Journal of Iranian Public Administration Studies

Journal of Iranian Public Administration Studies

Transition to Smart Governance: The Antecedents for Implementing a Smart Budgeting System in the Public Sector

Document Type : Original Article

Authors
Masoud Banafi 1
Mohammad Mahdi Shahbazi 2
1 Assistant Professor, Faculty of Governance, University of Tehran, Tehran, Iran
2 Phd in Entrepreneurship, University of Tehran and researcher at Research and Innovation Company (Knowledge Enterprise), Tehran, Iran.
10.22034/jipas.2025.521762.1803
Abstract
The budgeting system is one of the essential tools for accountability, control, and achieving national goals in governance. In this article emerging transformations and the increasing complexity of public issues have led traditional budgeting methods to lose their effectiveness and efficiency. Therefore, the transition from traditional governance to smart governance, as an institutional and public sector entrepreneurship initiative, holds significant importance. The aim of this research is to identify and prioritize the antecedents for implementing a smart budgeting system in Iran. From a methodological perspective, this study follows a sequential mixed-methods approach (qualitative in the first phase and quantitative in the second phase) and is applied in nature. In the qualitative phase, through thematic analysis and in-depth semi-structured interviews with 10 academic and executive experts, the required antecedents were identified. In the quantitative phase, the identified factors were prioritized using the Best-Worst Method (BWM) based on the opinions of 13 experts. The interviews resulted in 2 overarching themes, 4 organizing themes, and 19 basic themes. The findings from the quantitative phase indicate that the most important antecedents for implementing a smart budgeting system include: “Commitment and determination of senior governance leaders” (under the organizing theme “Cross-organization”), “Software infrastructure” (under the organizing theme “Information Technology”), “Management support (middle management)” (under the organizing theme “Change Management”), and “Access to data” (under the organizing theme “Organizational Resources”).
Keywords
Smart Budgeting
Smart Governance
Artificial Intelligence
Thematic Analysis
Best-Worst Method
اکبری، ایمان، بنافی، مسعود، محمودی، مصطفی، شیردل، میلاد (1402). از بودجه‌ریزی سنتی به بودجه‌ریزی هوشمند: رهنمودهایی برای هوشمندسازی بودجه‌ریزی در نظام حکمرانی. نخستین کنفرانس حکمرانی هوشمند، حکمرانی سرزمینی. دانشکده حکمرانی دانشگاه تهران. تهران.
باباجانی، جعفر (1387). نقش حسابداری و حسابرسی در استقرار نظام بودجه‌ریزی عملیاتی، مقاله ارائه شده در دومین کنفرانس بین‌‌المللی بودجه‌ریزی عملیاتی. تهران.
بنافی، مسعود (1402).  آسیب‌شناسی خط‌مشی‌های نخبگانی: واکاوی موانع جذب استعدادهای برتر در بخش دولتی ایران. مطالعات مدیریت دولتی ایران. سال 6، شماره 4. 176-149.
بنافی، مسعود، قرشی، سیدمجتبی (1399). نقش ابزارهای نرم در ایجاد پیامدهای سخت در حکمرانی: پیوندی بین خط‌مشی‌گذاری و حقوق (مورد مطالعه: شاخص قاچاق انسان). مطالعات مدیریت دولتی ایران. سال 3، شماره 4. 152-127.
حاجی‌زاده، مریم، حاجی‌زاده، مائده (1401). روند تحول روش‌های بودجه‌ریزی و عوامل موثر بر آن در ایران. مقاله ارائه شده در هفتمین همایش ملی پژوهش‌های نوین در مدیریت، اقتصاد و حسابداری ایران.
ربیعی، محدثه، مقیمی، سیدمحمد، عباسی، طیبه (1401). بررسی چالش‌ها و ارائه راهکار برای بهبود اثربخشی نظام پیش‌بینی منابع در نظام بودجه‌ریزی دولتی ایران. مدیریت دولتی. 15 (4)، 646-665.
زمانی، رضا (1398). نظام بودجه‌ریزی از انقلاب مشروطه تا کنون: مبتنی بر هویت قائم به شخص و دارای تعادل سیاسی (اما ناکارا) به همراه عدم تعادل‌های اقتصادی و حقوقی. فصلنامه راهبرد اقتصادی. 6 (22)، 105-136.
فرج‌وند، اسفندیار (1377). فراگرد تنظیم تا کنترل بودجه، تبریز، انتشارات احرار، چاپ اول.
فرزیب، علیرضا (1377). بودجه‌ریزی دولتی در ایران، تهران، انتشارات مرکز آموزش مدیریت دولتی، چاپ ششم.
هرندی، عطاءاله، هادی‌زاده، مرتضی (1403). بودجه‌‎بندی کارآمد در دولت مبتنی بر هوش مصنوعی در آیندة ایران: سناریوها، سیاست‏‌ها و اقدامات. پژوهش‌های برنامه و توسعه. سال 5، شماره 1. 147-115.
Akbari, I., Banafi, M., Mahmoudi, M., & Shirdel, M. (2023). From traditional budgeting to smart budgeting: Guidelines for smartening the budgeting system in governance. In 1st Conference on Smart Governance and Territorial Governance, Faculty of Governance, University of Tehran, Tehran, 102-126. (in Persian)
Anastasopoulos, L. J., Moldogaziev, T. T., & Scott, T. (2020). Organizational context and budget orientations: A computational text analysis. International Public Management
Journal, 23(2), 292–313.
 Attride-Stirling, J. (2001). Thematic networks: an analytic tool for qualitative research. Qualitative research, 1(3), 385-405.
Azar A, Khadivar A. (2012). A Neural Network Model for Activity-Cost Relationship Estimation in Performance-based Budgeting. JPBUD. 17(2), 7-38.
Babajani, J. (2008). The role of accounting and auditing in establishing a performance-based budgeting system. Paper presented at the 2nd International Conference on Performance-Based Budgeting. (in Persian)
Banafi, M. (2024). Investigating Elite Policies: Analysis of Obstacles to Attract Top Talents in Iran's Public Sector. Journal of Iranian Public Administration Studeis. 6(4). 149-176. (in Persian)
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. (in Persian)
Björklund, M., & Hegethorn, C. H. (2023). Pre-Implementing Smart Budgeting: An exploration into AI-supported budgeting. Access at: https://www.divaportal.org/smash/record.jsf?pid=diva2%3A1766588&dswid=-8985.
Buchanan, J. M. (2014). Public finance in democratic process: Fiscal institutions and individual choice. UNC Press Books.
Capone, C., Talgat, S., Hazir, O., Abdrasheva, K., & Kozhakhmetova, A. (2024). Artificial Intelligence Models for Predicting Budget Expenditures. Eurasian Journal of Economic and Business Studies, 68(1), 32-43.
Christou, P. A. (2022). How to use thematic analysis in qualitative research. Journal of Qualitative Research in Tourism, 3(2), 79-95.
Clarke, V., & Braun, V. (2017). Thematic analysis. The journal of positive psychology, 12(3), 297-298.
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.
Dobrescu, E. (2015). BARS curve in Romanian economy. Amfteatru Economic, 17(39), 693–705.
Drury, C., Management and Cost Accounting. 2008, London: South-western.
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., ... & Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International journal of information management, 57, 101994, 1-47.
Farajvand, E. (1998). The process of budget formulation and control (1st ed.). Tabriz: Ahrar Publications. (in Persian)
Farzib, A. (1998). Public budgeting in Iran (6th ed.). Tehran: State Management Training Center Publications. (in Persian)
Fernandez-Cortez, V., Valle-Cruz, D., & Gil-Garcia, J. R. (2020). Can artifcial intelligence help optimize the public budgeting process? Lessons about smartness and public value from the Mexican Federal Government. In 2020 Seventh international conference on EDemocracy & EGovernment (ICEDEG), 312–315.
Fotache, G., & Bucsa, R. C. (2024). The Integration of Artificial Intelligence in Managerial Accounting: A Literature Review. Economy Transdisciplinarity Cognition, 27(1), 5-15.
Gil-Garcia, J. R., Helbig, N., & Ojo, A. (2014). Being smart: Emerging technologies and innovation in the public sector. Government Information Quarterly, 31(S1), 11-18.
Gordon, L. A., & Sellers, F. E. (1984). Accounting and budgeting systems: The issue of congruency. Journal of Accounting and Public Policy, 3(4), 259-292.
Hajizadeh, M., & Hajizadeh, M. (2022). The evolution of budgeting methods and its influencing factors in Iran. Paper presented at the 7th National Conference on New Research in Management, Economics, and Accounting of Iran. (in Persian)
Harandi, A., & Hadizadeh, M. (2024). Efficient budgeting in an AI-based government in the future of Iran: Scenarios, policies, and actions. Program and Development Research, 5(1), 115–147. (in Persian)
Haseli, G., Sheikh, R., Wang, J., Tomaskova, H., & Tirkolaee, E. B. (2021). A novel approach for group decision making based on the best–worst method (G-bwm): Application to supply chain management. Mathematics, 9(16), 1881, 1-20.
Hope, J., & Fraser, R. (2003). Beyond budgeting: how managers can break free from the annual performance trap. Harvard Business Press.
Joyce, P. G. (2008). Does more (or even better) information lead to better budgeting? A new perspective. Journal of Policy Analysis and Management, 27(4), 945-960.
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.
Lohan, G. (2013). A brief history of budgeting: reflections on beyond budgeting, its link to performance management and its appropriateness for software development. In International Conference on Lean Enterprise Software and Systems (pp. 81-105). Berlin, Heidelberg: Springer Berlin Heidelberg.
Mintrom, M., Maurya, D., & Jingwei He, A. (2020). Policy entrepreneurship in Asia: the emerging research agenda. Journal of Asian Public Policy, 13(1), 1-17.
Mullen, P. R. (2006). Performance‐based budgeting: The contribution of the program assessment rating tool. Public Budgeting & Finance, 26(4), 79-88.
Puron-Cid, G. (2014). Factors for a successful adoption of budgetary transparency innovations: A questionnaire report of an open government initiative in Mexico. Government Information Quarterly, 31. 49-62.
Rabiei, M., Moghimi, S. M., & Abbasi, T. (2022). Investigating challenges and providing solutions to improve the effectiveness of the revenue forecasting system in Iran's public budgeting. Public Management, 15(4), 646–665. (in Persian)
Raibagi, K. (2020). Use of algorithmic decision making & AI in public organisations. AIM
Sánchez, M. A., & Zuntini, J. I. (2019). Digital readiness in government: the case of Bahía Blanca municipal government. International Journal of Electronic Governance, 11(2), 155-181.
Sastry, S., & King, S. (2005). Competing for funds in austere times: how to win with performance-based budgeting. The Journal of Government Financial Management, 54(4), 33-36.
Sgueo, G. (2015). Electornic Budgeting. Innovative Approaches to Budgeting. Innovative Approaches to Budgeting (November 27, 2015). European Parliamentary Research Service.
Szablics, B. (2019). Smart budget concept. Economic Alternatives, (1), 135-148.
Treija, S., Bratuškins, U., Koroļova, A., & Lektauers, A. (2021). Smart Governance: An Investigation into Participatory Budgeting Models. Environmental Sciences Proceedings, 11(1), 30,1-7.
Valle-Cruz, D. (2019). Public value of e-government services through emerging technologies. International Journal of Public Sector Management, 32(5), 530-545.
Valle-Cruz, D., Alejandro Ruvalcaba-Gomez, E., Sandoval-Almazan, R., & Ignacio Criado, J. (2019). A review of artificial intelligence in government and its potential from a public policy perspective. In Proceedings of the 20th annual international conference on digital government research, 91-99.
Valle-Cruz, D., Criado, J. I., Sandoval-Almazán, R., & Ruvalcaba-Gomez, E. A. (2020). Assessing the public policy-cycle framework in the age of artificial intelligence: From agenda-setting to policy evaluation. Government information quarterly, 37(4), 101509.
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.
Wirtz, B. W., Weyerer, J. C., & Sturm, B. J. (2020). The dark sides of artificial intelligence: An integrated AI governance framework for public administration. International Journal of Public Administration, 43(9), 818–829.
Zamani, R. (2019). The budgeting system from the Constitutional Revolution to the present: Identity-based, politically balanced (yet inefficient), with economic and legal imbalances. Strategic Economic Policy Journal, 6(22), 105–136. (in Persian)
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.

  • Receive Date 30 August 2024
  • Revise Date 08 November 2024
  • Accept Date 21 November 2024