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آینده نگاری پیشران های سازندۀ هوش مصنوعی در صنعت ورزش | |
| مطالعات مدیریت رفتار سازمانی در ورزش | |
| مقاله 1، دوره 12، شماره 4 - شماره پیاپی 48، دی 1404، صفحه 1-23 اصل مقاله (1.7 M) | |
| نوع مقاله: مقاله پژوهشی | |
| شناسه دیجیتال (DOI): 10.30473/fmss.2025.71496.2616 | |
| نویسندگان | |
| شادی رهبر یعقوبی1؛ مهوش نوربخش* 2؛ مهدی کهندل3؛ سید نعمت خلیفه4 | |
| 1دانشجوی دکتری گروه مدیریت ورزشی، واحد کرج، دانشگاه آزاد اسلامی، کرج، ایران | |
| 2استاد گروه مدیریت ورزشی، واحد کرج، دانشگاه آزاد اسلامی، کرج، ایران | |
| 3دانشیار گروه مدیریت ورزشی، واحد کرج، دانشگاه آزاد اسلامی،کرج، ایران | |
| 4استادیار گروه مدیریت ورزشی، واحد کرج، دانشگاه آزاد اسلامی، کرج، ایران | |
| چکیده | |
| هدف این پژوهش آینده نگاری راهبردی پیشران های سازندۀ هوش مصنوعی در صنعت ورزش بود. این پژوهش از نظر هدف، کاربردی و از نظر ماهیت براساس روش های جدید علم آینده پژوهی، تحلیلی اکتشافی محسوب می شود که با استفاده از روش تحلیل تأثیر متقابل انجام گرفته است. جامعه آماری شامل دو بخش منابع اطلاعاتی (مقالات مرتبط با موضوع تحقیق) و منابع انسانی (کارشناسان حوزه هوش مصنوعی، کارشناسان حوزه صنعت ورزش و اساتید دانشگاه) بود. روش نمونه گیری در هر دو بخش جامعه اطلاعاتی و انسانی هدفمند بود. در بخش جامعه اطلاعاتی 18 مطالعه بر مبنای معیارهای ورود و خروج و در بخش جامعه انسانی 18 نفر براساس 4 معیار تجربۀ کاری، تحصیلات کارشناسی ارشد و دکتری، تنوع و قابلیت همکاری انتخاب شدند. ابزار گردآوری داده ها چک لیست، پرسشنامه و ماتریس به ابعاد 27×27 بود. برای ارزیابی اعتبار و قابلیت اطمینان به نتایج از راهبردهای قابلیت باورپذیری، تأییدپذیری، مطالعه حسابرسی فرآیند، دلفی در دو دور، روایی صوری و محاسبه ضریب قابلیت اعتماد با روش تنصیف (دو نیمه کردن) استفاده شد. برای تحلیل مرور منابع و دیدگاه های خبرگان از تحلیل محتوا و در ادامه به ترتیب از تحلیل دلفی و تحلیل تأثیر متقابل استفاده شد. نتایج نشان داد در تبیین آینده هوش مصنوعی در صنعت ورزش 27 پیشران کلیدی وجود دارند که از بین آنها 5 پیشران (دگرگونی شغلی، سرمایه گذاری، دامنه گسترش هوش مصنوعی، آمادگی پذیرش فناوری هوش مصنوعی و زیرساخت و تجهیزات) جزء پیشران های سازنده آینده هوش مصنوعی در صنعت ورزش هستند. براساس این نتیجه مشخص شد بدیل های سازندۀ آینده هوش مصنوعی در صنعت ورزش طیف مختلفی از عوامل را در بر می گیرد که به نظر می رسد در آینده نزدیک دستخوش تغییر می شوند. | |
| کلیدواژهها | |
| آینده نگاری؛ برنامه ریزی راهبردی؛ عدم قطعیت؛ صنعت ورزش؛ هوش مصنوعی | |
| عنوان مقاله [English] | |
| Forecasting of AI Drivers in the Sports Industry | |
| نویسندگان [English] | |
| Shadi Rahbar Yaghobi1؛ Mahvash Noorbaksh2؛ mehdi kohandel3؛ Seyed Nemat Khalifeh4 | |
| 1Ph. D. Student of Sports Management Department, Karaj Branch, Islamic Azad University, Karaj, Ira | |
| 2Prof. of Sports Management Department, Karaj Branch, Islamic Azad University, Karaj, Iran | |
| 3Associate Professor, Department of Sports Management, Islamic Azad University, Karaj Branch | |
| 4Member of scientific islamic azad university | |
| چکیده [English] | |
| 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. | |
| کلیدواژهها [English] | |
| Strategic Forecasting, Strategic Planning, Uncertainty, Sports Industry, Artificial Intelligence | |
| مراجع | |
|
Ashouri M. Compilation Of a Pattern For The Development Of The Application Of Artificial Intelligence In The Sports Industry In Iran. Thesis. 2024. (in persian)
|
|
|
Bamunif AOA, Singh A, Nasser A, Fais M, Mohammed R, Sarangi PK. Sports Information & Discussion Forum Using Artificial Intelligence Techniques: A New Approach. Turkish Journal of Computer and Mathematics Education (TURCOMAT). 2021; 12(11): 2847-2854.
|
|
|
Cheng L, Varshney KR, Liu H. Socially Responsible AI Algorithms: Issues, Purposes, and Challenges. Journal of Artificial Intelligence Research. 2021; 71: 1137-1181.
|
|
|
Chesli SR, Mousavi SA, Kambiz Heidarzadeh Hanzaei MAA. Investigating the Factors and Consequences of the Intelligence Sale of Appliances and Sports Equipment in the Metaverse. Sciences and Techniques of Information Management. 2023; 3(9): 161-196. (in persian)
|
|
|
Claudino JG, Capanema DDO, de Souza TV, Serrão JC, Machado Pereira AC, Nassis GP. Current approaches to the use of artificial intelligence for injury risk assessment and performance prediction in team sports: a systematic review. Sports medicine-open. 2019; 5(1): 1-12.
|
|
|
Eid AIA, Miled AB, Fatnassi A, Nawaz MA, Mahmoud AF, Abdalla FA, et al. Sports Prediction Model through Cloud Computing and Big Data Based on Artificial Intelligence Method. Journal of Intelligent Learning Systems and Applications. 2024; 16(2): 53-79.
|
|
|
Fekrat A, Jaberi A. Phenomenology of the role of artificial intelligence marketing on increasing sales and exports of Iranian sports goods. Sports Marketing Studies. 2024; 5(2): 1-15. (in persian)
|
|
|
Ghorbani N. Identify and rank the effective factors in improving the use of artificial intelligence in sports venues. Thesis. 2022. (in persian)
|
|
|
Glebova E, Madsen D, Mihaľová P, Géczi G, Mittelman A, Jorgič B. Artificial intelligence development and dissemination impact on the sports industry labor market. Frontiers in Sports and Active Living. 2024; 6: 1363892.
|
|
|
Hall S, Workman M, Hardy J, Mazur C, Anable J, Powell M, et al. Doing business model innovation for sustainability transitions—Bringing in strategic foresight and human centred design. Energy Research & Social Science. 2022;: 102685.
|
|
|
Hammes F, Hagg A, Asteroth A, Link D. Artificial Intelligence in Elite Sports—A Narrative Review of Success Stories and Challenges. Frontiers in sports and active living. 2022; 4: 1-15.
|
|
|
He N, Yan S, Jiang Z, Qin X, Wang W, Liu C. Artificial Intelligence Technology in Sports Application: The Chinese Experience. In 2021 International Conference on Information Technology and Contemporary Sports (TCS) ; 2021: IEEE. p. 489-493.
|
|
|
Huang Y. The role of artificial intelligence technology in promoting the development of my country's sports industry. In 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022) ; 2022. p. 226-230.
|
|
|
Jeavons A. What is artificial intelligence? Research World. 2017; 2017(65): 75-75.
|
|
|
Kaur D, Uslu S, Rittichier KJ, Durresi A. Trustworthy artificial intelligence: a review. ACM Computing Surveys (CSUR). 2022; 55(2): 1-38.
|
|
|
Li A, Huang W. A comprehensive survey of artificial intelligence and cloud computing applications in the sports industry. Wireless Networks. 2023;: 1-12.
|
|
|
Liu H, Wang Y, Fan W, Liu X, Li Y, Jain S, et al. Trustworthy AI: A Computational Perspective. ACM Transactions on Intelligent Systems and Technology. 2022; 14(1): 1-59.
|
|
|
Lu L, Yang S, Li Q. The interaction of digital economy, artificial intelligence and sports industry development based on China PVAR analysis of provincial panel data. Heliyon. 2024; 10(4): 1-15.
|
|
|
Lv Z, Song S. Integration of Artificial Intelligence Plus Industry and Sports Industry: A Research on the Innovation and Development Strategy of Sports Industry. Advances in Social Science, Education and Humanities Research. 2020; 457: 7-12.
|
|
|
Ma W, Chen H. Application Scenarios and Forms of Artificial Intelligence in Physical Education. Advances in Education, Humanities and Social Science Research. 2024; 9(1): 13-13.
|
|
|
Nadikattu RR. Implementation of New Ways of Artificial Intelligence in Sports. Journal of Xidian University. 2020; 14(5): 5983 - 5997.
|
|
|
Nazari R, Shahvali J. Strategic Scenarios of Health-Based Sport in Iran. Sport Management Journal. 2022; 14(1): 172-151. (in persian)
|
|
|
Nikooye M. Providing an Integrated Strategic Foresight Evaluation Framework at National Level (Iran Spatial Planning Case). Phd Thesis. 2020. (in persian)
|
|
|
Pavljuk M. Forecast of Development Trends in Sport–Year 2030. In Management, Technology and Sport: Proceedings of the Second International Conference ; 2024. p. 61-67.
|
|
|
Prager SD, Wiebe K. Strategic foresight for agriculture: Past ghosts, present challenges, and future opportunities. Global Food Security. 2021; 28: 100489.
|
|
|
Qi Y, S.M. S, Baghaei S, Rezaei R, Li W. Digital technologies in sports: Opportunities, challenges, and strategies for safeguarding athlete wellbeing and competitive integrity in the digital era. Technology in Society. 2024; 77: 102496.
|
|
|
Shahvali Kohshouri J, Askari A, Nazari R, Naghsh A. The Formulation Iranian Educational Sports Strategies: Scenario-based. Research on Educational Sport. 2020; 8(21): 223-250. (in persian)
|
|
|
Shirooyehpour S, fazli S, Keshavarz Turk E. Modeling the Effect of Strategic Foresight on Dynamic Capabilities: The Moderating Role of Environmental Uncertainty. Iranian journal of management sciences. 2022; 17(65): 1-28. (in persian)
|
|
|
Soltanpour A,EGMR,FDH. The conceptual framework of the use of new technology in the media (a case study of artificial intelligence in the sports press). Communication Management in Sport Media. 2023. (in persian)
|
|
|
Tan T, Lee JW. Technology, innovation, and the future of the sport industry in Asia Pacific. Sport in Society. 2023; 26(3): 383-389.
|
|
|
Wang B. Research on the Design of Nutrition and Sports Health Management System Based on Artificial Intelligence. 3D Imaging Technologies—Multidimensional Signal Processing and Deep Learning Smart Innovation, Systems and Technologies. 2021;: 91-97.
|
|
|
Yan C. The Impact of Artificial Intelligence on Sports. International Journal of Sports, Yoga and Physical Activity. 2022; 1(1): 8-14.
Farid Fathi, A., Fattahpour Marandi, M., Farid Fathi, M., & Sarlab, R. (2023). Pathology of the penetration of luxury values Preference in Consumers of Sporting Goods. New Approaches in Sports Mmanagement, 11(42), 137-160.
|
|
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