A Financial Management Maturity Model in Sports Organizations: A Novel Approach Using Artificial Intelligence

Document Type : Original Article

Authors

1 Ph.D Candidate in Sports Management, Faculty of Sports Sciences, Isfahan Branch (Khorasgan), Islamic Azad University, Isfahan, Iran.

2 Faculty of Sports Sciences, Isfahan University, Isfahan, Iran

3 PhD in Sport Management, Lecturer of Faculty of Physical Education and Sport Sciences, Isfahan Branch, Islamic Azad University, Isfahan, Iran.

Abstract

This paper deals with the development of a financial management maturity model for sports organizations based on artificial intelligence. We jointly consider enhancing financial transparency, oversight and control, risk management, and using advanced technologies in sports organizations. The proposed scheme relies on a constructivist grounded theory approach. The research process involved data collection through in-depth interviews with five AI language models, ChatGPT, Claude, Google Gemini, Mistral, and LLaMA. In addition, these models were utilized as an alternative to traditional experts. Finally, extensive simulations were conducted to validate that 209 initial codes were identified, which were then refined to 44 codes and eventually consolidated into 11 key themes. These themes include financial transparency, oversight and control, budget planning, risk management, and the use of advanced technologies. Numerical results show the efficiency that these themes are interlinked in a chain-like manner and contribute to enhancing the financial efficiency of sports organizations.

Keywords

Main Subjects

References

Adigwe, C. S., Olaniyi, O. O., Olabanji, S. O., Okunleye, O. J., Mayeke, N. R., & Ajayi, S. A. (2024). Forecasting the future: The interplay of artificial intelligence, innovation, and competitiveness and its effect on the global economy. Asian journal of economics, business and accounting, 24(4), 126-146. https://doi.org/https://doi.org/10.9734/ajeba/2024/v24i41269
Akhtar, M., & Moridpour, S. (2021). A review of traffic congestion prediction using artificial intelligence. Journal of Advanced Transportation, 2021(1), 8878011. https://doi.org/https://doi.org/10.1155/2021/8878011
Algherairy, A., & Ahmed, M. (2025). Prompting large language models for user simulation in task-oriented dialogue systems. Computer Speech & Language, 89, 101697. https://doi.org/https://doi.org/10.1016/j.csl.2024.101697
AlZu'bi, S., Mughaid, A., Quiam, F., & Hendawi, S. (2024). Exploring the capabilities and limitations of chatgpt and alternative big language models. Artificial Intelligence and Applications, 2(1), 28-37. https://doi.org/https://doi.org/10.47852/bonviewAIA3202820
Amoz, N. (2024). what-is-a-large-language-model (Vol. 1)  https://doi.org/https://nikamooz.com/what-is-a-large-language-model/
Anney, V. N. (2014). Ensuring the quality of the findings of qualitative research: Looking at trustworthiness criteria. https://repository.udsm.ac.tz/server/api/core/bitstreams/cead7c8d-1b27-4a88-809f-3a82a3cbf575/content
Becker, D. M., Solberg, H. A., & Heyerdahl, G. S. (2023). The financial challenges of hosting sports events: a problem of insufficient separation between decision-making and decision-control. European Sport Management Quarterly, 23(5), 1549-1566.
Charmaz, K. (2014). Constructing grounded theory. In: sage.
Chun Tie, Y., Birks, M., & Francis, K. (2019). Grounded theory research: A design framework for novice researchers. SAGE open medicine, 7, 2050312118822927. https://doi.org/https://doi.org/10.1177/2050312118822927
Cong, Y. (2025). Demystifying large language models in second language development research. Computer Speech & Language, 89, 101700. https://doi.org/https://doi.org/10.1016/j.csl.2024.101700
Dastoom, s., ramzani nezhad, r., & sadeghi borujerdi, s. (2023). Designing the evaluation framework of Knowledge-based economy in Iranian sports and analysis of the development gap based on it. Sport Management Studies, 110-125(persian). https://doi.org/https://doi.org/10.22089/smrj.2020.9137.3095
Ghafouri, M., Alidoust, E., Khabiri, M., & Sajjadi, N. (2021). Identifying Financing Barriers in Iran's Professional Sports. Sport Physiology & Management Investigations, 13(2), 71-91. https://doi.org/https://dorl.net/dor/20.1001.1.1735.5354.1400.13.2.5.8.677
Goudarzi, M. (2017). Determine The exploratory model of financial management in sports federations. Applied Research in Sport Management, 6(2), 67-79(Persian). https://doi.org/20.1001.1.23455551.1396.6.2.6.0
Grilli, L., & Pedota, M. (2024). Creativity and artificial intelligence: A multilevel perspective. Creativity and Innovation Management, 33(2), 234-247. https://doi.org/https://doi.org/10.1111/caim.12580
Guangyu, H., Qin, Lian. (2024). The Battle of LLMs: A Comparative Study in Conversational QA Tasks
 Illinois Institute of Technology, 1(2), 1-13. https://doi.org/10.21203/rs.3.rs-4376810/v1
Husein, R. A., Aburajouh, H., & Catal, C. (2024). Large Language Models for Code Completion: A Systematic Literature Review. Computer Standards & Interfaces, 103917. https://doi.org/https://doi.org/10.1016/j.csi.2024.103917
Jalilvand, A., & Moorthy, S. (2024). Enterprise Risk Management Maturity: A Clinical Study of a US Multinational Nonprofit Firm. Journal of Accounting, Auditing & Finance, 39(3), 883-902.
Jia, N., Luo, X., Fang, Z., & Liao, C. (2024). When and how artificial intelligence augments employee creativity. Academy of Management Journal, 67(1), 5-32.
Kamyab, S., Soltanhoseini, M., & Rahimi Sereshbaderani, G. (2023). Methods of financing sports clubs during international sports sanctions. Sport Management Studies, 15(79), 105-124. https://doi.org/https://doi.org/10.22089/smrj.2022.11125.3463
Kirk, H. R., Vidgen, B., Röttger, P., & Hale, S. A. (2024). The benefits, risks, and bounds of personalizing the alignment of large language models to individuals. Nature Machine Intelligence, 1-10. https://doi.org/https://doi.org/10.1038/s42256-024-00820-y
Kucińska-Landwójtowicz, A., Czabak-Górska, I. D., Domingues, P., Sampaio, P., & Ferradaz de Carvalho, C. (2024). Organizational maturity models: the leading research fields and opportunities for further studies. International Journal of Quality & Reliability Management, 41(1), 60-83. https://www.emerald.com/insight/0265-671X.htm
Melina, G., Panton, A. J., Pizzinelli, C., Rockall, E., & Tavares, M. M. (2024). Gen-AI: Artificial Intelligence and the Future of Work. International Monetary Fund, 979, 1-37. https://assolavoro.eu/wp-content/uploads/2024/04/Gen-AI_Artificial-Intelligence-and-the-Future-of-Work.pdf
Mulugeta, B., Williamson, S., Monks, R., Hack, T., & Beaver, K. (2017). Cancer through black eyes views of UK-based black men towards cancer: A constructivist grounded theory study. European Journal of Oncology Nursing, 29, 8-16.
Pavlík, M., & Vaceková, G. (2013). Financial Management of Sports Clubs in the Czech Republic. Ekonomika a management, 30-39.
Rahmani, A., Mollanazari, M., Faal Ghayoumi, A., Mahmoudkhani, M., Behbahaninia, P. S., Parsaei, M., Ghadirian Arani, M. H., & Khadivar, A. (2022). Design of the Financial Management and Accounting Maturity Model for Public Sector Entities. Accounting and Auditing Review, 29(2), 287-310. https://doi.org/https://doi.org/10.22059/ACCTGREV.2022.337562.1008645
Razawi, M., & Freydoni, M. (2023). Economic policy model of Iranian football clubs. Sport Management Studies. https://doi.org/https://doi.org/10.22089/smrj.2021.9604.3226
Rehan, H. (2024). Revolutionizing America's Cloud Computing the Pivotal Role of AI in Driving Innovation and Security. Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023, 2(1), 239-240. https://doi.org/https://doi.org/10.60087/jaigs.v2i1.110
Rezasoltani, N., Moharramzadeh, M., Azizian Kohan, N., & Naghizadeh Baghi, A. (2024). A Meta-Narrative Review of Isomorphism in Sport Organizations. Journal of New Studies in Sport Management, 5(3), 1199-1212. https://doi.org/10.22103/jnssm.2024.22689.1249
Shemetev, A., & Pelucha, M. (2022). POTENTIALLY FRAUDULENT REPORTING IS NOT A PROBLEM: TRACKING THE ACTUAL FINANCIAL STATE OF AFFAIRS AND RISKS IN BIG COMPANIES BY ARTIFICIAL INTELLIGENCE. International Days of Science, 7, 70. https://doi.org/ISBN 978-80-7455-100-0
online
Simion, A. (2022). ANALYSIS AND EVALUATION OF FINANCIAL MANAGEMENT STRATEGIES OF SPORTS CLUBS. Annals of the University of Craiova, Economic Sciences Series, 2(50). https://doi.org/ojs.boulibrary.com
Tabuk, M. E. (2024). A bibliometric analysis of global publications on financial management in sports clubs. SPORT TK-Revista EuroAmericana de Ciencias del Deporte, 13, 43-43. https://doi.org/https://doi.org/10.6018/sportk.491131
Uparkar, S. (2024). IntelliView: An AI Based Mock Interview Platform. Indian Scientific Journal Of Research In Engineering And Management, 8(04), 1-5. https://doi.org/10.55041/ijsrem31356
Wang, L., Ma, C., Feng, X., Zhang, Z., Yang, H., Zhang, J., Chen, Z., Tang, J., Chen, X., & Lin, Y. (2024a). A survey on large language model-based autonomous agents. Frontiers of Computer Science, 18(6), 186345. https://doi.org/https://doi.org/10.1007/s11704-024-40231-1
Wang, L., Ma, C., Feng, X., Zhang, Z., Yang, H., Zhang, J., Chen, Z., Tang, J., Chen, X., & Lin, Y. (2024b). A survey on large language model based autonomous agents. Frontiers of Computer Science, 18(6), 186345. https://doi.org/https://doi.org/10.1007/s11704-024-40231-1
Young, A., Chen, B., Li, C., Huang, C., Zhang, G., Zhang, G., Li, H., Zhu, J., Chen, J., & Chang, J. (2024). Yi: Open foundation models by 01. ai. arXiv preprint arXiv:2403.04652. https://huggingface.co/01-ai
Zhang, J., Zhang, C., Lu, J., & Zhao, Y. (2025). Domain-specific large language models for fault diagnosis of heating, ventilation, and air conditioning systems by labeled-data-supervised fine-tuning. Applied Energy, 377(12437), 8. https://doi.org/https://doi.org/10.1016/j.apenergy.2024.124378
Zhou, E., & Lee, D. (2024). Generative artificial intelligence, human creativity, and art. PNAS nexus, 3(3), pgae052. https://doi.org/https://doi.org/10.1093/pnasnexus/pgae052
Journal of New Studies in Sport Management
Volume 6, Issue 3
August 2025
Pages 100-114

Files

Share

How to cite

Statistics