Presenting a Framework for Implementing AI‑Based Demand‑Driven Business Intelligence in the Apparel Industry

Document Type : Original Article (Mixed)

Authors

1 Department of Information Technology Management, Tehran Central Branch, Islamic Azad University, Tehran, Iran.

2 Department of Industrial Management, Tehran Central Branch, Islamic Azad University, Tehran, Iran.

Abstract
Abstract
The purpose of this research is to present a model for sustainable financial resource provision in Iran’s sports federations. This research was conducted qualitatively using a data-based theory approach. The statistical population of the research included 17 elites in the field of sports management and sports federation management. A semi-structured interview was used as the data collection tool. The grounded theory method was employed for data collection and analysis. Data analysis was carried out in three stages: open coding, axial coding, and selective coding. MAXQDA software version 24 was used for data analysis. The findings indicated that sustainable financial resource provision in Iran’s sports federations, as the core phenomenon, is shaped by factors such as dependence on government budgets, scarcity of sustainable financial resources, and the pressure of regional and global competitions, all within a context of economic limitations, managerial weaknesses, and infrastructural challenges. Factors such as government policies, the role of media, and organizational capabilities moderate the intensity and direction of these efforts. To overcome these challenges, adopting strategies such as diversifying financial resources, commercializing sports, and strengthening the branding of federations is essential. The successful implementation of these strategies leads to outcomes such as financial independence, infrastructure development, and increased competitiveness of sports federations, ultimately ensuring the sustainable growth of the country’s sports.
Introduction
The strong inclination of society towards sports and the demand for sports goods and services have led the sports industry to experience significant revenue generation and contribute substantially to the economies of nations. This industry, driven by major sporting events, creates opportunities for advertising across various media, thereby establishing the necessary platform for interaction between industry, commerce, and sports (Halkos & Tzeremes, 2013). The macroeconomic impact of sports, such as its contribution to Gross Domestic Product (GDP) and Gross National Product (GNP), as well as its role in job creation, compels countries to accurately and regularly assess sports' economic effects each year (Dimitropoulos & Alexopoulos, 2014). Professional clubs worldwide utilize various methods to secure financial resources and cover expenses, including attracting sponsors for commercial product advertising, player sales, ticket and merchandise sales, and offering ancillary services (Singh et al., 2016). One crucial method for funding sports activities, particularly championship sports, is attracting suitable sponsors by sports organizations and officials. In this regard, creating a healthy and conducive environment for investment by industrialists and the private sector in sports is essential and necessary. Capital owners are interested in establishing sports facilities, providing sports services, producing sportswear and equipment, and organizing profitable competitions because their fundamental goals include achieving global recognition through competitions, offering high-quality services and products, and most importantly, realizing profits through effective marketing (Andreopoulou et al., 2015). The significant presence of the government in professional sports has created challenges for both parties. On one hand, given the severe economic constraints in the country and intervening factors such as oppressive sanctions and threats to people's livelihoods, allocating substantial funds to professional sports is no longer justifiable for the government and the nation as it once was. On the other hand, professional sports, by relying on government and state budgets, has become a dependent phenomenon. Despite the abundant potential for revenue generation, sports clubs in Iran are not only unprofitable for governments and investors but also face fundamental challenges in meeting their own expenses. Therefore, the issue of financial provision, along with the existing tools, methods, and strategies for attracting capital to ensure the dynamic and efficient operation of professional sports, has become more critical than ever. Accordingly, the present research seeks to answer the question: How can a model for sustainable financial resource provision in Iran's sports federations be presented?
Theoretical Framework
Financial Resource Provision
The financial capacity of a profit organization is defined as the ability and potential to develop and deploy financial capital that can be converted into money: revenues, expenses, assets, and liabilities (Hall et al., 2003). From the perspective of sports financing, using the allocation of public resources in the Slovak Republic, according to the study by Kucera & Nemec (2021), four forms of financing can be discussed: assignment taxes; EU budget; budgets of state-owned companies; and budgets of central government, local government, and their parts are used to finance projects that also serve sports activities (indirect public resources).
Maleki et al. (2025) investigated the design of a model for innovative financing in the sports industry, focusing on the role of FinTechs. The research results indicated that the empowering drivers for sports startups are capital attraction through smart FinTech, novel revenue models with data analysis, smart contracts in transfers or sponsorships, and the application of blockchain in financial transparency, which are the five influential factors in this regard. The proposed policy recommendations focus on key influential drivers and include supporting infrastructure such as specialized accelerators in the sports and FinTech domain, access to seed capital, tax exemptions for innovators in the sports industry, and encouraging the use of artificial intelligence in sports data analysis. The results of this research can serve as a basis for policymaking to support sports startups, attract venture capital, and develop the digital sports economy.
Mokhlesi et al. (2024) examined the factors influencing financing in sports clubs and presented a model based on exploratory analysis. They stated that the increasing societal inclination towards sports and the demand for sports goods and services have led the sports industry to experience significant revenue generation and play a substantial role in the economy of any country. The results show that variables such as holding raffles among spectators, dedicated administrative buildings, financial support from fans, attracting foreign investors, ticket pricing in different tiers, advertising club products and services through media, receiving interest income from banks, using their own commercial licenses for business transactions, and dedicated stadiums are of higher importance.
Research Methodology
This research was conducted qualitatively using the grounded theory method. The statistical population of the study included 17 experts in the field of sports management and the management of sports federations. The data collection tool was semi-structured interviews. The grounded theory method was used for data collection and analysis.
Research Findings
Data analysis was performed in three stages: open coding, axial coding, and selective coding. The MAXQDA 24 software was used for data analysis. The findings indicated that the provision of sustainable financial resources in Iran's sports federations, as the core phenomenon, is shaped by factors such as dependence on government budgets, lack of stable financial resources, and the pressure of regional and global competitions; within a context of economic limitations, managerial weaknesses, and infrastructural challenges. Factors such as government policies, the role of media, and organizational capabilities moderate the intensity and direction of these efforts. To overcome these challenges, adopting strategies such as diversifying financial resources, commercializing sports, and strengthening federation branding is essential. The successful implementation of these strategies leads to outcomes such as financial independence, infrastructure development, and increased competitiveness of sports federations, ultimately ensuring the sustainable growth of the country's sports.
Conclusion
The present research was conducted with the aim of providing a model for sustainable financial resource provision in Iran's sports federations. The results of this research are aligned with the findings of Maleki et al. (2025), Mokhlesi et al. (2024), Varmus et al. (2023), Ahmadi (2022), Guevara et al. (2021), and Ghafouri Yazdi et al. (2021). Mokhlesi et al. (2024) stated that the increasing societal inclination towards sports and the demand for sports goods and services have led the sports industry to experience a significant revenue-generating trend, playing a crucial role in any country's economy. The results indicate that variables such as holding lotteries among spectators, having dedicated administrative buildings, fan financial support, attracting foreign investors, ticket pricing in different tiers, advertising club products and services through media, receiving bank deposit interest, using own commercial licenses for business transactions, and having dedicated stadiums are of higher importance.
As the core phenomenon, "The effort to provide sustainable financial resources in Iran's sports federations" is shaped by factors such as dependence on government budgets, lack of stable financial resources, and the pressure of regional and global competitions; within a context of economic limitations, managerial weaknesses, and infrastructural challenges. Factors such as government policies, the role of media, and organizational capabilities moderate the intensity and direction of these efforts. To overcome these challenges, adopting strategies such as diversifying financial resources, commercializing sports, and strengthening federation branding is essential.

Keywords

Subjects

Anderson, R., & Wilson, S. (2017). AI-powered Predictive Analytics in Customer Retention Strategies. Journal of Business Analytics, 14(3), 112-128.
Anitha, S., & Neelakandan, R. (2024). A demand forecasting model leveraging machine learning to decode customer preferences for new fashion products. Complexity, 2024, 1–12. https://www.hindawi.com/journals/complexity/2024/8425058/
Backs, S., & Jahnke, H., & Lüpke, L., & Stücken, M., & Stummer, C. (2021). Traditional versus fast fashion supply chains in the apparel industry: An agent-based simulation approach. Annals of Operations Research, 305(1–2), 487–512. https://doi.org/10.1007/s10479-020-03703-8
Ben, S., & Li, Z., & Wang, J. (2019). Demand-driven business intelligence for customer-centric decision-making. International Journal of Information Management, 47, 178–189. https://doi.org/10.1016/j.ijinfomgt.2019.01.004
Boz, E., & Çizmecioğlu, S., & Çalık, A. (2022). A novel MDCM approach for sustainable supplier selection in healthcare system in the era of logistics 4.0. Sustainability, 14(21), 13839. https://doi.org/10.3390/su142113839
Gartner. A. (2019). Top strategic technology trends for 2019: Empowering the digital workforce. Gartner Research. https://www.gartner.com/en/documents/3888976
Ghanbari Gheshlaghi, Z., & Rezaei, B., & Mohammadifar,Y. (2025). Identifying and prioritizing factors affecting the development of IoT-based businesses. Journal of New Approaches in Management and Marketing, 4(1), 106-126. doi: 10.22034/jnamm.2025.528979.1097. (In Persian).
Gupta, T., & Bansal, S. (2019). The AI advantage: Assessing personalization effects on e-commerce shopping behaviors. International Journal of Science and Research (IJSR), 8(8), 2313–2320. https://www.ijsr.net/abstract.php?paper_id=SR24321084709
Hajipourfard, H., & Soltani, B., & Tolouei Eshlaghi, A., & Tabatabaeian, S. H. (2022). Investigating factors affecting the development of information technology-based businesses in Iran. Journal of value creating in Business Management, 2(1), 49-72. doi: 10.22034/jbme.2022.349737.1031. (In Persian)
Hemati, A. (2024). The role of artificial intelligence in business digital transformation: An analysis of opportunities and challenges. Journal of Business Management Studies, 12(2), 45–62. (In Persian)
Hayatmehr, Z., & Bairamzadeh, S., & jalalzadeh, S. R. (2026). The impact of artificial intelligence and smart learning on strategic thinking and performance with the moderating role of personal morality (Case study: Management students). Management and Educational Perspective, 8(1), 112-134. doi: 10.22034/jmep.2025.499739.1467. (In Persian).
Jain, P., & Aggarwal, K. (2020). Transforming marketing with artificial intelligence. Int. Res. J. Eng. Technol. 7(7), 3964–3976. DOI:10.13140/RG.2.2.25848.67844
Kash, B. A., & Calhoun, J. N. (2019). Leveraging business intelligence for strategic planning in digital transformation. Journal of Business Strategy, 40(6), 25–34. https://doi.org/10.1108/JBS-03-2019-0056
Kash, R., & Calhoun, D. (2010). How companies win: Profiting from demand-driven business models no matter what business you’re in. HarperCollins. https://www.harpercollins.com/products/how-companies-win-richard-kash-david-calhoun
Kunz, M., & Birr, S., & Raslan, M., & Ma, L., & Li, Z., & Januschowski, T. (2023). Deep learning based forecasting: A case study from the online fashion industry. arXiv:2305.14406. https://arxiv.org/abs/2305.14406
Li, Z., & Gong, P., & Wang, Y., & Qu, S. (2024). The impact of digital transformation on enterprise organizational structure. Highlights in Business, Economics and Management, 41, 732–740. https://doi.org/10.54097/qt9jer93
Rahaman, M.M., & Maruri, J., & Begum, M., & Rahman, SM. T. (2025). Optimizing Supply Chain with Artificial Intelligence in Business. American Journal of Environment and Climate 4(3):123-134. DOI:10.54536/ajec.v4i3.5895.
Roth, G. (2024). Artificial intelligence in business platforms. Business Strategy and Digital Transformation Review, 8(1), 15–29.
Skenderi, G., & Joppi, C., & Denitto, M., & Cristani, M. (2021). Well Googled is half done: Multimodal forecasting of new fashion product sales with image-based Google Trends. arXiv. https://doi.org/10.48550/arXiv.2109.09824
Swaminathan, K., & Venkitasubramony, R. (2024). Demand forecasting for fashion products: A systematic review. International Journal of Forecasting, 40(1), 247–267. https://www.sciencedirect.com/science/article/abs/pii/S0169207023000134
Verhoef, P. C., & Broekhuizen, T., & Bart, Y., & Bhattacharya, A., & Dong, J. Q., & Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022
Wamba-Taguimdje, S. L., & Wamba, S. F., & Kamdjoug, J. R. K., & Wanko, C. E. T. (2020). Influence of artificial intelligence (AI) on firm performance: The business value of AI-based transformation projects. Business Process Management Journal, 26(7), 1893–1924. https://doi.org/10.1108/BPMJ-10-2019-0411
Zhou, L., & Naim, M. M., & Disney, S. M. (2017). The impact of product returns and remanufacturing uncertainties on the dynamic performance of a multi-echelon closed-loop supply chain. International Journal of Production Economics, 183, 487–502. https://doi.org/10.1016/j.ijpe.2016.11.020
Zolghadr, A., & Sarmad Saeedi, S., & Ghasemi, B. (2026). Modeling and Validating the Role of Artificial Intelligence in Enhancing the Export Capabilities of Electronics Industry Companies: A Mixed Approach. Journal of value creating in Business Management, 5(4), 252-278. doi: 10.22034/jvcbm.2025.532293.1577. (In Persian).
Volume 5, Issue 1 - Serial Number 12
Spring 2026
Pages 316-344

  • Receive Date 13 April 2026
  • Revise Date 13 May 2026
  • Accept Date 30 May 2026