Science and technology parks: Opening the pandora’s box of regional development

Data

2022-03-09

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Springer
Idioma
Inglês

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Resumo

For the last decades, Science and Technology Parks (STPs) have been emerging to help in the development of regions; as a consequence, there has been an improvement in RIS (Regional Innovation System) performance. This research aims to assess the con- tribution of STPs to the performance improvement of RIS in Portugal. A quantitative methodology is used, based on a framework, which is supported by four latent varia- bles: (1) Policy Instrument (PI); (2) Regional Innovation Inputs (INNI); (3) Regional Innovation Outputs (INNO), and (4) Regional Idiosyncrasies (REG). The data was col- lected from Regional Innovation Scoreboard reports available for the seven Portuguese regions: North, Center, Lisbon, Alentejo, Algarve, and Autonomous Regions of Azores and Madeira between 2007 and 2018. The working sample is composed of 392 observa- tions. Our findings show a clear innovation delimitation in Portugal. The North, Center, and Lisbon areas are the areas that have strong innovation. The rest of the country has moderate innovation, including the autonomous regions. Nonetheless, an improvement in innovation was registered between 2016 and 2019 in all regions except Alentejo and Algarve. This aligns with the Policy Instrument’s positive influence on the Regional Innovation inputs, which positively influences the Regional Innovation Outputs. The outcome allowed practical suggestions for regional stakeholders. This research is origi- nal for its methodological approach, never applied to the Portuguese context.

Palavras-chave

Regional innovation systems, Science and technology parks, Regional innovation scoreboard, Efficiency, Dominant policy input, Structural equation modelling

Tipo de Documento

Artigo

Versão da Editora

10.1007/s13132-022-00995-y

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Citação

Gomes, S., Lopes, J. M., Ferreira, L., & Oliveira, J. (2022). Science and technology parks: Opening the pandora’s box of regional development. Journal of Knowledge Economy, (2022), 1-24. Disponível no Repositório UPT, http://hdl.handle.net/11328/3957

Identificadores


1868-7865 (Print)
1868-7873 (Eletrónico)

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Acesso Aberto

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