FACTORS RELATED TO DIGITAL TRANSFORMATION IN LOCAL GOVERNMENT: A SCOPING REVIEW
Abstract
This study examines factors shaping digital transformation in local government and the mechanisms through which these factors influence implementation outcomes. Using a scoping review design, the study maps recent empirical and conceptual literature to capture the breadth and diversity of evidence. A systematic search was conducted in Scopus, Springer, and EBSCOhost using the keywords “digital transformation” AND “local government”, limited to English-language publications published between 2021 and 2025. The search identified 246 records, of which 22 studies met the inclusion criteria and were included in the final analysis. Extracted data were synthesized using a multi-level analytical framework encompassing individual, organizational, and environmental dimensions. The review identifies nine factors frequently discussed as shaping digital transformation in local government: digital capabilities and literacy, readiness for change, organizational capacity, the role of public managers and leadership, organizational culture and values, private sector demands, public expectations, regulatory and political conditions, and broader external conditions. The literature also highlights recurring barriers, including limited digital infrastructure and technical expertise, budget constraints, bureaucratic resistance to change, weak political support, insufficient change-management capability, rigid regulatory frameworks, and complex legacy systems. The findings indicate that digital transformation in local government is not driven by technology alone, but by the interaction of human capabilities, organizational arrangements, leadership, and external stakeholder pressures. Overall, this review underscores the importance of a holistic and integrated approach that strengthens human resources, adaptive governance, and stakeholder coordination to ensure effective, inclusive, and sustainable digital transformation, particularly in decentralized and resource-constrained contexts.
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