Document Type : Research Paper
Authors
1 Ph. D. Student of Sports Management Department, Karaj Branch, Islamic Azad University, Karaj, Ira
2 Prof. of Sports Management Department, Karaj Branch, Islamic Azad University, Karaj, Iran
3 Associate Professor, Department of Sports Management, Islamic Azad University, Karaj Branch
4 Member of scientific islamic azad university
Abstract
The objective of this research was to explore the strategic forecasting of AI drivers in the sports industry. This research is considered applied and exploratory in terms of its objective and nature, utilizing new methods in futures studies and analytical-exploratory analysis through the use of mutual effects analysis. The statistical population consisted of two parts: informational resources (relevant research articles) and human resources (AI experts, sports industry experts, and university professors). The sampling method employed was purposive in both the informational and human resource sections. In the informational resource section, 18 studies were selected based on inclusion and exclusion criteria, while in the human resource section, 18 individuals were chosen based on four criteria: work experience, educational background (bachelor's, master's, and doctoral degrees), diversity, and collaboration capability. The data collection tools included checklists, questionnaires, and 27x27 dimensional matrices. To assess the validity and reliability of the results, strategies such as credibility, confirmability, process audit study, two-round Delphi method, face validity, and calculation of the coefficient of reliability using the summarization method (split-half technique) were employed. Content analysis was used to analyze the review of resources and expert opinions, followed by Delphi analysis and mutual effects analysis. The results indicated the presence of 27 key drivers in the future of AI in the sports industry, among which five drivers (occupational transformation, investment, expansion scope of AI, readiness for AI technology adoption, and infrastructure and equipment) were identified as constructive drivers of the future of AI in the sports industry. These results suggest that the transformative alternatives of AI in the sports industry encompass a spectrum of factors that are likely to undergo changes in the near future.
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