DYNAMIC MULTI-ATTRIBUTE EVALUATION OF DIGITAL ECONOMY DEVELOPMENT IN CHINA: A PERSPECTIVE FROM INTERACTION EFFECT
提出一种基于灰色交互关联度的正态云矩阵模型，用于评价中国2013-2020年数字经济发展，发现年均增长7.87%但区域差异显著，交互效应仅影响高、低水平省份排名。
This study aims to reflect the grey information coverage and complex interactions effect in digital economy development. Therefore, a multi-attribute decision making method based on the grey interaction relational degree of the normal cloud matrix (GIRD-NCM) model is proposed. First, the original information coverage grey numbers are transformed into normal cloud matrixes, and then a novel Minkowski distance between normal clouds is proposed by using different information principles. Second, the GIRD-NCM model is established according to the Choquet fuzzy integral and grey relational degree. Finally, the dynamic comprehensive evaluation of digital economy development in China from 2013 to 2020 is conducted. The implementation, availability, and feasibility of the GIRD-NCM model are verified by comparative analysis with three existing evaluation models. The empirical findings reveal a stable growth trend in China’s digital economy, with an annual growth rate of 7.87%, however, there are notable regional development disparities. The change in interaction degree has no effect on the rankings of provinces that are in the lead or have a moderately high level of digital economy development, but has a positive and negative impact on the rankings of these provinces with high and low levels of digital economy development, respectively.