Relationships Between Perceived Usefulness and Fitness Wearable Technology User Adoption Mediated by Culture, Gender, and COVID-19: A Meta-Analysis

• Autorzy: Lizhen Shi , Xiaoling Huang , Safdar Abbas , Zong Qian Yang , Li Huang
• Języki publikacji: EN

Abstrakty

EN

With COVID-19 raging and individuals exercising at home, the adoption of fitness wearable technology (FWT) that help people monitor their physical state has become a pressing matter. Here, we try to bridge the gap that no researcher has examined the link between perceived usefulness (PU) and FWT adoption by using meta-analysis to comprehend the detailed numerical values and moderating factors affecting the relationship. A total of 24 articles with 7180 re-pendants were investigated from January 1, 2015 to March 1, 2022 A.D, producing significant results as follows: (1) There is publication bias in relevant research, and sensitivity analysis suggests that PU influences FWT adoption positively; (2) Subgroup test and regression analysis suggested that cultural background, gender, and COVID-19 can deepen this relationship to varying degrees. More precisely, female (r=0.669) have a greater impact on FWT adoption than men (r=0.658). In addition, users in other countries (r=0.670) are more concerned about PU than Chinese users (r=0.658). Regression analysis showed that after the COVID-19 outbreak, the coefficient (r=0.762) of PU on FWT adoption increased significantly, indicating that people need FWT-assisted exercise to understand and maintain their own physical fitness. The research opens up new ideas for different governments and scholars to promote mass fitness and public health during the COVID-19, providing a reference for the scientific research and development of PU and marketing promotion of the related enterprises' FWT.(original abstract)

Słowa kluczowe

EN

Sport; Sports equipment market; COVID-19; Public health

PL

Sport; Rynek sprzętu sportowego; COVID-19; Zdrowie publiczne

• Czasopismo: Quality in Sport
• Rocznik: 2022
• Tom: 8
• Numer: nr 1
• Strony: 55--69

Twórcy

autor

Lizhen Shi

• Southwest University, Chongqing, China

autor

Xiaoling Huang

• Southwest University, Chongqing, China

autor

Safdar Abbas

• Southwest University, Chongqing, China

autor

Zong Qian Yang

• Southwest University, Chongqing, China

autor

Li Huang

• Southwest University, Chongqing, China

Bibliografia

• Binyamin, S. S., & Hoque, M. R. (2020). Understanding the Drivers of Wearable Health Monitoring Technology: An Extension of the Unified Theory of Acceptance and Use of Technology. Sustainability, 12(22).
• Borenstein, M., Hedges,L. V.,Higgins, J. P. T.& Rothstein, H. R. (2009).Effect sizes based on means. In M. Borenstein, L. V. Hedges, J. P. T. Higgins, & H. R. Rothstein (Eds.), Introduction to meta-analysis. United Kingdom: John Wiley & Sons, Ltd. ,21-32.
• Canhoto, A. I., & Arp, S. (2017). Exploring the factors that support adoption and sustained use of health and fitness wearables. Journal of Marketing Management, 33(1-2), 32-60.
• Chen Xiaoyan & Gerard Cliquet.(2020). The Obstructive Effect of Privacy Concerns in the "Quantified Self" Movement: Taking Smart Band User Adoption as an Example. Enterprise Economics, (04), 108-118. doi: 10.13529/j .cnki.enterprise.economy.2020.04.014.
• Cheung, M. L., Chau, K. Y., Lam, M. H. S., Tse, G., Ho, K. Y., Flint, S. W., . . . Lee, K. Y. (2019). Examining Consumers' Adoption of Wearable Healthcare Technology: The Role of Health Attributes. International Journal of Environmental Research and Public Health, 16(13).
• Chuah, S. H.-W., Rauschnabel, P. A., Krey, N., Nguyen, B., Ramayah, T., & Lade, S. (2016). Wearable technologies: The role of usefulness and visibility in smartwatch adoption. Computers in Human Behavior, 65, 276-284. [23]
• Davis F D . (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319-340.
• Diao S. (2010). Emerging e-commerce consumer privacy concerns and adoption behavior research (PhD dissertation, Beijing University of Posts and Telecommunications). https://kns.cnki.net/KCMS/detail/detail.aspx?dbname =CDFD0911&filename=2010222219.nh
• Felea, M., Bucur, M., Negrutiu, C., Nitu, M., & Stoica, D. A. (2021). WEARABLE TECHNOLOGY ADOPTION AMONG ROMANIAN STUDENTS: A STRUCTURAL MODEL BASED ON TAM. Amfiteatru Economic, 23(57), 376-391.
• Higgins J,Thompson S G,Decks J J, et al.(2003). Measuring inconsistency in meta-analyses[J]. British Medical Journal,327(7414):557-560.
• Jin Xin. (2020). Empirical Analysis of Factors Affecting User Adoption Willingness of Knowledge Payment Platform. China Publishing, (20), 50-54.
• Kim, T., & Chiu, W. (2019). Consumer acceptance of sports wearable technology: the role of technology readiness. International Journal of Sports Marketing & Sponsorship, 20(1), 109-126.
• Li Juanjuan & Guo Shunli. (2022). Influencing factors of user knowledge adoption behavior in social question answering community from the perspective of cognition: An exploratory analysis based on grounded theory. Information Science, (02), 91-98. doi: 10.13833/j.issn.1007-7634.2022.02.012.
• Li Zhihui, Shen Zhifeng & Jiao Yuanyuan. (2019). A study on the influence of social support on early users' willingness to adopt new products: Multiple mediating effects based on peer influence and perceived value. Science and Science and Technology Management (11), 82- 97.
• Lu Xiaobin & Wang Jianya. (2015). Analysis of the current situation of cloud computing adoption behavior research. Chinese Library Journal, (01), 92-111. doi:10.13530/j.cnki.jlis.150005.
• 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. Retrieved from ://WOS:000386986000014. doi:10.1016/j.chb.2016.08.007
• Begg CB, Mazumdar M: Operating characteristics of a rank correlation test for publication bias. Biometrics. 1994, 50: 1088-1101. 10.2307/2533446.
• Pancar, T., & Ozkan Yildirim, S. (2021). Exploring factors affecting consumers' adoption of wearable devices to track health data. Universal Access in the Information Society.
• Park Ki-tae.(2009). American Pragmatism from the Historical Point of View. World History and Culture, 21: 307-30.
• Qiu Junqiang, Chen Yan, Xie Yan, Feng Lin, Luo Dan & Zhao Wenhua. (2021). Exercise promotes health: a review and prospect based on energy balance theory. Journal of Beijing Sport University, (05), 2-20. doi: 10.19582 /j.cnki.11-3785/g8.2021.05.001.
• Rosenthal, R. (1979). The file drawer problem and tolerance for null results. Psychological Bulletin, 86(3), 638-64. dx.doi.org/10.1037/0033-2909.86.3.638
• Rothstein, H. R., & Bushman, B. J. (2015). Methodological and Reporting Errors in Meta-Analytic Reviews Make Other Meta-Analysts Angry: A Commentary on Ferguson (2015). Perspectives on Psychological Science, 10(5), 677-679.
• Sergueeva, K., Shaw, N., & Lee, S. H. (2020). Understanding the barriers and factors associated with consumer adoption of wearable technology devices in managing personal health. Canadian Journal of Administrative Sciences-Revue Canadienne Des Sciences De L Administration, 37(1), 45-60.
• Strohrmann C, Rossi M, Arnrich B , et al. (2012). A Data-Driven Approach to Kinematic Analysis in Running Using Wearable Technology. International Conference on Wearable & Implantable Body Sensor Networks. IEEE,9(12):118-123.
• Talukder, M. S., Chiong, R., Bao, Y., & Malik, B. H. (2019). Acceptance and use predictors of fitness wearable technology and intention to recommend An empirical study. Industrial Management & Data Systems, 119(1), 170-188.
• Tan Longjiang. (2012). Research on the adoption behavior of B2B online payment in my country's small and medium-sized enterprises (PhD dissertation, Southwestern University of Finance and Economics). https://kns.cnki.net/KCMS/detail/detail.aspx?dbname=CDFD1214&filename= 1012509622.nh
• Tang Xuli, Zhang Bin & Zhang Yan. (2018). A Study on Information Adoption Intention of Online Health Community Users: From the Perspective of Health Literacy and Trust. Journal of Information Resource Management (03), 102-112. doi:10.13365/ j.jirm.2018.03.102.
• Wang Jie, Chen Jianzhi & Gao Shuang. (2014). Compulsive shopping from the perspective of materialistic values: a meta-analysis. Chinese Journal of Clinical Psychology, (03), 451-456. doi: 10.16128/j.cnki .1005-3611.2014.03.062.
• Wang Wei. (2020). Research on the adoption behavior of health information of WeChat elderly users. International Press, (03), 91-107. doi: 10.13495/j.cnki.cjjc.20200409.006.
• Wang, N., Feng, Y. M., Zhang, S. k. (2018). The impact of innovation in specific fields on the adoption of new products by consumers-taking sports bracelets as an example. Technological Economy (12), 5-13.
• Wei Mingxia & Xiao Kaihong.(2006). Analysis of Perceived Factors Affecting B2C E-commerce Online Consumption Behavior. Technology Management Research, (06), 175-179.
• Wu Jiang, Li Shanshan, Hu Xian & Wang Lin. (2017). An Empirical Study on Influencing Factors of Health Wearable Device Users' Intention to Include. Journal of Information Resource Management (02), 22-30. doi:10.13365/j.jirm .2017.02.022.
• Wu Jiang, Zeng Minne, Liu Fuzhen & Zhao Yang. (2017). Research on the adoption behavior of wearable device users based on meta-analysis method. Journal of Information Resource Management, (02), 5-13. doi: 10.13365/j.jirm .2017.02.005.
• Yang, H., Yu, J., Zo, H., & Choi, M. (2016). User acceptance of wearable devices: An extended perspective of perceived value. Telematics and Informatics, 33(2), 256-269. Retrieved from ://WOS:000367776800002. doi:10.1016/j.tele.2015.08.007 [6]
• Zhang Xiaodan, Jiang Hong & Wang Kehui.(2018). An Empirical Study on Influencing Factors of Academic APP Users' Adoption Intention. Library and Information Work (18), 90-101. doi:10.13266/j.issn.0252-3116.2018.18.010.
• Zhang Yong, Wang Xu, Li Zhangyu.(2021). Research on the impact of quantified self on the willingness to continue using wearable devices. Sports Research and Education,36(03):90-96.
• Zhang, M., Luo, M., Nie, R., & Zhang, Y. (2017). Technical attributes, health attribute, consumer attributes and their roles in adoption intention of healthcare wearable technology. International Journal of Medical Informatics, 108, 97-109.
• Zhao Yansheng & Wang Zhongjie. (2018). Research on Wearable Device Users' Willingness to Use Continuously: An Extended Model Based on ECM-IS. Journal of Northeastern University (Social Science Edition), (04), 366-372. doi:10.15936/j .cnki.1008-3758.2018.04.006.
• Zhu Zhangxiang, Liu Yongmei & Cao Xianye.(2020). Influencing factors of mobile medical users' adoption intention based on meta-analysis. Journal of System Management (01), 49-60.

Identyfikatory

DOI

10.12775/QS.2022.08.01.005