摘要：

Abstract:

【Purpose/significance】 Clarify the generation mechanism of government data barriers and provide new ideas for promoting

data connectivity, which is important for implementing the Digital China Strategy and preventing risk, disaster and crisis.【Method/pro⁃

cess】 This paper analyses the factors influencing the generation of government data barriers, constructs a multi-sectoral game model

from a single-layer to a multi-layer network in turn, introduces stochastic learning methods to restore the agent's initiative, and calcu⁃

lates the effect of the influencing factors through MATLAB simulations.【Result/conclusion】 The generation of government data barri⁃

ers is the result of multiple departments in the government data governance network repeatedly measuring the cooperative benefits,

relative benefits and distributed benefits. The most effective way to block the generation of government data barriers is to increase the

cooperative benefits in promoting data flow. The effectiveness of increasing the active benefits of one side will be diminished according

to the theory of free rider problem. Punishments from higher authorities have a greater impact than rewards, but are limited by the size

of the network. Reducing the cost of joint liability avoidance by higher and lower levels can make government departments inclined to

maintain the status quo. Practical strategies for controlling the generation of data barriers are proposed.

【

Innovation/limitation】 This

paper innovatively explains the process of generating government data barriers from the perspective of network evolution. In the future,

the coupling reaction of influencing factors should be considered to improve the extraction depth of network structure features.