KNOWLEDGE SHARING BY CIVIL SERVANTS IN ADMINISTRATIVE RESTRUCTURING AND DIGITAL GOVERNMENT DEVELOPMENT

Abstract

Knowledge sharing is considered an important organizational capability, contributing to learning, innovation, and improved operational efficiency. However, empirical studies on knowledge-sharing behavior in the public sector remain limited, particularly in the context of administrative restructuring and the transition toward digital government. In Vietnam, the process of administrative unit mergers, staff streamlining, and digital transformation poses an urgent requirement for civil servants to exchange and transfer knowledge to maintain continuity and efficiency in public service delivery. This article explores and examines the factors influencing civil servants’ intentions and knowledge-sharing behavior in the context of administrative restructuring toward digital government. Based on integrating three theoretical frameworks, namely Social Influence Theory (SIT), Social Cognitive Theory (SCT), and the Technology Acceptance Model (TAM), the study examines the role of social factors, individual cognitive factors, and technological factors in knowledge-sharing intention. At the same time, the study proposes the moderating role of trust in technology and knowledge ambidexterity in the relationship between intention and knowledge-sharing behavior. Survey data were collected from civil servants at administrative agencies in Ho Chi Minh City and were analyzed using the PLS-SEM model. The expected results are expected to contribute to knowledge management theory in the public sector and provide practical implications for the process of building digital government. This study still has several limitations that need to be considered. Firstly, data were collected mainly from civil servants in Ho Chi Minh City, so the generalizability to other localities is limited. Secondly, the cross-sectional research design has not fully reflected the temporal variation in knowledge-sharing behavior during the process of administrative restructuring and digital transformation. Thirdly, although the research model integrates SIT–SCT–TAM, it can still be extended to include institutional, leadership, and organizational culture factors. Fourthly, the use of self-report measures may lead to bias due to social desirability. Therefore, future studies should expand the sample scope, apply longitudinal designs, and incorporate additional actual behavioral data to enhance reliability and practical value.