Identification and Analysis of Knowledge-Based Governance Strategies in Science and Technology Parks: A Meta-Synthesis Approach

Purpose: This study aims to identify, analyze knowledge-based governance strategies in science and technology parks using a meta-synthesis approach, emphasizing the multi-level and multi-dimensional nature of governance in knowledge-intensive innovation ecosystems. With the rapid advancement of digital technologies, the growing complexity of knowledge flows, and the increasing interdependence among universities, industries, and government agencies, traditional linear and hierarchical governance models have proven insufficient for addressing dynamic and heterogeneous challenges. Knowledge-based governance, therefore, is not merely a managerial or administrative mechanism but functions as an integrative platform for institutionalizing intelligent knowledge flows, fostering transparency, trust, accountability, and collaborative innovation, while also ensuring sustainable social, economic, and environmental outcomes across diverse stakeholders. This study provides a theoretically grounded and empirically informed framework for governance in science and technology parks, highlighting the alignment of institutional, organizational, digital, and international dimensions to enhance decision-making, knowledge sharing, learning, and ecosystemic resilience, ultimately contributing to innovation-driven regional development.
Methodology: Grounded in an interpretive qualitative paradigm, this research employs the meta-synthesis method to systematically integrate and re-interpret findings from prior empirical and theoretical studies related to knowledge-based governance in science and technology parks. The study adopts Sandelowski and Barroso’s seven-step meta-synthesis framework, encompassing: (1) formulation of research questions; (2) comprehensive literature review; (3) systematic source identification and selection based on relevance and rigor; (4) detailed extraction of relevant data and concepts; (5) qualitative analysis and synthesis of primary, secondary, and final codes; (6) rigorous quality control to ensure the reliability, validity, and transparency of the synthesis process; and (7) presentation of synthesized findings in a structured framework. Through this methodology, the study develops a multi-dimensional, integrative set of governance strategies that reflects the interactions among institutional structures, organizational processes, digital platforms, policy frameworks, and international collaboration, providing a holistic understanding of governance mechanisms in science and technology parks. A total of 152 primary studies were examined, from which 78 secondary codes were generated and subsequently distilled into 9 overarching strategic dimensions, capturing the complexity and diversity of knowledge-based governance practices.
Results: The meta-synthesis identifies nine interrelated strategic dimensions central to effective knowledge-based governance in science and technology parks:

Transparency and accountability: This dimension encompasses institutional and legal transparency, open access to data, stakeholder responsiveness, and mechanisms for continuous reporting and feedback. The findings emphasize that transparency, coupled with stakeholder accountability, establishes the foundation for trust, collective learning, and decision-making legitimacy within multi-stakeholder environments. 2. Capacity building and empowerment: Effective governance requires both institutional capacity development and human capital empowerment. Key strategies include organizational strengthening, knowledge management systems, specialized training programs, intra- and inter-park knowledge sharing, and leadership development initiatives. These mechanisms enhance absorptive capacity, enable systematic learning, and facilitate the alignment of organizational objectives with broader governance goals. 3. Innovation and networking: The study underscores the role of open innovation, co-creation, and ecosystem-based networking as critical enablers of knowledge circulation and technology commercialization. By fostering interactions between startups, universities, research institutes, and industry partners, parks can support collaborative innovation, bridge gaps between knowledge producers and users, and accelerate the translation of knowledge into tangible economic and social value. 4. Digitalization and intelligent governance: Digital infrastructure, platform-based governance, and data-driven decision-making constitute the core of this dimension. The findings highlight how artificial intelligence, Internet of Things (IoT), and other digital technologies can optimize knowledge flows, enhance process efficiency, and support adaptive governance, while also enabling predictive analytics for strategic human capital planning and operational management within parks. 5. Smart policy-making: Adaptive and evidence-based policy frameworks, regulatory flexibility, and incentive structures are identified as essential for effective governance. Policies that integrate top-down guidance with participatory mechanisms allow for iterative learning, mitigate governance gaps, and align stakeholder interests while facilitating innovation and sustainable development. 6. Sustainable development and social responsibility: Governance strategies must incorporate environmental sustainability, ethical innovation, and social inclusion. Green technologies, low-carbon solutions, equitable access to resources, and socially responsible practices strengthen the legitimacy and long-term viability of parks, ensuring that knowledge-based growth is not solely economic but also socially and environmentally balanced. 7. Scientific diplomacy and international collaboration: Parks serve as nodes for global knowledge exchange, facilitating international technology transfer, cross-border learning, and collaborative innovation networks. Strategic partnerships at regional and international levels enhance the competitiveness of parks, allow for contextualized learning from diverse environments, and support the global positioning of national innovation systems. 8. Resilience and foresight: Governance frameworks must integrate adaptive capacities, risk management, strategic planning, and foresight mechanisms to address technological uncertainty, economic fluctuations, and evolving stakeholder expectations. Resilience is achieved not merely through robustness but by enabling rapid reconfiguration of resources, processes, and policies in response to emerging challenges. 9. Ecosystem convergence: Finally, the study highlights the convergence of university-industry-government networks and cross-sectoral collaborations as a central mechanism for integrated knowledge-based governance. Multi-level interactions among diverse actors facilitate trust, reduce conflicts of interest, accelerate knowledge transfer, and foster systemic innovation, ensuring that science and technology parks function as dynamic, learning-driven ecosystems rather than isolated entities.

Collectively, these nine dimensions provide a multi-level framework that guides the design, implementation, and evaluation of knowledge-based governance strategies in science and technology parks. They emphasize the interplay between institutional structures, digital tools, human capital development, policy frameworks, and international cooperation, establishing a foundation for participatory, transparent, and sustainable governance capable of enhancing regional innovation capacity.
Discussion: The findings of this meta-synthesis highlight that knowledge-based governance in science and technology parks is inherently multi-dimensional, dynamic, and deeply embedded in complex innovation ecosystems. The identification of nine interrelated strategic dimensions demonstrates that effective governance extends beyond traditional administrative or hierarchical approaches and requires an integrated framework combining institutional transparency, organizational capacity building, digital transformation, and collaborative innovation. These results are consistent with prior studies emphasizing the shift from linear governance models toward networked, participatory, and knowledge-driven systems.
A key contribution of this study lies in revealing the synergistic interaction among governance dimensions. For instance, transparency and accountability not only enhance trust but also enable more effective knowledge sharing and stakeholder engagement, which in turn strengthens innovation networks and ecosystem convergence. Similarly, digitalization and intelligent governance act as enablers that amplify the effectiveness of other dimensions by facilitating data-driven decision-making and optimizing knowledge flows. This interconnectedness suggests that governance strategies cannot be implemented in isolation but must be designed as part of a coherent and adaptive system.
Moreover, the findings underscore the critical role of contextual factors such as institutional structures, policy environments, and regional innovation capacities. The heterogeneity observed across science and technology parks indicates that while the proposed framework provides a comprehensive reference, its practical implementation should be tailored to local conditions. This aligns with the broader literature that emphasizes context-sensitive governance models in innovation ecosystems.
Importantly, this study bridges a significant gap in the literature by integrating fragmented perspectives on knowledge management, innovation, and governance into a unified analytical framework. It advances the understanding of how knowledge-based governance can simultaneously promote innovation, resilience, and sustainable development. The emphasis on dimensions such as scientific diplomacy, sustainability, and foresight further expands the scope of governance beyond economic performance toward long-term societal and environmental impact.
Conclusion: This research contributes to the literature by presenting a novel, multi-dimensional, and integrative framework for knowledge-based governance in science and technology parks. Unlike prior studies that primarily focus on operational efficiency or sector-specific interventions, this study emphasizes governance as a participatory, dynamic, and sustainability-oriented system. By detailing strategic dimensions across institutional, organizational, digital, policy, and international domains, the findings provide actionable guidance for designing resilient, transparent, and socially responsible governance mechanisms. The study enhances understanding of how knowledge-based governance can simultaneously support innovation, learning, and sustainable development, offering a roadmap for the strategic transformation of science and technology parks into knowledge-intensive ecosystems that balance economic, social, and environmental objectives.