Can Cross‐Sector Collaboration Contribute to Boundaries Reshaping of Digital Government Platforms? Empirical Evidence Based on Machine Learning and Text Analysis

Datos Bibliográficos

ID6446566
AutoresShaopeng Zhang (0000-0003-4415-1815, School of Economics and Management Northeast Forestry University Harbin China), Yinhao Yang (Bay Area International Business School Beijing Normal University Zhuhai China), Huanhui Gan (BDO China Shu Lun Pan CPAs Guangzhou China)
Año2025
Volumen103
Número3
Páginas756-772
Fecha de publicación2025-04-15
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaPublic Administration (JOURNAL)
Identificadores de la revistaISSN: 0033-3298 • E-ISSN: 1467-9299
EditorialWiley (PUBLISHER • GB)
DOI10.1111/padm.13064
OpenAlexW4409514139
IdiomaEN
Citas recibidas2
Referencias citadas55

Cross‐sector collaboration is regarded as an effective institution for the fragmentation of government organizations, but it is still unknown which organizational form can effectively promote the holistic governance of digital government platforms. We construct an attention‐based behavioral model according to behavior theory and then explore the impact and mechanism of cross‐sector collaboration on the holistic governance of digital government platforms. We show that cross‐sector collaboration has a negative effect on digital government platform governance. Mechanism analysis results show that cross‐sector collaboration based on the lead task system can enhance digital government platform governance through two pathways: the performance‐driven path of cross‐sector collaboration and the vertical intervention path steered by the leader's attention allocation. This study contributes both theoretical and empirical evidence to enhance the understanding of the micro‐operational mechanisms of cross‐sector collaboration based on the lead task system in digital government platforms

Business · Data science · Digital government · Digital transformation · Empirical evidence · Epistemology · Government (linguistics · Knowledge management · Linguistics · Natural language processing · World Wide Web · Artificial Intelligence · Computer Science · Digital Platforms and Economics · E-Government and Public Services · Privacy, Security, and Data Protection