Research Article
Comparison of Digital Economy Efficiency and Input Redundancy in China Based on DEA Model
@INPROCEEDINGS{10.4108/eai.17-6-2022.2322774, author={Ruping Wang and Xieyong Wang and Yujia Wang}, title={Comparison of Digital Economy Efficiency and Input Redundancy in China Based on DEA Model}, proceedings={Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China}, publisher={EAI}, proceedings_a={ICIDC}, year={2022}, month={10}, keywords={digital economy efficiency malmquist-dea dea model input redundancy}, doi={10.4108/eai.17-6-2022.2322774} }- Ruping Wang
Xieyong Wang
Yujia Wang
Year: 2022
Comparison of Digital Economy Efficiency and Input Redundancy in China Based on DEA Model
ICIDC
EAI
DOI: 10.4108/eai.17-6-2022.2322774
Abstract
Based on identifying the scope of industries of the digital economy, the article constructs a digital economy efficiency evaluation index system with reference to the theory of three factors of production and the “Classifications of Statistics of Digital Economy and Its Core(2021)”, selects the CCR-DEA, BBC-DEA and Malmquist-DEA models to measure the digital economy efficiency of 30 provinces and cities in China from 2013 to 2020 in two dimensions, static and dynamic, respectively; and the input redundancy of 30 provinces and cities are classified and compared. The study finds that: first, most of the 30 provinces and cities in China are inefficient during the study period, so there is still much room for improvement. Second, total factor productivity (TFP), in general, is increasing in an "M" shape, and it is mainly due to the increase of the technological progress index. Third, only 8 provinces and municipalities are zero redundancy areas, so the remaining provinces and municipalities still need to make corresponding policy adjustments according to their own conditions to guide the quality allocation of regional resources.