Scientific and technological parks in innovation ecosystems: the proposition of an analytical structure

Purpose This paper aims to propose an analytical structure for scientific and technological parks (STPs) as innovation ecosystems based on generating knowledge spillovers. Design/methodology/approach The analytical structure is constructed using a strategic approach, with STPs being viewed as an ecosystem and their interactions with the social context based on knowledge spillovers. In the empirical phase, a case study is developed in a Brazilian STP focused on food and renewable energy, enabling the application of the proposed analytical structure. Findings This study proposes that STPs can be central for innovation ecosystems, coordinating activities and resources. Also, STPs generate knowledge spillovers for geographically close and external actors, expanding the impact and benefits of innovation. The integration of these two propositions composes the proposed analytical structure that emphasizes the STP as the protagonist of the discussion on ecosystem management. Originality/value This study explores the relationship between STPs, innovation ecosystems and knowledge spillovers to clarify their strategic role in fostering innovation. It integrates multiple theoretical perspectives to propose new, broadly applicable frameworks. Given the limited and recent research on STPs within innovation ecosystems, the study provides a timely opportunity to investigate the management role of STPs at the organizational level.

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Publication Details

Journal
Competitiveness Review An International Business Journal incorporating Journal of Global Competitiveness
Published
2024-12-24
DOI
https://doi.org/10.1108/cr-06-2024-0113
Citations
1
Primary Topic
University-Industry-Government Innovation Models
Type
article
Field-Weighted Citation Impact
0.73
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article

Scientific and technological parks in innovation ecosystems: the proposition of an analytical structure

Camila Coletto, Daniela Callegaro de Menezes, Leonardo Caliari
1 citations
Competitiveness Review An International Business Journal incorporating Journal of Global Competitiveness
University-Industry-Government Innovation Models
0.73
article

Scientific and technological parks in innovation ecosystems: the proposition of an analytical structure

Camila Coletto, Daniela Callegaro de Menezes, Leonardo Caliari
article en
1 citations

Abstract

Purpose This paper aims to propose an analytical structure for scientific and technological parks (STPs) as innovation ecosystems based on generating knowledge spillovers. Design/methodology/approach The analytical structure is constructed using a strategic approach, with STPs being viewed as an ecosystem and their interactions with the social context based on knowledge spillovers. In the empirical phase, a case study is developed in a Brazilian STP focused on food and renewable energy, enabling the application of the proposed analytical structure. Findings This study proposes that STPs can be central for innovation ecosystems, coordinating activities and resources. Also, STPs generate knowledge spillovers for geographically close and external actors, expanding the impact and benefits of innovation. The integration of these two propositions composes the proposed analytical structure that emphasizes the STP as the protagonist of the discussion on ecosystem management. Originality/value This study explores the relationship between STPs, innovation ecosystems and knowledge spillovers to clarify their strategic role in fostering innovation. It integrates multiple theoretical perspectives to propose new, broadly applicable frameworks. Given the limited and recent research on STPs within innovation ecosystems, the study provides a timely opportunity to investigate the management role of STPs at the organizational level.

Competitiveness Review An International Business Journal incorporating Journal of Global CompetitivenessVol. 36(1)
Universidade Federal do Rio Grande do Sul (BR), Instituto Federal Farroupilha (BR)
Openalex Percentile: Top 20%
University-Industry-Government Innovation Models
0.73
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