Information from the abstract
This study examines the interdependencies among good governance components using data from the Sustainable Governance Indicators project. Employing expectation-maximization clustering, Bayesian network-tree augmented naive Bayes classification and Bayesian structural equation modeling, the analysis reveals key governance drivers, including parties and interest associations, adaptability, and interministerial coordination. Additionally, evidence-based instruments and societal consultation amplify systemic interactions, reinforcing governance effectiveness. The findings challenge the assumption of independent governance components, highlighting synergistic and cascading effects. This study extends the application of governance theory and resource dependence theory, demonstrating the necessity of integrated governance strategies. By offering a nuanced understanding of governance dynamics, this research provides policymakers with actionable insights to enhance resilience, inclusivity, and adaptability in OECD and EU governance frameworks. Points to practitioners: Policymakers should strengthen interministerial coordination, adaptability, and societal consultation to leverage governance synergies and enhance policy coherence and implementation. Investing in data-driven policymaking—through impact assessments and policy evaluations—improves transparency, accountability, and public trust. Fostering institutional adaptability, political participation, and citizen engagement is essential for inclusive and sustainable governance in dynamic policy environments.
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This record has an Impact Signal of 76/100 based on recency, source, collaboration, and bibliographic signals. It prioritizes monitoring and is not a judgment of research quality.
Related topics: Public Policy and Administration Research · Sustainability and Climate Change Governance · E-Government and Public Services
Thai researcher and institutional participation
Boonlert Jitmaneeroj · Chulalongkorn University
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