Sport Management Journal

The Model of Reconstructing Organizational Paradigms in Sports Clubs Based on Artificial Intelligence

Articles in Press

Document Type : Research Paper

Authors

Farahnaz Shams 1
Naser Gholami 2

1 Department of Physical Education, Farhangian University, Iran, Isfahan

2 Department Of physical Education; Farhangian University, Iran, Tehran

https://doi.org/10.22059/jsm.2025.391827.3457
Abstract
Introduction: The purpose of this study was to develop a model for reconstructing organizational paradigms in sports clubs through artificial intelligence (AI), utilizing the grounded theory approach.

Methodology: This research was exploratory in terms of its objective and qualitative in terms of its strategy. It employed the grounded theory method based on Strauss and Corbin’s approach. The researcher conducted semi-structured interviews with current and former managers and deputies of sports clubs across the country. Data were collected using purposive sampling and the snowball sampling technique until theoretical saturation was achieved. Data triangulation was applied to ensure robustness.

Findings: The coding process yielded 88 concepts in open coding, 25 subcategories in axial coding, and five main categories (causal conditions, intervening conditions, contextual conditions, strategies, and consequences) in selective coding, which were integrated into the final research model.

Conclusion: The adoption of AI in sports clubs is significantly influenced by environmental, managerial, cultural, and financial factors. By establishing appropriate conditions, providing training, and developing infrastructure, sports clubs can leverage AI’s benefits. This study offers an analytical framework for reconstructing organizational paradigms in sports clubs through AI, enabling them to align logically and systematically with the rapidly growing global use of AI in sports.

Keywords

sports clubs
organizational transformations
grounded theory approach
artificial intelligence
Subjects
Sport Management Journal

Articles in Press, Accepted Manuscript
Available Online from 19 May 2025

  • Receive Date 13 March 2025
  • Revise Date 18 May 2025
  • Accept Date 19 May 2025

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