AI-Enabled Financial Planning, ESG Risk Disclosure, and Firm Value: A Synthetic Panel Data Simulation Approach
Keywords:
AI-enabled financial planning, ESG risk disclosure, Investment efficiency, Tobin’s Q, corporate finance
Abstract
This study aims to replicate a panel data investigation of the connection between ESG risk disclosure and AI financial planning, investment efficiency and firm value. The study has a balanced firm-year sample of 300 firms for 5 years, making a total of 1,500 observations. The main explanatory variable is AI-enabled financial planning, dependent variable is firm value, mediating mechanism is investment efficiency, and moderating factor is ESG risk disclosure. Descriptive statistics, correlation analysis, multicollinearity test and regression models with industry and year effects are used for the analysis. The results suggest that Firm value is positively and significantly impacted by the application of AI in financial planning. Firm value is also positively associated with ESG risk disclosure and with efficiency in investment. Investment efficiency mediates the effect of AI-enabled financial planning on firm value. This implies that AI-based financial systems create value by improving the efficiency of capital allocation. But ESG disclosure does not significantly moderate the relationship between AI planning and firm value. The study adds to the finance and planning literature by bringing together digital financial planning, ESG disclosure and investment efficiency in a single value creation framework
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2.Babina, T., Fedyk, A., He, A., & Hodson, J. (2024). Artificial intelligence, firm growth, and product innovation. Journal of Financial Economics, 151, Article 103745. https://doi.org/10.1016/j.jfineco.2023.103745
3.Biddle, G. C., & Hilary, G. (2006). Accounting quality and firm-level capital investment. The Accounting Review, 81(5), 963–982. https://doi.org/10.2308/accr.2006.81.5.963
4.Biddle, G. C., Hilary, G., & Verdi, R. S. (2009). How does financial reporting quality relate to investment efficiency? Journal of Accounting and Economics, 48(2–3), 112–131. https://doi.org/10.1016/j.jacceco.2009.09.001
5.Borges, A. F. S., Laurindo, F. J. B., Spínola, M. M., Gonçalves, R. F., & Mattos, C. A. (2021). The strategic use of artificial intelligence in the digital era: Systematic literature review and future research directions. International Journal of Information Management, 57, Article 102225. https://doi.org/10.1016/j.ijinfomgt.2020.102225
6.Chen, F., Hope, O.-K., Li, Q., & Wang, X. (2011). Financial reporting quality and investment efficiency of private firms in emerging markets. The Accounting Review, 86(4), 1255–1288. https://doi.org/10.2308/accr-10040
7.Chen, H., Chiang, R. H. L., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165–1188. https://doi.org/10.2307/41703503
8.Cheng, B., Ioannou, I., & Serafeim, G. (2014). Corporate social responsibility and access to finance. Strategic Management Journal, 35(1), 1–23. https://doi.org/10.1002/smj.2131
9.Dhaliwal, D. S., Li, O. Z., Tsang, A., & Yang, Y. G. (2011). Voluntary nonfinancial disclosure and the cost of equity capital: The initiation of corporate social responsibility reporting. The Accounting Review, 86(1), 59–100. https://doi.org/10.2308/accr.00000005
10.Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., Medaglia, R., ... Williams, M. D. (2021). Artificial intelligence: Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, Article 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.004
11.Eccles, R. G., Ioannou, I., & Serafeim, G. (2014). The impact of corporate sustainability on organizational processes and performance. Management Science, 60(11), 2835–2857. https://doi.org/10.1287/mnsc.2014.1984
12.El Ghoul, S., Guedhami, O., Kwok, C. C. Y., & Mishra, D. R. (2011). Does corporate social responsibility affect the cost of capital? Journal of Banking & Finance, 35(9), 2388–2406. https://doi.org/10.1016/j.jbankfin.2011.02.007
13.Enholm, I. M., Papagiannidis, E., Mikalef, P., & Krogstie, J. (2022). Artificial intelligence and business value: A literature review. Information Systems Frontiers, 24(5), 1709–1734. https://doi.org/10.1007/s10796-021-10186-w
14.Fatemi, A., Glaum, M., & Kaiser, S. (2018). ESG performance and firm value: The moderating role of disclosure. Global Finance Journal, 38, 45–64. https://doi.org/10.1016/j.gfj.2017.03.001
15.Flammer, C. (2015). Does corporate social responsibility lead to superior financial performance? A regression discontinuity approach. Management Science, 61(11), 2549–2568. https://doi.org/10.1287/mnsc.2014.2038
16.Friede, G., Busch, T., & Bassen, A. (2015). ESG and financial performance: Aggregated evidence from more than 2000 empirical studies. Journal of Sustainable Finance & Investment, 5(4), 210–233. https://doi.org/10.1080/20430795.2015.1118917
17.Gomariz, M. F. C., & Ballesta, J. P. S. (2014). Financial reporting quality, debt maturity and investment efficiency. Journal of Banking & Finance, 40, 494–506. https://doi.org/10.1016/j.jbankfin.2013.07.013
18.Goodell, J. W., Kumar, S., Lim, W. M., & Pattnaik, D. (2021). Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis. Journal of Behavioral and Experimental Finance, 32, Article 100577. https://doi.org/10.1016/j.jbef.2021.100577
19.Haefner, N., Wincent, J., Parida, V., & Gassmann, O. (2021). Artificial intelligence and innovation management: A review, framework, and research agenda. Technological Forecasting and Social Change, 162, Article 120392. https://doi.org/10.1016/j.techfore.2020.120392
20.Lucas, H. C., Jr., Agarwal, R., Clemons, E. K., El Sawy, O. A., & Weber, B. (2013). Impactful research on transformational information technology: An opportunity to inform new audiences. MIS Quarterly, 37(2), 371–382. https://doi.org/10.25300/MISQ/2013/37.2.03
21.McNichols, M. F., & Stubben, S. R. (2008). Does earnings management affect firms’ investment decisions? The Accounting Review, 83(6), 1571–1603. https://doi.org/10.2308/accr.2008.83.6.1571
22.Mikalef, P., & Gupta, M. (2021). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, 58(3), Article 103434. https://doi.org/10.1016/j.im.2021.103434
23.Richardson, S. (2006). Over-investment of free cash flow. Review of Accounting Studies, 11(2–3), 159–189. https://doi.org/10.1007/s11142-006-9012-1
24.Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J.-F., Dubey, R., & Childe, S. J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356–365. https://doi.org/10.1016/j.jbusres.2016.08.009
Published
2026-07-03
How to Cite
Panda, D. A. (2026). AI-Enabled Financial Planning, ESG Risk Disclosure, and Firm Value: A Synthetic Panel Data Simulation Approach. IJRDO Journal of Economics, Planning and Finance Management, 4(1), 27-53. Retrieved from https://ijepfmjournal.com/article/view/6737
Section
Articles
Copyright (c) 2026 Dr. Amrit Panda
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
