Issue |
SHS Web Conf.
Volume 216, 2025
International Conference on the Impact of Artificial Intelligence on Traditional Economic Sectors (ICIAITES 2025)
|
|
---|---|---|
Article Number | 02001 | |
Number of page(s) | 12 | |
Section | Artificial Intelligence and Human-Computer Interaction in Sports, Medicine, and Education | |
DOI | https://doi.org/10.1051/shsconf/202521602001 | |
Published online | 23 May 2025 |
Stakeholder Partnerships in AI-Driven Economic Models for Sports Management
1
Professor, Candidate of biological sciences, Department of Sports Management, National University of Uzbekistan,
Uzbekistan
2
Associate Professor, Candidate of technical sciences, Department of Sports Management, National University of Uzbekistan,
Uzbekistan
3
Associate Professor, Department of Sports Management, National University of Uzbekistan,
Uzbekistan
* Corresponding author: saejrasukurova@gmail.com
In this data-driven era, AI-driven economic models have emerged as a possible prescription in the sports management domain. Scholars have noted that artificial intelligence is transforming the decisionmaking process, performance analytics, and the financial sustainability, strategic planning, and operational efficiency of sports organizations across the global sports industry. The paper attempts to move forward research in AI-driven economic models for sports management from theoretical, empirical, and computational contexts to emerging stakeholder partnership frameworks that address current industry challenges. In proposing such a framework, the authors aim to develop Analytical Hierarchy Process (AHP) and regression-based framework that is particularly suited for the iterative evaluation, optimization, and validation of stakeholder partnership in the different decision-support models such as resource allocation strategies and revenue forecasting systems. Additionally, the AHP-based framework is used to organize a hierarchical assessment of stakeholder partnerships to identify some best practices related to specific economic and managerial decisions. This approach then furthers the examination of the strategic and financial implications related to the use of AI-driven models in terms of investment decisions, performance analytics, and stakeholder engagement. In order to practicallly approve feasibility of the framework, A closing case finally examines the application of the framework in a prominent sports club (i.e., a leading football club in Uzbekistan) in context of the AI-driven economic model - stakeholder partnership nexus. Its effect is to increase the economic viability of sports enterprises operating using the AI-driven decision-making framework based on the aforementioned methodological insights.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.