شناسایی و اعتبارسنجی ابعاد مدل جهت واکاوی تأثیر حالت مدیریت هوشمند بر ورزش‌های دانشگاهی استان مرکزی با نقش فناوری اینترنت اشیاء
محورهای موضوعی : مدیریت
حافظ محرابی حصار
1
,
حمید فروغی پور
2
*
,
محمد نیکروان
3
1 - گروه تربیت بدنی و علوم ورزشی ،واحد بروجرد، دانشگاه آزاد اسلامی، بروجرد، ایران
2 - گروه تربیت بدنی و علوم ورزشی، واحد بروجرد، دانشگاه آزاد اسلامی، بروجرد، ایران.
3 - گروه تربیت بدنی و علوم ورزشی، واحد بروجرد، دانشگاه آزاد اسلامی، بروجرد، ایران.
کلید واژه: مدیریت هوشمند ورزش, فناوری نوین آموزشی , فناوری اینترنت اشیا, آموزش پیشرفته ورزشی.,
چکیده مقاله :
پژوهش حاضر با هدف شناسایی و اعتبارسنجی ابعاد مدل جهت واکاوی تأثیر حالت مدیریت هوشمند بر ورزش‌های دانشگاهی استان مرکزی با نقش فناوری اینترنت اشیاء انجام شده است. این تحقیق از حیث هدف، اکتشافی و از نظر روش از نوع تحقیق آمیخته (کمی و کیفی) بوده است. در بخش کیفی با بررسی گروهی از مدیران و کارکنان ورزش‌های دانشگاهی استان مرکزی، متغیرهای مؤثر شناسایی شد. در بخش کيفي، به روش مصاحبه نیمه ساختار یافته نظرات خبرگان جمع‌آوری گردید. در این تحقیق با استفاده از رویکرد تحلیل محتوا و ویژگی‌های جمعیت شناختی و ایجاد کدهای اولیه تحقیقات انجام گرفت که پس از آن کدگذاری محوری و پایایی مدل کیفی سپس بررسی و تشریح مقولات صورت گرفت. برای استخراج کدها در این بخش کیفی از نرم‌افزار MAXQDA استفاده شده است. در بخش کمی جامعه آماری اين تحقيق را مدیران و کارکنان و خبرگان دانشگاهی استان مرکزی تشکیل داده است. با توجه به نامحدود بودن جامعه آماری، بر اساس فرمول کوکران، 384 نفر به عنوان نمونه در نظر گرفته شده است. روش تحليل داده‌ها نيز با استفاده از نرم افزار Smart-PLS بوده است. نتایج حاصل از کدگذاری محوری، نشان می‌دهد 28 کد اولیه در قالب 5 مقوله پیامدهای عملکرد مدیریت هوشمند بر ورزش‌های دانشگاهی، عوامل آموزشی، عوامل سازمانی مدیریت، عوامل فردی مدیریت، عوامل فناوری دسته‌بندی شده‌اند. در بخش کمی اعتبارسنجی مدل نتایج نشان داد پیامدهای عملکرد مدیریت هوشمند، عوامل آموزشی، عوامل سازمانی مدیریت هوشمند، عوامل فردی مدیریت هوشمند، عوامل فناوری مدیریت هوشمند بر ورزش‌های دانشگاهی استان مرکزی تأثیر دارد.
The present study was conducted with the aim of identifying and validating the dimensions of the model to analyze the effect of smart management mode on university sports in Markazi Province with the role of Internet of Things technology. This research was exploratory in terms of purpose and mixed research (quantitative and qualitative) in terms of method. In the qualitative part, effective variables were identified by surveying a group of university sports managers and employees in Markazi Province. In the qualitative part, expert opinions were collected using a semi-structured interview method. In this research, research was conducted using the content analysis approach and demographic characteristics and creating initial codes, after which axial coding and reliability of the qualitative model were then examined and explained. MAXQDA software was used to extract codes in this qualitative part. In the quantitative part, the statistical population of this study consisted of university managers, employees, and experts in Markazi Province. Given the unlimited statistical population, 384 people were considered as a sample based on the Cochran formula. The data analysis method was also using Smart-PLS software. The results of axial coding show that 28 initial codes are categorized into 5 categories: consequences of smart management performance on university sports, educational factors, organizational factors of management, individual factors of management, and technological factors. In the quantitative part of the model validation, the results showed that the consequences of smart management performance, educational factors, organizational factors of smart management, individual factors of smart management, and technological factors of smart management have an effect on university sports in Markazi Province.
1. Mohammadi, Sardar, Ghaedi. (2019). Presenting a model of factors influencing the decision to use smartphones in the context of sports: Application of the technology acceptance and pleasant experience model. Sports Management Studies, 60(12), 17-39.
2. Mahmoudian, Abed, Sadeghi Boroujerdi, Delshab, & Gharibi. (2019). Presenting a model of factors influencing the intention to use smartphones in sports consumption. Sports Management and Development, 8(3), 118-134.
3. A. J. White, J. Batten, S. Robinson et al. (2018). “Tackling in physical education rugby: an unnecessary risk?” Injury Prevention, vol. 24, no. 2, pp. 114-115, 2018. View at: Publisher Site | Google Scholar
4. A. Javed, H. Larijani, and A. Wixted (2018). “Improving energy consumption of a commercial building with iot and machine learning,” IT Professional, vol. 20, no. 5, pp. 30–38.
5. A. Judge-Stasiak. (2022). “Special admission: how college sports recruitment favors white, suburban athletes,” International Journal for Educational Integrity, vol. 18, no. 1, p. 1, 2022. View at: Publisher Site | Google Scholar
6. A. O. Akmandor, Y. I. N. Hongxu, and N. K. Jha. (2018). “Smart, secure, yet energy-e fficient, Internet-of-Things sensors, ” IEEE Transactions on Multi-Scale Computing Systems, vol. 4, no. 4, pp. 914 –930.
7. A. Zielonka, A. Sikora, M. Wozniak, W. Wei, Q. Ke, and Z. Bai. (2021). “Intelligent Internet of Things system for smart home optimal convection, ” IEEE Transactions on Industrial Informatics , vol. 17, no. 6, pp. 4308 –4317.
8. B. E. Maamari and J. F. Majdalani. (2019). “The effect of highly emotionally intelligent teachers on their students’ satisfaction,” International Journal of Educational Management, vol. 33, no. 1, pp. 179–193.
9. Ben-Daya, M. E. (2019). "Internet of things and supply chain management: a literature review. " International Journal of Production Research 57, 15-16 (2019): 4719-4742. https://doi.org/10.1080/00207543.2017 .1402140.
10. C. K. Ng, C. H. Wu, K. L. Yung, W. H. Ip, and T. Cheung. (2018). “A semantic similarity analysis of Internet of Things,” Enterprise Information Systems, vol. 12, no. 7, pp. 820–855.
11. C. Roure and D. Pasco. (2018). “Exploring situational interest sources in the French physical education context,” European Physical Education Review, vol. 24, no. 1, pp. 3–20.
12. Dweekat, A. J. (2017). A supply chain performance measurement approach using the internet of things: Toward more practical SCPMS. Industrial Management & Data Systems, 117(2), 267-286. https://www.emerald .com/insight/content/doi/10.1108/IMDS-03-2016-0096/full/html.
13. Dadhaneeya, H., Nema, P. K., & Arora, V. K. (2023). Internet of things in food processing and its potential in industry 4.0 era: A review. Trends in Food Science & Technology. https://doi.org/10.1016/ j.tifs.2023.07.006.
14. Elnour, M., Fadli, F., Himeur, Y., Petri, I., Rezgui, Y., Meskin, N., & Ahmad, A. M. (2022). Performance and energy optimization of building automation and management systems: Towards smart sustainable carbon-neutral sports facilities. Renewable and Sustainable Energy Reviews, 162, 112401.
15. F. V. Paulovich, M. C. F. De Oliveira, and O. N. Oliveira Jr. (2018). “ A future with ubiquitous sensing and intelligent systems, ” ACS Sensors, vol. 3, no. 8, pp. 1433 –1438.
16. G. Escriva-Boulley, D. Tessier, N. Ntoumanis, and P. Sarrazin. (2018). “Need-supportive professional development in elementary school physical education: effects of a cluster-randomized control trial on teachers’ motivating style and student physical activity,” Sport, Exercise, and Performance Psychology, vol. 7, no. 2, pp. 218–234.
17. G. Manogaran, D. Lopez, and N. Chilamkurti. (2018). “In-Mapper combiner based MapReduce algorithm for processing of big climate data,” Future Generation Computer Systems, vol. 86, pp. 433–445.
18. H. Nakayama, M. Ogino, S. Nagahiro, and S. Iwabuchi. (2018). “The management of sports-related concussion and head injuries,” Japanese Journal of Neurosurgery, vol. 27, no. 1, pp. 4–8.
19. Huang, Z., Xu, S., De, L., Xiong, M., Gang, W., Liu, M., & Neely, L. (2022). The Intelligent Management Mode of College Sports under the Background of 5G Internet of Things. Mobile Information Systems, 2022.
20. J. Chen, W. Wang, Y. Zhou, S. H. Ahmed, and W. Wei. (2021). “Exploiting 5G and Blockchain for medical applications of drones, ” IEEE Network, vol. 35, no. 1, pp. 30 –36.
21. J. Kharel, H. T. Reda, and S. Y. Shin. (2019). “Fog computing-based smart health monitoring system deploying lora wireless communication,” IETE Technical Review, vol. 36, no. 1, pp. 69– 82.
22. J. S. Shin and H. K. Yoon. (2018). “The relationships between self-management behavior, self-efficacy, and performance of college golf athletes,” Korean Journal of Sports Science, vol. 27, no. 2, pp. 283–294.
23. Li-Yun, Z., Cheng-Ke, W., & Qiang, Z. (2022). The Construction of Folk Sports Featured Towns Based on Intelligent Building Technology Based on the Internet of Things. Applied Bionics and Biomechanics, 2022.
24. Braksiek, M. (2021). “Pre-service physical education teachers’ attitudes toward inclusive physical education,” German Journal of Exercise and Sport Research, vol. 52, no. 1, pp. 1–10.
25. Mostafa, N., Walaa, H., & Hisham, A. (2019). Impacts of internet of things on supply chains: a framework for warehousing. Social sciences, 8, no. 3:p 84. https://doi.org/10.3390/socsci8030084.
26. M. Chen, Y. Ma, Y. Li, D. Wu, Y. Zhang, and C. H. Youn. (2017). “Wearable 2.0: enabling human-cloud integration in next generation healthcare systems,” IEEE Communications Magazine, vol. 55, no. 1, pp. 54–61.
27. M. Devarajan and L. Ravi. (2019). “Intelligent cyber-physical system for an e fficient detection of Parkinson disease using fog computing,” Multimedia Tools and Applications, vol. 78, no. 23, pp. 32695 –32719.
28. M. Hamnah, P. Haris, H. S. Ali et al. (2018). “Computationally intelligent techniques for resource management in mmWave small cell networks,” IEEE Wireless Communications, vol. 25, no. 4, pp. 32–39.
29. M. K. Priyan and G. U. Devi. (2019). “A survey on internet of vehicles: applications, technologies, challenges and opportunities,” International Journal of Advanced Intelligence Paradigms, vol. 12, no. 1/2, pp. 98–119.
30. M. Mayer and A. J. Baeumner. (2019). “A megatrend challenging analytical chemistry: biosensor and chemosensor concepts ready for the Internet of Things,” Chemical Reviews, vol. 119, no. 13, pp. 7996–8027.
31. M. Tariq, H. Majeed, M. O. Beg, F. A. Khan, and A. Derhab. (2019). “Accurate detection of sitting posture activities in a secure IoT based assisted living environment,” Future Generation Computer Systems, vol. 92, pp. 745–757.
32. Nozari, H., Ghahremani-Nahr, J., Fallah, M., & Szmelter-Jarosz, A. (2022). Assessment of cyber risks in an IoT-based supply chain using a fuzzy decision-making method. International Journal of Innovation in Management, Economics and Social Sciences, 2, no.p 1. DOI: https://doi.org/10.52547/ijimes.2.1.52.
33. O. B. Sezer, E. Dogdu, and A. M. Ozbayoglu. (2018). “Context-aware computing, learning, and big data in internet of things: a survey,” IEEE Internet of Things Journal, vol. 5, no. 1, pp. 1–27.
34. P. M. Kumar, S. Lokesh, R. Varatharajan, G. Chandra Babu, and P. Parthasarathy. (2018). “Cloud and IoT based disease prediction and diagnosis system for healthcare using Fuzzy neural classifier,” Future Generation Computer Systems, vol. 86, pp. 527–534.
35. P. S. Aithal and S. Aithal. (2019). “Management of ICCT underlying technologies used for digital service innovation,” International Journal of Management, Technology, and Social Sciences, vol. 4, no. 2, pp. 110–136.
36. P. Spachos, I. Papapanagiotou, and K. N. Plataniotis. (2018). “Microlocation for smart buildings in the era of the internet of things: a survey of technologies, techniques, and approaches, ” IEEE Signal Processing Magazine, vol. 35, no. 5, pp. 140 –152.
37. P. Verma and S. K. Sood. (2018). “Internet of things-based student performance evaluation framework, ” Behaviour & Information Technology, vol. 37, no. 2, pp. 102–119.
38. R. Fernandez Molanes, K. Amarasinghe, J. Rodriguez-Andina, and M. Manic. (2018). “Deep learning and reconfigurable platforms in the internet of things: challenges and opportunities in algorithms and hardware,” IEEE Industrial Electronics Magazine, vol. 12, no. 2, pp. 36–49.
39. R. Kretschmann (2018). “Physical education 2.0,” SSRN Electronic Journal, vol. 13, no. 4, pp. 395–405.
40. R. Punj and R. Kumar. (2019). “Technological aspects of WBANs for health monitoring: a comprehensive review, ” Wireless Networks, vol. 25, no. 3, pp. 1125–1157.
41. Ray, P. P. (2015, December). Generic Internet of Things architecture for smart sports. In 2015 international conference on control, instrumentation, communication and computational technologies (ICCICCT) (pp. 405-410). IEEE.
42. Ren, P., Nie, M., & Ming, H. (2021). Optimization of sports good recycling management system based on Internet of Things. Wireless Communications and Mobile Computing, 2021.
43. S. Ankit, K. Dheeraj, and H. Jürgen. (2018). “IoT based information and communication system for enhancing underground mines safety and productivity: genesis, taxonomy and open issues,” Ad Hoc Networks, vol. 78, pp. 115–129.
44. S. H. Lee and T. D. Kwon. (2018). “The analysis on research trend related to doping in Korea’s physical education,” Korean Journal of Sports Science, vol. 27, no. 2, pp. 9–17.
45. S. Kumar, R. D. Raut, and B. E. Narkhede. (2020). “A proposed collaborative framework by using artificial intelligence-internet of things (AI-IoT) in COVID-19 pandemic situation for healthcare workers,” International Journal of Healthcare Management, vol. 13, no. 4, pp. 337–345.
46. S. R. Zahra and M. A. Chishti. (2019). “Assessing the services, security threats, challenges and solutions in the Internet of Things, ” Scalable Computing: Practice and Experience, vol. 20, no. 3, pp. 457 –484.
47. S. W. Choi. (2018). “Influence of college student’s exercise regularity to health improvement behavior and connected recognition for life-time sports,” Korean Journal of Sports Science, vol. 27, no. 2, pp. 117–124.
48. Tavakkoli-Moghaddam, R., Ghahremani-Nahr, J., Samadi Parviznejad, P., Nozari, H., & Naja, E. (2022). Application of internet of things in the food supply chain: a literature review. Journal of applied research on industrial engineering, 9(4): 475-492. https://doi.org/10.22105/jarie. 2021.301205.1368.
49. T. H. Oh and D. J. Kim. (2019). “Relationship between job stress and job enthusiasm of college sports part-time lecturers: verification of the mediated effects of overcoming power,” Korean Journal of Sports Science, vol. 28, no. 5, pp. 253–263.
50. V. Jagadeeswari, V. Subramaniyaswamy, R. Logesh, and V. Vijayakumar. (2018). “A study on medical internet of things and big data in personalized healthcare system,” Health Information Science and Systems, vol. 6, no. 1, pp. 14–20.
51. W. Wang, Z. Gong, J. Ren, F. Xia, Z. Lv, and W. Wei. (2021). “Venue topic model –enhanced joint graph modelling for citation recommendation in scholarly big data,” ACM Transactions on Asian and Low-Resource Language Information Processing, vol. 20, no. 1, pp. 1 –15.
52. W. Wei, Q. Ke, J. Nowak, M. Korytkowski, R. Scherer, and M. Wo źniak. (2020). “Accurate and fast URL phishing detector: a convolutional neural network approach,” Computer Networks, vol. 178, p. 107275.
53. X. Deng, P. Jiang, X. Peng, and C. Mi (2019). “An intelligent outlier detection method with one class support tucker machine and genetic algorithm toward big sensor data in internet of things,” IEEE Transactions on Industrial Electronics, vol. 66, no. 6, pp. 4672–4683.
54. X. Xiao-wei. (2020). “Study on the intelligent system of sports culture centers by combining machine learning with big data, ” Personal and Ubiquitous Computing, vol. 24, no. 1, pp. 151–163.
55. Y. Miao, G. Wu, C. Liu, M. S. Hossain, and G. Muhammad. (2019). “Green cognitive body sensor network: architecture, energy harvesting, and smart clothing-based applications, ” IEEE Sensors Journal, vol. 19, no. 19, pp. 8371–8378.
56. Y. Yang, X. Mei, and J. Guo. (2021). “Improving strategies of college physical education teachers’ core accomplishment under the background of Internet+,” International Journal of Frontiers in Sociology, vol. 3, no. 17, pp. 19–31.
57. Yu, H., Cai, Z., Xie, W., Xiao, H., Zhang, S., & Wang, F. (2022). Research on the Construction of Intelligent Sports Health Management System Based on Internet of Things and Cloud Computing Technology. Wireless Communications and Mobile Computing, 2022.