Data-Driven Conceptual models for Sustainably Funding and Evaluating Community-Led Development Initiatives
Keywords:
Data-Driven, Conceptual, Models, Sustainable, Community, EvaluationAbstract
Community-led development (CLD) initiatives are increasingly recognized as critical mechanisms for sustainable socio-economic development, particularly in resource-constrained settings. This paper proposes data-driven conceptual models for sustainably funding and evaluating CLD initiatives. Through a systematic review of over 100 scholarly articles, policy reports, and practitioner studies published between 2000 and 2024, the study identifies key strategies, funding mechanisms, and evaluation approaches that enhance sustainability, accountability, and impact. The proposed models integrate data analytics, participatory evaluation, financial sustainability, stakeholder engagement, and impact assessment to guide practitioners, policymakers, and funders. The study demonstrates that leveraging data-driven insights enhances transparency, improves resource allocation, and supports evidence-based decision-making in community-led development programs.
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