آمار
| تعداد نشریات | 26 |
| تعداد شمارهها | 447 |
| تعداد مقالات | 4,557 |
| تعداد مشاهده مقاله | 5,379,991 |
| تعداد دریافت فایل اصل مقاله | 3,580,057 |
The Role of Perceived Risk in the Adoption of Internet of Things Technology in Sports | ||
| Journal of New Studies in Sport Management | ||
| مقاله 3، دوره 4، شماره 3، آبان 2023، صفحه 846-856 اصل مقاله (1.04 M) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.22103/jnssm.2023.21381.1185 | ||
| نویسندگان | ||
| Alireza Nazemi Bidgoli1؛ Ehsan Mohamadi Turkmani2؛ Hamid Reza Irani* 3 | ||
| 1Department of Sport Management, Master student of Sport Sciences and Health, University of Tehran, Tehran, Iran | ||
| 2Assistant Professor, Department of Sport Management, Faculty of Sport Sciences and Health, University of Tehran, Tehran, Iran | ||
| 3Assistant Professor, Department of Marketing, Faculty of Management and Accounting, College of Farabi, University of Tehran, Qom, Iran | ||
| چکیده | ||
| The Internet of Things (IoT) is one technology that can revolutionize traditional methods and transform sports infrastructure. To promote the adoption of IoT effectively, it's vital for sports manager to understand the factors that positively and negatively affect it. The aim of this study was to investigate how perceived risk impacts people's willingness to use IoT technology in sports. This quantitative study used a survey method and applied a descriptive approach. The statistical population included Iranian athletes, and 394 individuals completed questionnaires using a non-probability sampling method. Data analysis was performed using Smart PLS3 software. Results showed that perceived risk has a direct and negative impact on perceived ease of use, willingness to use, and perceived usefulness. However, its effect on attitude towards use was insignificant. The study also confirmed the positive impact of perceived ease of use on perceived usefulness and attitude towards use. Perceived usefulness had a greater effect on the latter variable. Additionally, perceived usefulness had a significant positive impact on willingness to use IoT technology in sports, as did attitude towards use. Attitude towards use also had a significant positive impact on willingness to use IoT technology in sports. The study recommends implementing strategies to enhance and improve perceived usefulness, ease of use, and attitude towards use while reducing perceived risk to increase acceptance and willingness to use IoT technology in sports. | ||
| کلیدواژهها | ||
| Intention to use؛ Iranian Athletes؛ Perceived Risk؛ Technology acceptance model | ||
| مراجع | ||
|
Aldowah, H., Rehman, S., Ghazal, S., & Umar, I. (2017). Internet of Things in Higher Education: A Study on Future Learning. Journal of Physics Conference Series, 892, 012017.
AlHadid, I., Abu-Taieh, E., Alkhawaldeh, R. S., Khwaldeh, S., Masa’deh, R. e., Kaabneh, K., & Alrowwad, A. A. (2022). Predictors for E-Government Adoption of SANAD App Services Integrating UTAUT, TPB, TAM, Trust, and Perceived Risk. International Journal of Environmental Research and Public Health, 19(14), 8281.
Ansari, M., Mohammadian, A., & Nevisande, E. (2017). Identifying the applications of internet of things in the smart home by using meta synthesis Method. Journal of Information Technology Management, 9(4), 659-678. doi:10.22059/JITM.2017.227832.1967
Asad, M., Moustafa, A., & Yu, C. (2020). A critical evaluation of privacy and security threats in federated learning. Sensors, 20(24), 7182.
Balaji, M., & Roy, S. K. (2017). Value co-creation with Internet of things technology in the retail industry. Journal of Marketing Management, 33(1-2), 7-31.
bandari, Saidi, S., Sohail, & Ghasemi. (2021). Identification and ranking of attitudinal factors related to e-commerce education in shopping (case study: students of electronics department of Kharazmi University). Sociology of Education, 6(2), 138-151.
Bansal, M., Chana, I., & Clarke, S. (2020). A survey on iot big data: current status, 13 v’s challenges, and future directions. ACM Computing Surveys (CSUR), 53(6), 1-59.
Bauer R, A. (1960). Consumer Behavior as Risk Taking. Proceedings of the 43rd National Conference of the American Marketing Assocation, June 15, 16, 17, Chicago, Illinois, 1960.
Bontempo, R. N., Bottom, W. P., & Weber, E. U. (1997). Cross‐cultural differences in risk perception: A model‐based approach. Risk analysis, 17(4), 479-488.
Capasa, L., Zulauf, K., & Wagner, R. (2022). Virtual reality experience of mega sports events: A technology acceptance study. Journal of Theoretical and Applied Electronic Commerce Research, 17(2), 686-703.
Catarinucci, L., De Donno, D., Mainetti, L., Patrono, L., Stefanizzi, M. L., & Tarricone, L. (2017). An IoT-aware architecture to improve safety in sports environments. Journal of communications software and systems, 13(2), 44-52.
Cavdar Aksoy, N., Kocak Alan, A., Tumer Kabadayi, E., & Aksoy, A. (2020). Individuals' intention to use sports wearables: the moderating role of technophobia. International Journal of Sports Marketing and Sponsorship, 21(2), 225-245.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
Dian, F. J., Vahidnia, R., & Rahmati, A. (2020). Wearables and the Internet of Things (IoT), applications, opportunities, and challenges: A Survey. IEEE access, 8, 69200-69211.
Dowling, G. R., & Staelin, R. (1994). A model of perceived risk and intended risk-handling activity. Journal of consumer research, 21(1), 119-134.
Duan, R., & Guo, L. (2021). Application of blockchain for internet of things: a bibliometric analysis. Mathematical Problems in Engineering, 2021, 1-16.
Ebrahimi, A., Jafarzadeh, M., & Bozorgi, S. (2012). Analyzing factors Affecting Consumers’ Attitude & Intention to Purchase Counterfeit products of luxury Brands In clothing Industry. New Marketing Research Journal, 2(3), 1-34.
El-Qirem, I. A. (2013). Critical factors influencing E-Banking service adoption in Jordanian commercial banks: a proposed model. International business research, 6(3), 229.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behaviour: An introduction to theory and research (Vol. 27).
Gharahkhani, M., & Pourhashemi, S. O. (2021). Analyzing the influencing factors in the acceptance of the Internet of Things (IoT) in the Iranian insurance industry. Iranian Journal of Insurance Research, 11(1), 41-56.
Girish, V., Kim, M.-Y., Sharma, I., & Lee, C.-K. (2022). Examining the structural relationships among e-learning interactivity, uncertainty avoidance, and perceived risks of COVID-19: Applying extended technology acceptance model. International Journal of Human–Computer Interaction, 38(8), 742-752.
golshan, Athena, & Roudbane, P. (2020). Investigating factors affecting the acceptance of smart healthcare devices using the hybrid technology acceptance model. Journal of Health and Biomedical Informatics, 7(3), 282-292.
Hajisalim, M., & Badizadeh, A. (2018). The Effect of Mobile Software Features on Customer Attitude and Satisfaction. Journal of Development & Evolution Mnagement, 9(special issue), 63-73.
hosseininia, g., Moghaddas Farimani, S., & Marefat Gharehbaba, N. (2022). Constructs Affecting the Willingness to Adopt Internet of Things (IoT) by Early Adopter Farmers in Tehran Province. Iranian Agricultural Extension and Education Journal, 17(2), 235-249.
Javani, V., & Karimivand, H. (2022). Social Media and Sports Stakeholders Challenges and Opportunities. Journal of New Studies in Sport Management, 3(3), 494-508.
Kamali Mohammadzadeh, A., Ghafoori, S., Mohammadian, A., Mohammadkazemi, R., Mahbanooei, B., & Ghasemi, R. (2018). A Fuzzy Analytic Network Process (FANP) approach for prioritizing internet of things challenges in Iran. Technology in Society, 53, 124-134.
Kim, K. J., & Shin, D.-H. (2015). An acceptance model for smart watches: Implications for the adoption of future wearable technology. Internet Research.
Kim, T. G., Lee, J. H., & Law, R. (2008). An empirical examination of the acceptance behaviour of hotel front office systems: An extended technology acceptance model. Tourism management, 29(3), 500-513.
Koksalmis, G. H., Arpacı, İ., & Koksalmis, E. (2022). Predicting the Intention to Use Bitcoin: An Extension of Technology Acceptance Model (TAM) with Perceived Risk Theory. In M. Al-Emran & K. Shaalan (Eds.), Recent Innovations in Artificial Intelligence and Smart Applications (pp. 105-120). Cham: Springer International Publishing.
Kos, A., Wei, Y., Tomažič, S., & Umek, A. (2018). The role of science and technology in sport. Procedia Computer Science, 129, 489-495.
Kunz, R. E., & Santomier, J. P. (2019). Sport content and virtual reality technology acceptance. Sport, Business and Management: An International Journal, 10(1), 83-103.
Leveaux, R. (2010). Facilitating Referee’s Decision Making in Sport via the Application of Technology. Communications of the IBIMA.
Lin, H.-F. (2007). Predicting consumer intentions to shop online: An empirical test of competing theories. Electronic Commerce Research and Applications, 6(4), 433-442.
Lin, W.-B. (2008). Investigation on the model of consumers’ perceived risk—integrated viewpoint. Expert Systems with Applications, 34(2), 977-988.
Lu, H. P., Hsu, C. L., & Hsu, H. Y. (2005). An empirical study of the effect of perceived risk upon intention to use online applications. Information management & computer security, 13(2), 106-120.
Lunney, A., Cunningham, N. R., & Eastin, M. S. (2016). Wearable fitness technology: A structural investigation into acceptance and perceived fitness outcomes. Computers in Human Behavior, 65, 114-120.
Mutahar, A., Aldholay, A., Isaac, O., Jalal, A., & Kamaruddin, F. (2022). The Moderating Role of Perceived Risk in the Technology Acceptance Model (TAM): The Context of Mobile Banking in Developing Countries (pp. 389-403).
Patel, P. C., Parida, V., & Tran, P.-K. (2022). Perceived risk and the need for trust as drivers of improved surgical skills in 3D surgical video technology. Journal of Innovation & Knowledge, 7(4), 100269.
qolamian, Ramadanzadeh, Moslem, Mahmoudi, Ahmad, Azizi, & Bahadur. (2022). Providing a model of key success factors in the process of sports businesses. Strategic Management Studies Quarterly.
Rondan-Cataluña, F. J., Arenas-Gaitán, J., & Ramírez-Correa, P. E. (2015). A comparison of the different versions of popular technology acceptance models: A non-linear perspective. Kybernetes.
Sahebkaran, M. A., Khoshbakhti, J., & Kariminejad, R. (2022). Identifying Effective Drivers in the Future of Sports Businesses in Khorasan Razavi Province. Journal of New Studies in Sport Management, 3(3), 509-520.
Shambiati, H., Shafii Nikabadi, M., Khatami Firouzabadi, S. M. A., Rahmani Manesh, M., & Saberi, S. (2022). A model to optimize the performance of information processing in the virtual supply chain, based on the Internet of Things. Production and Operations Management, 13(1), 1-24.
Shekari, A., Mosuavi, S. N., & Gholami Chenarestan Olya, A. (2020). Explaining Model of Attitude towards Advertising in Sporting Goods via Instagram Using Technology Acceptance Model. Journal of Business Management, 12(45), 203-225.
Shin, S., & Lee, W.-j. (2014). The effects of technology readiness and technology acceptance on NFC mobile payment services in Korea. Journal of Applied Business Research (JABR), 30(6), 1615-1626.
Soto-Beltrán, L. L., Robayo-Pinzón, O. J., & Rojas-Berrio, S. P. (2022). Effects of perceived risk on intention to use biometrics in financial products: evidence from a developing country. International Journal of Business Information Systems, 39(2), 170-192.
Sukendro, S., Habibi, A., Khaeruddin, K., Indrayana, B., Syahruddin, S., Makadada, F. A., & Hakim, H. (2020). Using an extended Technology Acceptance Model to understand students’ use of e-learning during Covid-19: Indonesian sport science education context. Heliyon, 6(11), e05410.
Tan, G. W.-H., Ooi, K.-B., Chong, S.-C., & Hew, T.-S. (2014). NFC mobile credit card: the next frontier of mobile payment? Telematics and Informatics, 31(2), 292-307.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.
Vermesan, O., Friess, P., Guillemin, P., Sundmaeker, H., Eisenhauer, M., Moessner, K., . . . Giaffreda, R. (2022). Internet of things strategic research and innovation agenda Internet of Things Applications-From Research and Innovation to Market Deployment (pp. 7-142): River Publishers.
Wilkerson, G. B., Gupta, A., & Colston, M. A. (2018). Mitigating sports injury risks using internet of things and analytics approaches. Risk analysis, 38(7), 1348-1360.
Yu, X. (2022). Farmers’ trust in government and participation intention toward rural tourism through TAM: The moderation effect of perceived risk. Frontiers in Psychology, 13.
Zarei, M., Mohammadian, A., & Ghasemi, R. (2016). Internet of things in industries: A survey for sustainable development. International Journal of Innovation and Sustainable Development, 10(4), 419-442.
Zhan, K. (2021). Sports and health big data system based on 5G network and Internet of Things system. Microprocessors and Microsystems, 80, 103363.
Zohrabi, A., Karimi, J., & Mohebi, A. (2020). Explaining the Applications of Internet of things in Iran's Sports Industry: A Sustainable Development Approach. Communication Management in Sport Media, 7(3), 91-98. | ||
|
آمار تعداد مشاهده مقاله: 272 تعداد دریافت فایل اصل مقاله: 278 |
||