The impact of digital transformation on green total factor productivity of heavily polluting enterprises

被引:14
作者
Han, Jiabin [1 ]
Sun, Ruyu [1 ]
Zeeshan, Muhammad [1 ]
Rehman, Alam [2 ]
Ullah, Irfan [3 ]
机构
[1] Liaoning Tech Univ, Sch Business Adm, Huludao, Peoples R China
[2] Natl Univ Modern Language, Fac Management Sci, Islamabad, Pakistan
[3] Nanjing Univ Informat Sci & Technol, Reading Acad, Nanjing, Peoples R China
关键词
digital transformation; green total factor productivity; green innovation; management efficiency; external transaction costs; EFFICIENCY; EMISSION;
D O I
10.3389/fpsyg.2023.1265391
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
IntroductionDigital transformation has become an important engine for economic high-quality development and environment high-level protection. However, green total factor productivity (GTFP), as an indicator that comprehensively reflects economic and environmental benefits, there is a lack of studies that analyze the effect of digital transformation on heavily polluting enterprises' GTFP from a micro perspective, and its impact mechanism is still unclear. Therefore, we aim to study the impact of digital transformation on heavily polluting enterprises' GTFP and its mechanism, and explore the heterogeneity of its impact.MethodsWe use Chinese A-share listed enterprises in the heavily polluting industry data from 2007 to 2019, measure enterprise digital transformation indicator using text analysis, and measure enterprise GTFP indicator using the GML index based on SBM directional distance function, to investigate the impact of digital transformation on heavily polluting enterprises' GTFP.ResultsDigital transformation can significantly enhance heavily polluting enterprises' GTFP, and this finding still holds after considering the endogenous problem and conducting robustness tests. Digital transformation can enhance heavily polluting enterprises' GTFP by promoting green innovation, improving management efficiency, and reducing external transaction costs. The improvement role of digital transformation on heavily polluting enterprises' GTFP is more obvious in the samples of non-state-owned enterprises, non-high-tech industries, and the eastern region. Compared with blockchain technology, artificial intelligence technology, cloud computing technology, big data technology, and digital technology application can significantly improve heavily polluting enterprises' GTFP.DiscussionOur paper breaks through the limitations of existing research, which not only theoretically enriches the literature related to digital transformation and GTFP, but also practically provides policy implications for continuously promoting heavily polluting enterprises' digital transformation and facilitating their high-quality development.
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页数:15
相关论文
共 71 条
[1]   Digital economy and green total factor productivity-based on the empirical research on the resource-based cities [J].
Chen, Shi ;
Yang, Yang ;
Wu, Tingting .
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (16) :47394-47407
[2]   The impact of information and communication technology adoption on multinational firm boundary decisions [J].
Chen, Wenjie ;
Kamal, Fariha .
JOURNAL OF INTERNATIONAL BUSINESS STUDIES, 2016, 47 (05) :563-576
[3]   The effect of digital transformation on real economy enterprises? total factor productivity [J].
Cheng, Yiran ;
Zhou, Xiaorui ;
Li, Yongjian .
INTERNATIONAL REVIEW OF ECONOMICS & FINANCE, 2023, 85 :488-501
[4]   Productivity and undesirable outputs: A directional distance function approach [J].
Chung, YH ;
Fare, R ;
Grosskopf, S .
JOURNAL OF ENVIRONMENTAL MANAGEMENT, 1997, 51 (03) :229-240
[5]  
Clemons E. K., 1993, Journal of Management Information Systems, V10, P9
[6]   Nexus between digital transformation and energy technology innovation: An empirical test of A-share listed enterprises [J].
Du, Juntao ;
Shen, Zhiyang ;
Song, Malin ;
Zhang, Linda .
ENERGY ECONOMICS, 2023, 120
[7]   Promoting enterprise productivity: The role of digital transformation [J].
Du, Xinyi ;
Jiang, Kangqi .
BORSA ISTANBUL REVIEW, 2022, 22 (06) :1165-1181
[8]  
Du Y., 2022, J ZHONGNAN U EC LAW, V66, P119
[9]   Digital Transformation on Enterprise Green Innovation: Effect and Transmission Mechanism [J].
Feng, Hua ;
Wang, Fengyan ;
Song, Guomin ;
Liu, Lanlan .
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (17)
[10]   OUTPUT SLACKS-ADJUSTED COST EFFICIENCY AND VALUE-BASED TECHNICAL EFFICIENCY IN DEA MODELS [J].
Fukuyama, Hirofumi ;
Weber, William L. .
JOURNAL OF THE OPERATIONS RESEARCH SOCIETY OF JAPAN, 2009, 52 (02) :86-104