Research on the Impact of Digital Transformation on Enterprise Investment Efficiency
DOI:
https://doi.org/10.54691/xy92v891Keywords:
Digital Transformation; Investment Efficiency; Over-investment; Under-investment; Financing Constraints; Nature of Property Rights.Abstract
Against the backdrop of the rapid development of the digital economy, enterprise digitalization has become a key approach to improving resource allocation efficiency. However, low investment efficiency remains a major obstacle to achieving high-quality development. Based on sample data of Chinese A-share listed companies from 2008 to 2022, this study constructs an enterprise digitalization index through text mining and uses the Richardson expected investment model to evaluate the issue of low investment efficiency. The study further provides empirical evidence on how digital transformation affects enterprise investment efficiency and the underlying mechanisms through which this effect operates. The empirical results show that digital transformation significantly reduces the phenomenon of low investment efficiency, mainly by curbing over-investment. In the basic model, the mitigating effect of digital transformation on under-investment does not reach statistical significance, but this effect becomes evident when using instrumental variable estimation and longer lag periods. The core mechanism by which digital transformation inhibits over-investment is alleviating financing constraints. For private enterprises, the improvement in investment efficiency brought about by digital transformation is particularly significant. This study confirms how digital transformation optimizes enterprise resource allocation at the enterprise level and provides policy insights for differentially promoting the digital strategies of various types of enterprises and deepening the governance reform of state-owned enterprises.
Downloads
References
[1] Soomro, M. A., & Khan, A. N. (2026). Leadership in times of crisis: Cultivating crisis management through digital transformation and organizational agility. Engineering, Construction and Architectural Management, 33(7), 5400–5417. https://doi.org/10.1108/ECAM-05-2024-0620
[2] Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118–144.
[3] He, F., & Liu, H. X. (2019). Evaluating the performance improvement effect of digital transformation of the real economy from the perspective of the digital economy. Reform, (4), 137–148.
[4] Qin, Y., Cui, Z., Zhang, Y., et al. (2026). How digital and intelligent transformation reshape traditional manufacturing: A study based on the textile and garment industry and the shared intelligent manufacturing model. Industrial Economic Review, (3), 40–53. https://doi.org/10.19313/j.cnki.cn10-1223/f.20260529.001
[5] Bu, X. (2023). Reform and path of financial digital transformation. Bonds, (12), 47–51.
[6] Modigliani, F., & Miller, M. H. (1959). The cost of capital, corporation finance and the theory of investment. American Economic Review, 48(4), 443–453.
[7] Stein, J. C. (n.d.). Agency, information and corporate investment. Social Science Electronic Publishing.
[8] Hu, F. (2025). Digital transformation, external information friction, and enterprise investment performance. Communication of Finance and Accounting, (2), 49–52, 126. https://doi.org/10.16144/j.cnki.issn1002-8072.2025.02.009
[9] Han, Z. X., & Hou, L. (2025). Digital transformation, supply chain spillover, and supplier investment efficiency. Finance and Economy, (3), 36–48. https://doi.org/10.19622/j.cnki.cn36-1005/f.2025.03.004
[10] Jensen, M. C. (1986). Agency costs of free cash flow, corporate finance, and takeovers. The American Economic Review, 76(2), 323–329. https://www.jstor.org/stable/1818789
[11] Xia, Y. Q., & Jia, X. H. (2026). Digital transformation, management agency costs, and enterprise information transparency. Communication of Finance and Accounting, (3), 78–82. https://doi.org/10.16144/j.cnki.issn1002-8072.2026.03.011
[12] Huang, X. H., Zhang, Y. J., & Wang, Y. (2026). Digital cooperation between banks and enterprises and shadow banking activities of non-financial enterprises. Nankai Business Review, 1–46. https://link.cnki.net/urlid/12.1288.f.20260425.1408.002
[13] Fazzari, S. M., Hubbard, R. G., Petersen, B. C., Blinder, A. S., & Poterba, J. (1988). Financing constraints and corporate investment. National Bureau of Economic Research, 19, 141–206.
[14] Alfaro, I., Bloom, N., & Lin, X. (2018). The finance uncertainty multiplier. Social Science Electronic Publishing.
[15] Wang, D., Li, D., & Li, H. (2020). Customer concentration and enterprise investment efficiency. Accounting Research, (1), 110–125.
[16] Richardson, S. (2006). Over-investment of free cash flow. Review of Accounting Studies, 11(2–3), 159–189.
[17] Wu, F., Hu, H. Z., Lin, H. Y., et al. (2021). Enterprise digital transformation and capital market performance: Empirical evidence from stock liquidity. Management World, 37(7), 130–144, 10. https://doi.org/10.19744/j.cnki.11-1235/f.2021.0097
[18] Hadlock, C. J., & Pierce, J. R. (2010). New evidence on measuring financial constraints: Moving beyond the KZ index. Review of Financial Studies, 23(5), 1909–1940.
[19] Wang, Y., Tan, Z., & Zheng, L. K. (2020). Research on the impact of digital inclusive finance on social security. Quantitative Economic Technology and Economic Research, 37(7), 92–112. https://doi.org/10.13653/j.cnki.jqte.2020.07.005
[20] You, X. Y. (2011). Analysis of the impact of administrative factors on equity investment of state-owned enterprises. Communication of Finance and Accounting, (2), 102. https://doi.org/10.16144/j.cnki.issn1002-8072.2011.02.082
[21] Xu, T., & Jiang, X. (2025). Political promotion incentives, equity incentives, and substantive innovation of state-owned enterprises: From the perspective of executives' dual identities. Studies in Science of Science and Management of S.& T., 46(10), 81–101. https://doi.org/10.20201/j.cnki_ssstm.2025.10.004
[22] Stiglitz, J. E., & Weiss, A. (1981). Credit rationing in markets with imperfect information. The American Economic Review, 71(3), 393–410. https://www.jstor.org/stable/1802787
[23] Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36(4), 717–731.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Scientific Journal of Economics and Management Research
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
