THE CONSTRUCTION OF RISK ASSESSMENT MODEL AND EARLY WARNING MECHANISM FOR CHINA-MYANMAR CROSS-BORDER DATA FLOW

Abstract

With the deepening of the Digital Belt and Road (DBR) initiative and the rapid development of cross-border digital economy cooperation between China and Myanmar, the scale of cross-border data flow between the two countries has expanded exponentially, covering cross-border e-commerce, digital trade, border smart governance, cross-border financial services and other key fields. However, the significant differences in data governance systems, digital infrastructure construction levels, cybersecurity legal systems, and geopolitical environments between China and Myanmar have led to diversified and dynamic potential risks in cross-border data flow, which seriously restrict the standardized, safe and high-quality development of bilateral digital economic cooperation. To solve the problems of single risk dimension, outdated evaluation methods, lack of dynamic early warning capabilities and insufficient targeted research in existing cross-border data flow risk research, this paper constructs a multi-dimensional risk assessment index system for China-Myanmar cross-border data flow based on the new digital governance synergy theory and risk cascade amplification theory. This paper innovatively adopts the improved entropy weight-TOPSIS method combined with system dynamics (SD) to build a dynamic risk assessment model, and constructs a four-level dynamic early warning mechanism integrating risk identification, real-time assessment, level early warning and emergency response. Based on the latest panel data of China-Myanmar digital cooperation from 2021 to 2025, this paper conducts quantitative empirical analysis on the risk intensity, evolution trend and cascade transmission mechanism of China-Myanmar cross-border data flow. The research results show that the overall risk level of China-Myanmar cross-border data flow presents a fluctuating downward trend from 2021 to 2025, but technical risk and institutional governance risk are the core dominant risks, and geopolitical risk has a significant periodic amplification effect. The model can effectively identify dynamic mutation points of risks, and the early warning mechanism can realize real-time monitoring and hierarchical pre-control of cross-border data flow risks. This research fills the research gap of targeted risk assessment and early warning for China-Myanmar cross-border data flow, provides new theoretical paradigms and technical methods for cross-border data risk governance of neighboring countries along the Belt and Road, and provides empirical support and decision-making reference for the safe and orderly development of bilateral cross-border data cooperation.