Factor-driven or innovation-driven? The role of digital technology in the cleanliness of industrial structure

被引:9
作者
Zhu, Xuehong [1 ,2 ]
Dong, Yu [1 ]
Xu, Qiong [1 ]
机构
[1] Cent South Univ, Sch Business, Changsha 410083, Peoples R China
[2] Cent South Univ, Inst Met Resources Strategy, Changsha 410083, Peoples R China
关键词
Manufacturing industry; Digital technology; The cleanliness of industrial structure; Total factor productivity; Factor distortion; GROWTH; PRODUCTIVITY; MODEL; ICT; MISALLOCATION; DETERMINANTS; INVESTMENT; CHINA; PRICE;
D O I
10.1016/j.jclepro.2024.142136
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The role of digital technology in structural change of three major industries has been widely recognized, but its influence on the internal cleanliness change of the industry has not been confirmed. Based on panel data of 36 industrial sub -sectors in China from 2002 to 2020, this paper discusses the mechanism of digital technology driving the cleanliness of industrial structure from a heterogeneity perspective. The theoretical model indicates that variations in output growth across different industries can be attributed to total factor productivity (TFP) and factor distortions, and the heterogeneous contribution of digital technology to TFP and factor distortions leads to the change of industrial structure. The empirical results show that digital technology can not only promote innovation -driven development by increasing total factor productivity, but also help factor -driven development by reducing factor distortion. Heterogeneity tests show that digital technology contributes to the cleanliness of industrial structure, and polluting industries are mainly driven by factors, while cleaning industries are mainly driven by innovation. Therefore, it is necessary to correct the application direction of digital technology in time to better empower innovative development and clean production.
引用
收藏
页数:15
相关论文
共 76 条
[11]   STRUCTURAL CHANGE AND THE KALDOR FACTS IN A GROWTH MODEL WITH RELATIVE PRICE EFFECTS AND NON-GORMAN PREFERENCES [J].
Boppart, Timo .
ECONOMETRICA, 2014, 82 (06) :2167-2196
[12]   Creative accounting or creative destruction? Firm-level productivity growth in Chinese manufacturing [J].
Brandt, Loren ;
Van Biesebroeck, Johannes ;
Zhang, Yifan .
JOURNAL OF DEVELOPMENT ECONOMICS, 2012, 97 (02) :339-351
[13]  
Broda C, 2017, RES ECON, V71, P759, DOI 10.1016/j.rie.2017.10.001
[14]   Can reduced entry barriers worsen market performance? A model of employee entry [J].
Burke, AE ;
To, T .
INTERNATIONAL JOURNAL OF INDUSTRIAL ORGANIZATION, 2001, 19 (05) :695-704
[15]   The digital economy, industrial structure upgrading, and carbon emission intensity -- empirical evidence from China's provinces [J].
Chang, Hong ;
Ding, Qingyi ;
Zhao, Wanzheng ;
Hou, Na ;
Liu, Wenwen .
ENERGY STRATEGY REVIEWS, 2023, 50
[16]   Comparative analysis of total factor productivity in China's high-tech industries [J].
Chen, Xiaoqing ;
Liu, Xinwang ;
Zhu, Qingyuan .
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2022, 175
[17]  
Chen Y.B., 2013, Econ. Res., V48
[18]   Industrial structure, technical progress and carbon intensity in China's provinces [J].
Cheng, Zhonghua ;
Li, Lianshui ;
Liu, Jun .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2018, 81 :2935-2946
[19]   Digital technologies, innovation, and skills: Emerging trajectories and challenges [J].
Ciarli, Tommaso ;
Kenney, Martin ;
Massini, Silvia ;
Piscitello, Lucia .
RESEARCH POLICY, 2021, 50 (07)
[20]   A Crash Course in Good and Bad Controls [J].
Cinelli, Carlos ;
Forney, Andrew ;
Pearl, Judea .
SOCIOLOGICAL METHODS & RESEARCH, 2024, 53 (03) :1071-1104