Document Type

Journal Article

Publication Title

Innovation and Management Review

Publisher

Emerald

School

School of Business and Law

RAS ID

52084

Comments

Fioravanti, V. L. S., Stocker, F., & Macau, F. (2022). Knowledge transfer in technological innovation clusters. Innovation & Management Review. Advance online publication. https://doi.org/10.1108/INMR-12-2020-0176

Abstract

Purpose: The aim of this research is to analyze the knowledge transfer process in technological innovation clusters. The problem of the study addresses how organizations can act in a network to enhance experiences and gains, particularly in the aspect of knowledge management. Design/methodology/approach: The study is qualitative, applied through a case study, cross-sectional and multiple sources of evidence – semistructured interviews, nonparticipant observation and analysis of documents and secondary institutional data. The case analyzed was the Technology Park of São José dos Campos, in Brazil, involving private companies, governmental organizations, universities and research institutions. Findings: The results reinforce the arguments that the transfer of knowledge is influenced by factors, facilitators or inhibitors such as: cooperation, relationship with institutions, workforce mobility and geographical proximity, influencing the competitiveness and performance of the organizations in the cluster. Research limitations/implications: This study advances the knowledge management literature in network environments, especially in technological innovation clusters, systematizing and highlighting the facilitating and inhibiting dimensions of knowledge transfer. Practical implications: The present work has a direct dialogue with the managers and actors involved in the governance of these organizational arrangements with regard to increasing the capacity for creation and the dissemination of knowledge among organizations, educational institutions, government and companies. Originality/value: There is a presence of aspects indicating that knowledge goes beyond borders through dynamic and collaborative structures, reinforcing the premise that clusters must be perceived as an evolutionary system, whose result of interactions leads to a superior joint capacity.

DOI

10.1108/INMR-12-2020-0176

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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