跨部门协作能否重塑数字政府平台的边界?基于机器学习和文本分析的实证证据

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

Public Administration · 2025
被引 8
ABS 4

中文导读

研究了跨部门协作对数字政府平台整体治理的影响,发现其有负面效应,但基于牵头任务制的协作可通过绩效驱动和领导注意力分配两条路径改善治理。

Abstract

ABSTRACT 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.

数字政府跨部门协作机器学习文本分析公共管理