Developing a Model of Factors Predicting Future Cash Flows Using an Interpretive Structural Modeling Approach

Sara  Doost; Abbas Ramezanzadeh Zaidi; Reza  Ziari

Authors

Sara Doost Department of Accounting, Se.C., Islamic Azad University, Semnan, Iran Author https://orcid.org/0009-0008-8214-963X
Abbas Ramezanzadeh Zaidi Department of Accounting, Nek.C., Islamic Azad University, Roudehen, Iran Corresponding author https://orcid.org/0009-0006-8144-3648
Reza Ziari Department of Accounting, Se.C., Islamic Azad University, Semnan, Iran Author https://orcid.org/0009-0004-2315-5539

Keywords:

future cash flow prediction, future cash flows, interpretive structural modeling.

Abstract

This study aimed to develop a model of factors predicting future cash flows using an Interpretive Structural Modeling (ISM) approach. The information required for Interpretive Structural Modeling was collected from 17 experts, including financial managers and accounting managers of companies listed on the Tehran Stock Exchange, all of whom had more than 10 years of professional experience and held master's or doctoral degrees in finance or accounting. In addition, for the quantitative phase, 142 companies were selected from among firms listed on the Tehran Stock Exchange using the systematic elimination sampling technique and were examined over the period from 2014 to 2024. To evaluate the predictive capability of the model, data-mining procedures were implemented using Weka software. The proposed Interpretive Structural Modeling (ISM) model provides a hierarchical framework for analyzing and understanding the complex relationships among factors affecting the prediction of future cash flows. The model categorizes the factors into different levels and represents the direction of their effects through directional arrows. At the top of the structure is the dependent variable, “future cash flow prediction,” which represents the ultimate objective of the analysis. Factors at lower levels include “economic factors” (such as exchange rates and interest rates), “industry environment factors” (such as competition and price fluctuations), and “corporate financial factors” (such as liabilities, earnings quality, capital structure, and working capital management). These factors are positioned at intermediate levels and influence one another as well as factors located at higher levels. Finally, “accounting and managerial factors” (such as corporate governance, internal control systems, and accounting conservatism) are positioned at a higher level than industry environment and corporate financial factors and directly affect the ability to predict future cash flows.

References

[1] A. S. Rantala, "Cash Flow Forecasting: A Dual Perspective on Theoretical Insights and Case Study Findings," Lappeenranta-Lahti University of Technology LUT, 2025.

[2] M. Wouters and F. Stadtherr, "How Management Accountants Purposefully Create Cash Flow Forecasts in Capital Budgeting: A Field Study of Product Development Decisions," Accounting Perspectives, 2024, doi: 10.1111/1911-3838.12361.

[3] S. Nallareddy, M. Sethuraman, and M. Venkatachalam, "Earnings or Cash Flows: Which Is a Better Predictor of Future Cash Flows?," SSRN, 2018. [Online]. Available: https://ssrn.com/abstract=3054644

[4] B. Kimouche, "Properties of Earnings and Cash Flows in Algerian Companies," Modern Management Review, vol. 28, no. 1, 2023, doi: 10.7862/rz.2023.mmr.05.

[5] A. Hajiannezhad, S. R. Hosseini, and S. R. Danesh Sararoudi, "The Predictive Power of Earnings and Cash Flows for Future Cash Flow," Asset Management and Financing, vol. 9, no. 4, pp. 1-26, 2021.

[6] S. Jafarloo and A. Eskandari, "Forecasting Future Cash Flows Based on Operating Cash Flows, Earnings, and Accruals," Accounting and Management Perspective, vol. 6, no. 85, pp. 115-129, 2023.

[7] G. Asadi and S. Azizi Basir, "Examining the Relationship Between Profitability and Liquidity in Companies and Its Effect on Dividend Payout," Management Message, vol. 28, no. 3, pp. 133-155, 2008.

[8] M. A. Aghaei, A. Nezafat, M. Nazemi Ardakani, and A. A. Javan, "Examining Factors Affecting Cash Holdings in Companies Listed on the Tehran Stock Exchange," Financial Accounting Research, vol. 1, no. 1, pp. 53-70, 2009.

[9] G. Bolou, J. Babakhani, and B. Mohseni Maleki, "The Relationship Between Cash Holdings Above and Below the Optimal Level and Future Performance of Companies Listed on the Tehran Stock Exchange," Accounting Knowledge, vol. 11, no. 3, pp. 7-29, 2012.

[10] M. Fischer, "The Source of Financing in Mergers and Acquisitions," The Quarterly Review of Economics and Finance, vol. 65, pp. 227-239, 2017, doi: 10.1016/j.qref.2017.01.003.

[11] A. Karbalaei Karim, Y. Tarivardi, A. Yaghoubi Nejad, and A. Jahanshad, "Designing a Conceptual-Mathematical Model for Predicting Financial Distress Based on Adjusted Cash Flow Statements," Financial Management Strategy, vol. 13, no. 2, 2025.

[12] N. Lehmann, "The Role of Corporate Governance in Shaping Accruals Manipulation Prior to Acquisitions," Accounting and Business Research, vol. 46, no. 4, pp. 327-364, 2016, doi: 10.1080/00014788.2015.1116969.

[13] H. N. Higgins, "Do Stock-for-Stock Merger Acquirers Manage Earnings? Evidence from Japan," Journal of Accounting and Public Policy, vol. 32, no. 1, pp. 44-70, 2013, doi: 10.1016/j.jaccpubpol.2012.10.001.

[14] K. T. Malikov and A. M. Zalataa, "Earnings Management by Acquiring Firms in Cash Mergers," Accounting and Business Research, 2024, doi: 10.1080/00014788.2023.2288567.

[15] M. Ahmadvand, "Examining the Effect of Board Size on the Relationship Between Managerial Myopia and Operating Cash Flow and Stock Price," Accounting and Management Perspective, vol. 7, no. 99, pp. 236-246, 2024.

[16] S. Pornupatham, H. T. Tan, T. Vichitsarawong, and G. S. Yoo, "The Effect of Cash Flow Presentation Method on Investors' Forecast of Future Cash Flows," Management Science, vol. 69, no. 3, pp. 1877-1900, 2023, doi: 10.1287/mnsc.2022.4406.

[17] C. Baum, M. Caglayan, N. Ozkan, and O. Talavera, "The Impact of Macroeconomic Uncertainty on Cash Holdings for Non-Financial Firms," SSRN, 2004. [Online]. Available: https://doi.org/10.2139/ssrn.555952

[18] S. Roy, S. Polley, S. De, C. Gangwal, and C. Mitra, "Harnessing AI and Machine Learning for Improved Cash Flow Forecasting," ed: ResearchGate, 2025.