts for the areas where they are undertaken. Although these collaborations have recognized importance and a high potential to generate economic and social benefits, there is no consensus in the literature on a consolidated conceptual model for assessing their socioeconomic impacts. Given this scenario, this study reviews 94 studies on the socioeconomic impact of university–industry collaborations using a context–intervention–mechanism–outcomes configuration. The impacts identified in the systematic literature review are classified into: (1) economic, (2) social, and (3) financial. The systematic literature review also indicates that the impact of collaborations can change the context and enhance the mechanisms of technology transfer. From a theoretical viewpoint, this work contributes to the structuring of a conceptual model for assessing the socioeconomic impacts of university–industry collaborations. In addition, the results have contributions for management in each strand of the triple helix: they may be useful to guide universities and companies on how to assess the socioeconomic impacts of each collaboration, direct public agents in the evaluation of results of investments, and support the development of policies for innovation and technology management.
“…These sub-categories were then organized into four main categories of phases in IP commercialization: ideation, development, creation, and commercialization (Table 2). (Ravi & Janodia, 2022); (Hayter & Link, 2022), (Mets et al, 2016), (Maslak & Pererva, 2023), (Damij et al, 2022), (Kodynetz & Maidanyk, 2019), (Pererva & Maslak, 2022) Identification Ideation…”
Section: Statistical Description and Analysismentioning
confidence: 99%
“…Research, Product development (Deshpande & Nagendra, 2020), (Tsybulev, 2014), (Maslak & Pererva, 2023), (Mets et al, 2016), (Kusmintarti et al, 2022), (Kruachottikul et al, 2023), (Vimalnath et al, 2022), (Park & Kang, 2015) R&D Development…”
Section: Blending the Knowledge Base On Ip Commercialization Phasesmentioning
This study aims to develop a comprehensive understanding of intellectual property (IP) commercialization in the creative industry, highlighting its essential role in the growth of the sector. 16 relevant articles were analyzed, resulting in the development of a four-phase model of IP commercialization: ideation, development, creation, and commercialization. These phases are combined with the concept of creativity-based innovation specific to the creative industry to form an integrative framework. Each phase emphasizes the interaction between divergent thinking and sequential processes in the commercialization journey while highlighting the central role of creativity at each stage. The findings of this study contribute to the academic discourse and provide practical guidance for practitioners, policymakers, and stakeholders in developing IP commercialization strategies in the creative industry.
“…Thus, policies should encourage the creation of these networks among SMEs to allow firms to create more innovative products and processes (Pires et al 2020). The ability to create and implement intellectual property is also among the most significant drivers of an innovation system and the number of scientific publications, PCT patent applications, licence and patent revenues are considered the main indicators for driving innovation (studies using the Regional Innovation Scoreboard show how high-tech industries exhibited a high patenting intensity) (Mets et al 2016).…”
Research and Innovation Strategies for Smart Specialization (RIS3) was integrated as a key piece of the cohesion policy for the European Union (EU) for 2014-2020. A RIS3 is an innovative approach that seeks to increase economic growth and to create jobs in Europe by enabling regions to identify and develop their competitive advantages. During the recent years, more than 120 RIS3 have been developed, being a large-scale EU experience aimed to develop innovation-driven economic transformations at national and regional levels. The objective of this article is to explore the models that best explain innovative employment and the emergence of new markets in Europe's regions. For that purpose, the latest dataset of the Regional Innovation Scoreboard 2019 was used, and regressions performed to identify the main factors behind the impact of regional innovation. The results unveil the 'double edge role' that some variables have on regional innovation, indicating the difficulties of managing different trade-offs and of a standalone innovation policy strategy. Policy measures are discussed to best manage these critical compromises and increase the impact of RIS3.
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