Welcome to Francis Academic Press

Academic Journal of Business & Management, 2023, 5(2); doi: 10.25236/AJBM.2023.050201.

Research on the influencing factors of digital transformation of manufacturing industry in Jiangxi province

Author(s)

Tang Guoji, Jing Shuo

Corresponding Author:
​Tang Guoji
Affiliation(s)

Gannan Normal University, Faculty of Economics and Management, Ganzhou, Jiangxi, 341000, China

Abstract

Based on the sample data of 11 prefecture-level cities in Jiangxi Province from 2011 to 2020, this paper uses text mining technology to extract the keyword frequency related to digital transformation in government reports to construct the digital transformation index of manufacturing industry. This paper empirically explores the influence of government support and scientific and technological development level on the digital transformation of manufacturing enterprises.The results show that government support and technology development level significantly promote the digital transformation of manufacturing industry.Through the robustness test, the regression results are still consistent. The mechanism analysis finds that the government support and the level of scientific and technological development can promote the digital transformation of manufacturing enterprises by influencing the credit level of financial institutions.

Keywords

Manufacturing; digitization; text mining

Cite This Paper

Tang Guoji, Jing Shuo. Research on the influencing factors of digital transformation of manufacturing industry in Jiangxi province. Academic Journal of Business & Management (2023) Vol. 5, Issue 2: 1-6. https://doi.org/10.25236/AJBM.2023.050201.

References

[1] Wang Xinguang. Does managers' short-sighted behavior hinder the digital transformation of enterprises——Empirical evidence based on text analysis and machine learning[J]. Modern Economic Discussion, 2022(6): 103-113.

[2] WU Fei, CHANG Xi, REN Xiaoyi. Government-driven innovation: fiscal technology expenditure and enterprise digital transformation[J]. Journal of Fiscal Research, 2021(1): 102-115.

[3] JIN Yuchao, SHI Wen, TANG Song, JIN Qinglu. Capital allocation in industrial policy: market forces and government support[J]. Journal of Finance and Economics, 2018, 44(04): 4-19.

[4] Tong Yu. Research on influencing factors of digital transformation of China's manufacturing industry[J]. Research of Technology Economics and Management, 2022(3): 124-128.

[5] Gu Haifeng, Bian Yuchen. Does technology-finance coupling synergy improve corporate financing efficiency?——Based on evidence from 755 technology-based listed companies in China[J]. Statistics & Information Forum, 2020, 35(09): 94-109.

[6] Wen Zhonglin, Ye Baojuan. Mediation effect analysis: method and model development [J]Progress in Psychological Science, 2014, 22 (05): 731-745.

[7] MAO Qilin, XU Jiayun. The impact of government subsidies on new product innovation of enterprises:Based on the perspective of "moderate range" of subsidy intensity[J]. China Industrial Economics, 2015(06): 94-107.

[8] LI Ping, WANG Chunhui. Nonlinear Research on Enterprise Technology Innovation Funded by Government Science and Technology: Threshold Regression Analysis Based on Provincial Panel Data in China from 2001 to 2008[J]. China Soft Science, 2010(08): 138-147.