@article{ZHAO2025, 
author = {Zhouhua ZHAO and Yaqi YUAN and Qi YUN},
title = {The measurement of industrial intelligence level in the Yellow River Basin and its spatio-temporal evolution analysis},
year = {2025},
journal = {Journal of Economics of Water Resources},
volume = {43},
number = {6},
pages = {12-19},
keywords = {industrial intelligence, entropy weight method, vertical and horizontal pull-out grade method, spatio-temporal evolution, the Yellow River Basin},
url = {https://www.sciopen.com/article/10.3880/j.issn.1003-9511.2025.06.002},
doi = {10.3880/j.issn.1003-9511.2025.06.002},
abstract = {To examine the level of industrial intelligence and its spatio-temporal evolution in the Yellow River Basin and to provide a reference for promoting high-quality development of industrial intelligence in the Yellow River Basin, this paper constructs an evaluation index system in four dimensions: digital-intelligence infrastructure, digital-intelligence applications, digital-intelligence benefits, and digital-intelligence environmental protection, to measure industrial intelligence across nine provinces (autonomous regions) in the Yellow River Basin. Using the Dagum Gini coefficient and kernel density estimation, this paper analyzes regional disparities and their spatio-temporal evolution of industrial intelligence level in the Yellow River Basin. The results indicate that the level of industrial intelligence in the Yellow River Basin has risen steadily but remains uneven, with downstream regions leading and the middle and upper reaches lagging; overall regional disparities in the industrial intelligence level are narrowing and are mainly driven by interregional differences; and the distribution of the industrial intelligence level in the Yellow River Basin is distinctly multimodal, exhibiting a clear polarization trend.}
}