Studies in Public Service Administration

The Application of Big Data in Iran’s Public Budgeting System: An Analysis of Challenges, Strategies, and Opportunities

Document Type : Original Article

Authors

Afsaneh Dehghanpour-Farashah 1
Pouyan Pouyanfar 2
Masoud Banafi 1

1 Assistant Professor, Faculty of Governance, College of Management, University of Tehran, Tehran, Iran.

2 Master’s Degree in Public Administration, University of Tehran, Tehran, Iran

https://doi.org/10.22054/spsa.2026.91411.1127
Abstract
Public budgeting is widely recognized as a primary instrument of fiscal and economic policymaking. The integration of big data can create new capacities within budgeting systems by enhancing transparency, improving forecasting accuracy, strengthening accountability, and optimizing resource allocation processes. Existing studies have identified general trends in the application of big data in budgeting systems; however, they have not comprehensively examined the challenges, opportunities, and policy guidelines related to its implementation within policymaking systems. Accordingly, this study aims to identify the challenges, solutions, and opportunities associated with the use of big data in Iran’s public budgeting system. The research adopts a qualitative approach using thematic analysis. The study population consisted of experts in public budgeting, who were selected through purposive and snowball sampling techniques. Data were collected through semi‑structured interviews, and theoretical saturation was achieved after the fifteenth interview. The collected data were organized and analyzed according to the stages of thematic analysis.
The analysis resulted in the identification of 24 main themes that explain the various dimensions of challenges, strategies for overcoming these challenges, and opportunities arising from the application of big data in Iran’s public budgeting system. The findings provide a scientific basis for policymakers and public sector managers seeking to reform budgeting processes through data‑driven approaches and to enhance financial transparency and accountability.

Keywords

Big data
Public budgeting
Challenges and opportunities
Thematic analysis
Data driven budgeting
Data driven governance
  1. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative research in psychology, 3(2), 77-101. https://doi.org/10.1191/1478088706qp063oa
  2. Cockcroft, S., & Russell, M. (2018). Big data opportunities for accounting and finance practice and research. Australian Accounting Review, 28(3), 323-333. https://doi.org/10.1111/auar.12218
  3. Davies, J., Arana-Catania, M., Procter, R., Van Lier, F. A., & He, Y. (2021). Evaluating the application of NLP tools in mainstream participatory budgeting processes in Scotland. ACM International Conference Proceeding Series, 362–366. https://doi.org/10.1145/3494193.3494242
  4. Desouza, K. C., & Jacob, B. (2017). Big data in the public sector: Lessons for practitioners and scholars, Administration & society, 49(7), 1043-1064. https://doi.org/10.1177/0095399714555751
  5. Gamage, P. (2016). New development: Leveraging ‘big data’analytics in the public sector. Public Money & Management, 36(5), 385-390. https://doi.org/10.1080/09540962.2016.1194087
  6. Green, S., McKinney Jr, E., Heppard, K., & Garcia, L. (2018). Big data, digital demand and decision-making. International Journal of Accounting & Information Management, 26(4), 541-555. https://doi.org/10.1108/IJAIM-02-2017-0019
  7. Guba, G. & Lincoln, Y. S. (1994). Competing paradigms in qualitative research. In Handbook of qualitative research, 2(163 -194), 105.
  8. Höchtl, J., Parycek, P., & Schöllhammer, (2016). Big data in the policy cycle: Policy decision making in the digital era. Journal of Organizational Computing and Electronic Commerce, 26(1-2), 147-169. https://doi.org/10.1080/10919392.2015.1125187
  9. Hollands, F. M., Shand, R., Yan, B., Leach, S. M., Dossett, D., Chang, F., & Pan, Y. (2024). A comparison of three methods for providing local evidence to inform school and district budget decisions. Leadership and Policy in Schools, 23(2), 296-330. https://doi.org/10.1080/15700763.2022.2131581
  10. Kheyfets, I., Mastruzzi, M., Merotto, D., & Sondergaard, L. (2011). A New Data Tool to BOOST Public Spending Efficiency.
  11. Li, C., Xu, Y., Zheng, H., Wang, Z., Han, H., & Zeng, L. (2023). Artificial intelligence, resource reallocation, and corporate innovation efficiency: Evidence from China’s listed companies. Resources Policy, 81, 103324. https://doi.org/10.1016/j.resourpol.2023.103324
  12. Moradi, T., Kabir, M. J., Pourasghari, H., Ehsanzadeh, S. J., & Aryankhesal, A. (2023). Challenges of budgeting and Public Financial Management in Iran’s health system: a qualitative study. Medical Journal of the Islamic Republic of Iran, 37, 80. https://doi.org/10.47176/mjiri.37.80
  13. Nagirikandalage, P., Binsardi, A., & Kooli, K. (2025). The role of big data in public sector accounting and budgeting practices: evidence from a pandemic environment of an emerging economy. International Journal of Accounting, Auditing and Performance Evaluation, 21(1-2), 229-258. https://doi.org/10.1504/IJAAPE.2025.144894
  14. Saunders, M. N. (2011). Research methods for business students, 5/e. Pearson Education India.
  15. Valle-Cruz, D., Fernandez-Cortez, V., & Gil-Garcia, J. R. (2022). From E-budgeting to smart budgeting: Exploring the potential of artificial intelligence in government decision-making for resource allocation. Government Information Quarterly, 39(2), 101644. https://doi.org/10.1016/j.giq.2021.101644
  16. Warren, J. D., Moffitt, K. C., & Byrnes, P. (2015). How big data will change accounting, Accounting horizons, 29(2), 397-407. https://doi.org/10.2308/acch-51069
  17. Zhang, J., Rardin, R. L., & Chimka, J. R. (2023). Budget constrained model selection for multiple linear regression. Communications in Statistics-Simulation and Computation, 52(11), 5537-5549. https://doi.org/10.1080/03610918.2021.1991956
  18. Zhyber, T., Pyslytsya, A., Zavystovska, H., Tymchenko, O., & Shchur, R. (2024). Data-Driven Public Budgeting: Business Management Approach and Analytics Methods Algorithmization. In Data-Centric Business and Applications: Modern Trends in Financial and Innovation Data Processes 2023. Volume 2 (pp. 89-124). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-53984-8_5
  19. Arabsarmazdi, M., & Moradi, A. (2020). Opportunities and challenges of big data application in public sector accounting information systems from an accountability perspective, Auditing Knowledge, 20(79), 95–122. [In Persian]
  20. Azar, A. & Amirkhani, T. (2017). Black Hole of Budgeting in Public Budgeting System of Iran. Journal of Public Administration, 8(4), 571-590. doi: 10.22059/jipa.2017.62177 [In Persian]
  21. Banafi, M., & Shahbazi, M.M. (2025). Transition to Smart Governance: The Antecedents for Implementing a Smart Budgeting System in the Public Sector, Journal of Iranian Public Administration Studies. 7(4). 159-193. doi:10.22034/jipas.2025.521762.1803[In Persian]
  22. Banafi, M., & Ghorashi, S. M. (2020). The Role of Soft Instruments in Creating Hard Consequences in Governance: A Link between Public Policy and Law Case Study: Trafficking in Person Report, Journal of Iranian Public Administration Studies, 3(4), 127–152. doi: 10.22034/jipas.2021.314720.1286. [In Persian]
  23. Dehghanpour Farashah,A. and Dehghanpour Farashah,A. (2024). Analyzing the Ethical and Policy Considerations of Data-Driven Governance. Strategic Studies of public policy, 14(51), 104-124. https://doi.org/10.22034/sspp.2024.2025254.3587 [In Persian]
  24. Dehghanpour Farashah, A., Abbasi, T., & Dehghanpour Farashah, A. (2023). Identifying and Prioritizing the Barriers of Public Accountability in Iranian Public Organizations. Journal of Iranian Public Administration Studies, 6(3), 97-123. doi:10.22034/jipas.2022.322195.1322[In Persian]
  25. Hadad M, salehi aba S. (2024). New Opportunities and Challenges of Smart Government Budgeting In the age of Artificial Intelligence. JEPR. 29(3), 143-169. doi:61882/jepr.29.3.143[In Persian]
  26. Helili, K., & Valavi, M. R. (2017). Big data technology: Opportunities, challenges, and strategies. Interdisciplinary Studies of Strategic Knowledge, 7(28), 7–28.
  27. Noobari, F. (2022). The absence of a systemic perspective in macro-level budget formulation. Economic Security, 10(3), 19–26. [In Persian]
  28. Saedi, A., & Asadi, N. (2025). Analyzing and evaluating the consequences of big data sovereignty in human resource management. Journal of Public Organizations Management, 13(1, Serial No. 49), 109–122. https://doi.org/10.30473/ipom.2025.72310.5036[In Persian]
  29. The Islamic Republic News Agency. (2025). Implementation of the first version of the integrated government financial information platform: Emphasis on digital governance. Retrieved from https://www.irna.ir[In Persian]

 

Studies in Public Service Administration
Volume 3, Issue 10
Spring 2026
Pages 45-90

  • Receive Date 11 February 2026
  • Revise Date 15 April 2026
  • Accept Date 23 April 2026

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