Designing a model of government supportive policies in knowledge-based companies: Meta synthesis approach

This study presents a novel model for identifying the key categories and elements of government supportive policies targeted at knowledge-based companies. Employing a qualitative research design based on the meta-synthesis approach, the study follows the seven-step process outlined by Sandelowski and Barroso (2007). A total of 34 studies were selected for final evaluation based on their relevance to the research topic and the quality of the sources. To ensure the reliability of the findings, inter-coder agreement was assessed using the Kappa coefficient, which yielded a value of 0.81. The analysis, conducted using MAXQDA20 software, led to the identification of five key categories and 16 associated concepts. These categories include: (1) Supportive and Financial Policies, (2) Technology Development and Innovation, (3) Management and Organizational Development, (4) Development Challenges and Strategies, and (5) Sustainability and Environment. This model provides a practical framework for policymakers and organizational leaders to align strategies with effective government support mechanisms. The study also highlights critical gaps—particularly in areas such as R&D subsidies, structural challenges, resource allocation, environmental considerations, and technology support—that should be addressed in future policy development. The findings offer important insights for both policymakers and knowledge-based companies by providing a framework to align governmental support with the evolving needs of these firms, thereby fostering innovation and sustainable growth.

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Publication Details

Journal
Sustainable Futures
Published
2025-06-21
DOI
https://doi.org/10.1016/j.sftr.2025.100903
Citations
1
Primary Topic
Innovation Policy and R&D
Type
article
Field-Weighted Citation Impact
3.13
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article

Designing a model of government supportive policies in knowledge-based companies: Meta synthesis approach

Mojtaba Heidari, Reza Rostamzadeh, Karim Esgandari, Hanieh Mahooti
1 citations
Sustainable Futures
Innovation Policy and R&D
3.13
article

Designing a model of government supportive policies in knowledge-based companies: Meta synthesis approach

Mojtaba Heidari, Reza Rostamzadeh, Karim Esgandari, Hanieh Mahooti
article en
1 citations

Abstract

This study presents a novel model for identifying the key categories and elements of government supportive policies targeted at knowledge-based companies. Employing a qualitative research design based on the meta-synthesis approach, the study follows the seven-step process outlined by Sandelowski and Barroso (2007). A total of 34 studies were selected for final evaluation based on their relevance to the research topic and the quality of the sources. To ensure the reliability of the findings, inter-coder agreement was assessed using the Kappa coefficient, which yielded a value of 0.81. The analysis, conducted using MAXQDA20 software, led to the identification of five key categories and 16 associated concepts. These categories include: (1) Supportive and Financial Policies, (2) Technology Development and Innovation, (3) Management and Organizational Development, (4) Development Challenges and Strategies, and (5) Sustainability and Environment. This model provides a practical framework for policymakers and organizational leaders to align strategies with effective government support mechanisms. The study also highlights critical gaps—particularly in areas such as R&D subsidies, structural challenges, resource allocation, environmental considerations, and technology support—that should be addressed in future policy development. The findings offer important insights for both policymakers and knowledge-based companies by providing a framework to align governmental support with the evolving needs of these firms, thereby fostering innovation and sustainable growth.

Sustainable FuturesVol. 10
Islamic Azad University of Urmia (IR), Payame Noor University (IR)
Openalex Percentile: Top 8%
Innovation Policy and R&D
3.13
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