Analysis of the Impact and Challenges of Technology Application in Sports Development
Article Sidebar
Main Article Content
Abstract
The purpose of this article is to study the role of technology in sports development, analyze innovations used in the sports industry, and identify challenges associated with implementing technology in sports. The article aims to provide valuable information to sports administrators, fitness enthusiasts, and researchers on the sustainable and efficient use of technology in sports development. The application of technology in the sports industry plays a significant role in enhancing and improving training, competition, sports officiating, sports communication, and human resource management. Modern technologies have been introduced to advance various aspects of sports, including motion sensors, GPS systems, and wearable technologies that enhance training efficiency and monitor athlete performance. Examples of these technologies include AR systems, step counter applications, virtual reality (VR), and the Nintendo Switch. The use of technology in data management and decision-making also contributes to more accurate and efficient data analysis, such as with Hawk-Eye technology and video analysis. Moreover, the application of cloud computing and artificial intelligence (AI) in storing and analyzing competition data enables more effective strategy prediction and improvement. However, the adoption of technology in the sports industry still faces several challenges, such as data privacy and security concerns, high costs, accessibility, and the acceptance of new technologies by users.
Addressing these issues requires clear policy development and staff training to adapt and use technology effectively. This article emphasizes exploring the role of technology in sports development and offers suggestions for future technology implementation in the sports industry to ensure sustainable and efficient use of technology in sports.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Article Screening Policy
- All research and academic articles to be published must be considered and screened by three peer reviews in the relevant field / article.
- All articles, texts, illustrations and tables published in the journal are the personal opinions of the authors. Editors don't always have to agree. And no responsibility whatsoever is the sole responsibility of the author.
- The articles to be published must never be published. Where did you first publish? And not in the consideration of other journals If the audit found that there has been a duplicate publication It is the sole responsibility of the author.
- Any article that the reader sees as being plagiarized or impersonated without reference. Or mislead the work of the author Please let the journal editor know it will be your greatest blessing.
References
Dellaserra, C. L., Gao, Y., & Ransdell, L. (2014). Use of integrated technology in team handball: A case study. International Journal of Sports Science & Coaching, 9(1), 181-192.
Gardner, S. D., Lepicki, E. R., & Donnell, K. M. (2003). Cyberspace cybercorps and computer technology in human resource management. Technical report.
Gholami, H., Zailani, S., Hashim, N. A. B., & Yusof, K. A. (2016). Green human resources management. Ekonomska Istraživanja, 29(1), 766-778. https://doi.org/10.1080/1331677X.2016.1231514
Jones, B., Till, K., Emmonds, S., Hendricks, S., Mackreill, R., Darrall-Jones, J., & Rock, A. (2017). Accessing off-field brains in sport: An applied research model to develop practice. British Journal of Sports Medicine, 51(11), 910-910.
Jones, R. D., Mundy, P., Weaving, D., Lavers, B., & Read, D. B. (2016, October). Privacy analysis of global positioning system monitoring in English professional rugby union. In 2016 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) (pp. 62-67). IEEE.
Kim, H., Kim, H., & Lee, J. (2021). Data-driven intelligent sports analytics: Applications and challenges. Applied Sciences, 11(5), 2134.
Lorenzo, J., Lorenzo, A., Quintana-Domeque, C., & Sene, D. (2020). Machine learning in the prediction of professional basketball player compensation. International Journal of Computer Science in Sport, 19(1), 1-21.
Millar, P., & Stevens, J. (2012). Management training and national sport organization managers: Examining the impact of training on individual and organizational performances. Sport Management Review, 15(3), 288-303.
Priyashantha, R. M. V. K., De Alwis, A. C., & Welmilla, I. (2022). E-HRM Practices: How does it impact employees' well being?. International Journal of Human Resource Studies, 12(1).
Ratten, V. (2020). Sport technology: Closing the knowledge gap. Journal of High Technology Management Research, 31(2), 100376.
Schlegel, M., & Hill, A. (2020). Securing the internet of things in the sport industry. Sport & Entertainment Review, 6(1), 3.
Stone, D. L., & Dulebohn, J. H. (2015). Emerging issues in theory and research on electronic human resource management (eHRM). Human Resource Management Review, 25(2), 139-145.
Wu, H. J., Zhao, H. Y., & Zhao, J. (2013). Research on architecture of cloud computing based training system for national fitness exercise instruction. Journal of Beijing Sport University, 36(1), 119-124.
Zhang, C., Xiao, X., Zhang, Y., Zheng, J., & Chen, X. (2021). Application of big data and artificial intelligence in sports. Journal of Physics: Conference Series