Data-driven, Digital Transformation and Enterprise Total Factor Productivity — Empirical Evidence from A-share Listed Companies in China
Journal: Modern Economics & Management Forum DOI: 10.32629/memf.v5i2.1966
Abstract
With the continuous development of the digital economy, economies around the world have taken the promotion of big data as an important driver for high-quality economic development. This paper empirically examines the role and influence mechanism of big data-driven enterprise total factor productivity using a multi-period double-difference model with exogenous policy shocks of the National Comprehensive Pilot Zone on Big Data set up in China, with the help of enterprise data of China's A-share listed companies from 2010 to 2020. The results of the study show that big data development can significantly increase firms' total factor productivity, which still holds after a series of robustness tests such as Machine Learning, and is more pronounced in larger firms. Promoting the digital transformation of enterprises is an important mechanism of action for the development of big data to promote the total factor productivity of enterprises. This paper enriches the mechanism of the role of big data in driving the total factor productivity of enterprises, and provides empirical references for the regional emphasis on the development of big data and the transformation of enterprise databasing.
Keywords
big data, digital transformation, TFP, DID, machine learning
Funding
General Project of Educational Science Planning in Hunan Province: Research on the path of cultivating college students' green consumption concepts under the perspective of ecological moral education (XJK22BGD036)
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[1] Kaihao Liu, Yiran Wang, Yunfei Hao. How does the tax reduction policy affect the total factor productivity of enterprises? — Empirical evidence from the "two-tax merger"[J/OL]. Modern Finance and Economics,2024(02):99-113. (in Chinese)
[2] Xicang Zhao, Liang Xu, Yusen Luo. Does Intellectual Property Protection Enhance Total Factor Productivity of Enterprises? — Evidence from Chinese A-share Listed Companies[J]. Journal of Jiangsu University (Social Science Edition),2023,25(06):68-83. (in Chinese)
[3] Delong HU, Manzhen SHI. Research on the impact of digital economy on enterprise total factor productivity[J]. Contemporary Finance and Economics,2023(12):17-29. (in Chinese)
[4] Lin XU, Linqi HOU, Guangbin CHENG. Research on the Innovation Effect of State-level Big Data Comprehensive Pilot Zone[J]. Science and Technology Progress and Countermeasures,2022,39(20):101-111.
[5] Lili WEI, Hongyan XIU, Yuqi HOU. Research on the impact of digital economy on the ecologization of urban industry — a quasi-natural experiment based on the establishment of national-level big data comprehensive pilot zone[J]. Urban Issues,2022(11):34-42. (in Chinese)
[6] Haoliang CHANG, Bei JIN, Fei XUE. Impact of big data strategy on carbon emissions from electricity consumption — a quasi-natural experiment based on a national-level big data comprehensive pilot zone[J]. Economic and Management Research,2023,44(05):93-109. (in Chinese)
[7] Yihao Zhang, Xiaohui Guo. Big data development and enterprise total factor productivity--an empirical analysis based on the national-level big data comprehensive pilot zone[J]. Industrial Economics Research,2023(02):69-82. (in Chinese)
[8] Yutang Shi, Xiaodan Wang. Can the Establishment of Comprehensive Big Data Pilot Zone Drive Digital Transformation of Enterprises? — An empirical study based on a quasi-natural experiment[J/OL]. Research in Science:1-18. (in Chinese)
[9] Chernozhukov V, Chetverikov D, Demirer M, et al. Double/debiased machine learning for treatment and structural parameters [J]. The Econometrics Journal, 2018, 21(1):C1-C68.
[10] Ting Jiang. Mediating and moderating effects in empirical studies of causal inference[J]. China Industrial Economy,2022(05):100-120. (in Chinese)
[2] Xicang Zhao, Liang Xu, Yusen Luo. Does Intellectual Property Protection Enhance Total Factor Productivity of Enterprises? — Evidence from Chinese A-share Listed Companies[J]. Journal of Jiangsu University (Social Science Edition),2023,25(06):68-83. (in Chinese)
[3] Delong HU, Manzhen SHI. Research on the impact of digital economy on enterprise total factor productivity[J]. Contemporary Finance and Economics,2023(12):17-29. (in Chinese)
[4] Lin XU, Linqi HOU, Guangbin CHENG. Research on the Innovation Effect of State-level Big Data Comprehensive Pilot Zone[J]. Science and Technology Progress and Countermeasures,2022,39(20):101-111.
[5] Lili WEI, Hongyan XIU, Yuqi HOU. Research on the impact of digital economy on the ecologization of urban industry — a quasi-natural experiment based on the establishment of national-level big data comprehensive pilot zone[J]. Urban Issues,2022(11):34-42. (in Chinese)
[6] Haoliang CHANG, Bei JIN, Fei XUE. Impact of big data strategy on carbon emissions from electricity consumption — a quasi-natural experiment based on a national-level big data comprehensive pilot zone[J]. Economic and Management Research,2023,44(05):93-109. (in Chinese)
[7] Yihao Zhang, Xiaohui Guo. Big data development and enterprise total factor productivity--an empirical analysis based on the national-level big data comprehensive pilot zone[J]. Industrial Economics Research,2023(02):69-82. (in Chinese)
[8] Yutang Shi, Xiaodan Wang. Can the Establishment of Comprehensive Big Data Pilot Zone Drive Digital Transformation of Enterprises? — An empirical study based on a quasi-natural experiment[J/OL]. Research in Science:1-18. (in Chinese)
[9] Chernozhukov V, Chetverikov D, Demirer M, et al. Double/debiased machine learning for treatment and structural parameters [J]. The Econometrics Journal, 2018, 21(1):C1-C68.
[10] Ting Jiang. Mediating and moderating effects in empirical studies of causal inference[J]. China Industrial Economy,2022(05):100-120. (in Chinese)
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