Identifying the influence of obsolescence risk and health beliefs in fitness wearable healthcare technology
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This study aimed to examine factors influencing the adoption of fitness wearable technologies (FWTs) by extending the Unified Theory of Acceptance and Use of Technology (UTAUT2). A survey was conducted with 574 fitness wearable users in India to test a conceptual Fitness Wearable Adoption Model (FWAM) incorporating additional constructs of obsolescence risk, health belief, and perceived accuracy alongside UTAUT2 variables. Structural equation modeling revealed performance expectancy, effort expectancy, social influence, hedonic motivation, price value, health belief, and obsolescence risk positively affected adoption intentions, while perceived security had no effect. Perceived accuracy mediated the impact of performance expectancy, while price value mediated the relationship between obsolescence risk and intentions. The research makes key contributions by adapting UTAUT2 to a new context, integrating additional adoption factors, identifying mediating mechanisms, and revealing moderating effects of age. Findings provide valuable insights into consumer acceptance of fitness wearables that can inform strategies for manufacturers, marketers, and health practitioners to promote adoption. A major focus of the investigation is to develop strategies for increasing the adoption of wrist-worn fitness technology that provides an opportunity for fitness wearable technology manufacturers to strengthen relationships with older age groups through effective communication techniques.
Abstract
This study aimed to examine factors influencing the adoption of fitness wearable technologies (FWTs) by extending the Unified Theory of Acceptance and Use of Technology (UTAUT2). A survey was conducted with 574 fitness wearable users in India to test a conceptual Fitness Wearable Adoption Model (FWAM) incorporating additional constructs of obsolescence risk, health belief, and perceived accuracy alongside UTAUT2 variables. Structural equation modeling revealed performance expectancy, effort expectancy, social influence, hedonic motivation, price value, health belief, and obsolescence risk positively affected adoption intentions, while perceived security had no effect. Perceived accuracy mediated the impact of performance expectancy, while price value mediated the relationship between obsolescence risk and intentions. The research makes key contributions by adapting UTAUT2 to a new context, integrating additional adoption factors, identifying mediating mechanisms, and revealing moderating effects of age. Findings provide valuable insights into consumer acceptance of fitness wearables that can inform strategies for manufacturers, marketers, and health practitioners to promote adoption. A major focus of the investigation is to develop strategies for increasing the adoption of wrist-worn fitness technology that provides an opportunity for fitness wearable technology manufacturers to strengthen relationships with older age groups through effective communication techniques.
참고문헌 (99)
- Ajzen, I., "The theory of planned behavior", Organizational Behavior and Human Decision Processes, 50(2), pp.179~211 (1991)[DOI]
- Alalwan, A. A., "Examining factors influencing Jordanian customers’ intentions and adoption of internet banking : Extending UTAUT2 with risk", Journal of Retailing and Consumer Services, 40, pp.125~138 (2018)[DOI]
- Anderson, M., "Technology use among seniors" (2017), Pew Research Center for Internet & Technology
- Apasrawirote, D., "Digital marketing capability : The mystery of business capabilities", Marketing Intelligence & Planning, 40(4), pp.477~496 (2022)[DOI]
- Barkley, J. E., "The relationship between fitness app use and physical activity behavior is mediated by exercise identity", Computers in Human Behavior, 108, pp.106313~ (2020)[DOI]
- Baron, R. M., "The moderator–mediator variable distinction in social psychological research : Conceptual, strategic, and statistical considerations", Journal of Personality and Social Psychology, 51(6), pp.1173~1182 (1986)[DOI]
- Basoglu, N., "What will it take to adopt smart glasses : A consumer choice-based review", Technology in Society, 50(1), pp.50~56 (2017)[DOI]
- Bowlds, T. F., "Software obsolescence risk assessment approach using multicriteria decision‐making", Systems Engineering, 21(5), pp.455~465 (2018)[DOI]
- Chen, S. C., "Understanding the effect of social media marketing activities : The mediation of social identification, perceived value, and satisfaction", Technological Forecasting and Social Change, 140, pp.22~32 (2019)[DOI]
- Chi, T., "Understanding consumer perceived value of casual sportswear : An empirical study", Journal of Retailing and Consumer Services, 18(5), pp.422~429 (2011)[DOI]
- Chin, W. W., "Advancing the theory of adaptive structuration : The development of a scale to measure faithfulness of appropriation", Information Systems Research, 8(4), pp.342~367 (1997)[DOI]
- Cho, V., "How social influence through information adoption from online review sites affects collective decision-making", Enterprise Information Systems, 15(10), pp.1562~1586 (2021)[DOI]
- Chung, S. -W., "Technological expectation and consumer preferences for product form", Journal of Business Research, 65(9), pp.1290~1294 (2012)[DOI]
- Davis, F. D., "Perceived usefulness, perceived ease of use, and user acceptance of information technology", MIS Quarterly, 13(3), pp.319~340 (1989)[DOI]
- Dehghani, M., "Will smartwatches last? Factors contributing to intention to keep using smart wearable technology", Telematics and Informatics, 35(2), pp.480~490 (2018)[DOI]
- Devine, J. K., "Technical, regulatory, economic, and trust issues preventing successful integration of sensors into the mainstream consumer wearables market", Sensors, 22(7), pp.2731~ (2022)[DOI]
- Duarte, P., "A mixed methods UTAUT2-based approach to assess mobile health adoption", Journal of Business Research, 102, pp.140~150 (2019)[DOI]
- Dwivedi, Y. K., "Re-examining the unified theory of acceptance and use of technology(UTAUT) : Towards a revised theoretical model", Information Systems Frontiers, 21(3), pp.719~734 (2017)[DOI]
- Ertiö, T., "Consumerism in online health information search and selftracking devices", International Journal of Consumer Studies, 43(3), pp.245~252 (2019)
- Fan, W., "Investigating the impacting factors for the healthcare professionals to adopt artificial intelligence-based medical diagnosis support system(AIMDSS)", Annals of Operations Research, 294(1), pp.567~592 (2020)
- Feehan, L. M., "Accuracy of fitbit devices: Systematic review and narrative syntheses of quantitative data", JMIR MHealth and UHealth, 6(8), pp.e10527~ (2018)[DOI]
- Ferrer, R. A., "Risk perceptions and health behavior", Current Opinion in Psychology, 5, pp.85~89 (2015)[DOI]
- Gao, Y., "An empirical study of wearable technology acceptance in healthcare", Industrial Management & Data Systems, 115(9), pp.1704~1723 (2015)[DOI]
- Goldsmith, E. B., "Social influence and sustainability in households", International Journal of Consumer Studies, 35(2), pp.117~121 (2011)[DOI]
- Goutam, D., "Technology readiness and e-service quality–impact on purchase intention and loyalty", Marketing Intelligence & Planning, 40(2), pp.242~255 (2022)[DOI]
- Hackley, C., "Implications of the selfie for marketing management practice in the era of celebrity", Marketing Intelligence & Planning, 36(1), pp.49~62 (2018)[DOI]
- Hair, J. F., Jr, "A primer on partial least squares structural equation modeling (PLS-SEM)" (2016), Sage Publications
- Han, L., "The intention to adopt electric vehicles : Driven by functional and non-functional values", Transportation Research Part A : Policy and Practice, 103, pp.185~197 (2017)[DOI]
- Hartl, R. F., "Reputation or warranty, what is more effective against planned obsolescence", International Journal of Production Research, 61(3), pp.939~954 (2023)[DOI]
- Huang, Y., "Validity of fitbit, jawbone UP, nike+, and other wearable devices for level and stair walking", Gait & Posture, 48, pp.36~41 (2016)[DOI]
- Jayawardena, N. S., "Artificial Intelligence for Marketing Management", pp.120~141 (2022)
- Jayawardena, N. S., "Exploring the differential effects of consumer brand attitude persuasion for printed advertisements in luxury and nonluxury brands", Asia Pacific Journal of Marketing & Logistics (2023)[DOI]
- Jayawardena, N. S., "Luxury marketing, sustainability and technology", pp.1~14 (2023), Routledge
- Katoch, R., "Online spiritual meets(OSMs)and user behavior–A divine application of technology during COVID-19", Computers in Human Behavior, 139, pp.107514~ (2023)[DOI]
- Kim, T., "Consumer acceptance of sports wearable technology : The role of technology readiness", International Journal of Sports Marketing and Sponsorship, 20(1), pp.109~126 (2019)[DOI]
- Kim, T. B., "Validating the moderating role of age in the multi-perspective acceptance model of wearable healthcare technology", Telematics and Informatics, 61, pp.101603~ (2021)[DOI]
- Kim, J., "Beyond coolness : Predicting the technology adoption of interactive wearable devices", Journal of Retailing and Consumer Services, 49, pp.114~119 (2019)[DOI]
- Kline, R. B., "Principles and practice of structural equation modeling" (2011), Guilford Press
- Kumar, A., "The effect of perceived security and grievance redressal on continuance intention to use M-wallets in a developing country", International Journal of Bank Marketing, 36(7), pp.1170~1189 (2018)[DOI]
- Kuppelwieser, V. G., "Consumer responses to planned obsolescence", Journal of Retailing & Consumer Services, 47, pp.157~165 (2019)
- Lavuri, R., "Identifying factors influencing purchase intention of sustainable luxury retailing products", International Journal of Retail & Distribution Management (2023)[DOI]
- Lee, J. E., "Effects of price discount on consumers’ perceptions of savings, quality, and value for apparel products : Mediating effect of price discount affect", Fashion and Textiles, 5, pp.1~21 (2018)
- Lee, J., "Sustainable wearables : Wearable technology for enhancing the quality of human life", Sustainability, 8(5), pp.466~ (2016)[DOI]
- Lian, J. W., "Online shopping drivers and barriers for older adults : Age and gender differences", Computers in Human Behavior, 37, pp.133~143 (2014)
- Li, J., "Health monitoring through wearable technologies for older adults : Smart wearables acceptance model", Applied Ergonomics, 75(2018), pp.162~169 (2019)[DOI]
- Lima, V., "Non-dyadic human–robot interactions and online brand communities", Marketing Intelligence & Planning, 40(6), pp.724~737 (2022)[DOI]
- Liu, H., "Exploring the intention-behavior gap in the technology acceptance model : A mixed-methods study in the context of foreign-language teaching in China", British Journal of Educational Technology, 50(5), pp.2536~2556 (2019)[DOI]
- Li, H., "Examining individuals’ adoption of healthcare wearable devices : An empirical study from a privacy calculus perspective", International Journal of Medical Informatics, 88(555), pp.8~17 (2016)[DOI]
- Lunney, A., "Wearable fitness technology : A structural investigation into acceptance and perceived fitness outcomes", Computers in Human Behavior, 65, pp.114~120 (2016)[DOI]
- MacKenzie, S. B., "Common method bias in marketing : Causes, mechanisms, and procedural remedies", Journal of Retailing, 88(4), pp.542~555 (2012)[DOI]
- Miraz, M. H., "Trust, transaction transparency, volatility, facilitating condition, performance expectancy towards cryptocurrency adoption through intention to use", Journal of Management Information & Decision Sciences, 25(1), pp.1~20 (2022)
- Mishra, A., "Factors influencing actual usage of fitness tracking devices : Empirical evidence from the UTAUT model", Health Marketing Quarterly, 40(1), pp.1~20 (2022)[DOI]
- Mishra, U., "Luxury marketing, sustainability and technology", pp.92~115 (2023), Routledge
- Mohr, D. C., "Continuous evaluation of evolving behavioral intervention technologies", American Journal of Preventive Medicine, 45(4), pp.517~523 (2013)
- Moore, G. C., "Development of an instrument to measure the perceptions of adopting an information technology innovation", Information Systems Research, 2(3), pp.192~222 (1991)[DOI]
- Nasir, S., "Consumers’ and physicians’ perceptions about high-tech wearable health products", Procedia-Social and Behavioral Sciences, 195, pp.1261~1267 (2015)[DOI]
- Nunnally, J. C., "Psychometric theory (McGraw-hill series in psychology)(vol. 3)" (1994), McGraw-Hill
- Okazaki, S., "Exploring convenience in mobile commerce : Moderating effects of gender", Computers in Human Behavior, 29(3), pp.1234~1242 (2013)
- Pantano, E., "Obsolescence risk in advanced technologies for retailing : A management perspective", Journal of Retailing and Consumer Services, 20(2), pp.225~233 (2013)[DOI]
- Pirhonen, J., ""These devices have not been made for older people’s needs"–older adults’ perceptions of digital technologies in Finland and Ireland", Technology in Society, 62, pp.101287~ (2020)
- Podsakoff, P. M., "Sources of method bias in social science research and recommendations on how to control it", Annual Review of Psychology, 63(1), pp.539~569 (2012)[DOI]
- Preacher, K. J., "SPSS and SAS procedures for estimating indirect effects in simple mediation models", Behavior Research Methods, Instruments, & Computers, 36(4), pp.717~731 (2004)[DOI]
- Rahardjo, B., "The analysis of intention and use of financial technology", Journal of Accounting and Strategic Finance, 3(1), pp.88~102 (2020)[DOI]
- Rani, N., "Wearables can help me learn : A survey of user perception of wearable technologies for learning in everyday life", Education and Information Technologies, 27(3), pp.3381~3401 (2022)[DOI]
- Rashotte, L., "The Blackwell encyclopedia of sociology" (2007), Blackwell Publishing
- Reyes-Mercado, P., "Adoption of fitness wearables", Journal of Systems & Information Technology, 20(1), pp.103~127 (2018)[DOI]
- Reyes-Mercado, P., "Adoption of digital learning environments during the COVID-19pandemic : merging technology readiness index and UTAUT model", Journal of International Education in Business, 16(1), pp.91~114 (2022)[DOI]
- Rosenstock, I. M., "Why people use health services", The Milbank Memorial Fund Quarterly, 44(3), pp.94~127 (1966)[DOI]
- Sapp, S. G., "Examination of the health belief model to predict the dietary quality and body mass of adults", International Journal of Consumer Studies, 31(3), pp.189~194 (2007)[DOI]
- Saprikis, V., "A comparative study of users versus nonusers’behavioral intention towards M-banking apps’ adoption", Information, 13(1), pp.30~ (2022)[DOI]
- Schierz, P. G., "Understanding consumer acceptance of mobile payment services : An empirical analysis", Electronic Commerce Research and Applications, 9(3), pp.209~216 (2010)[DOI]
- Seyed Esfahani, M., "Impact of consumer innovativeness on really new product adoption", Marketing Intelligence & Planning, 39(4), pp.589~612 (2021)[DOI]
- Shaw, N., "The non-monetary benefits of mobile commerce : Extending UTAUT2 with perceived value", International Journal of Information Management, 45, pp.44~55 (2019)[DOI]
- Shin, D. -H., "The effects of trust, security, and privacy in social networking : A security-based approach to understand the pattern of adoption", Interacting with Computers, 22(5), pp.428~438 (2010)[DOI]
- Shin, G., "Wearable activity trackers, accuracy, adoption, acceptance, and health impact : A systematic literature review", Journal of Biomedical Informatics, 93, pp.103153~ (2019)[DOI]
- Sim, J. J., "Understanding and predicting the motivators of mobile music acceptance–a multi-stage MRA-artificial neural network approach", Telematics and Informatics, 31(4), pp.569~584 (2014)[DOI]
- Solomon, R., "Electronic part life cycle concepts and obsolescence forecasting", IEEE Transactions on Components and Packaging Technologies, 23(4), pp.707~717 (2000)[DOI]
- Soodan, V., "Modeling customers’ intention to use e-wallet in a developing nation : Extending UTAUT2 with security, privacy and savings", Journal of Electronic Commerce in Organizations(JECO), 18(1), pp.89~114 (2020)[DOI]
- Stevens, J. P., "Outliers and influential data points in regression analysis", Psychological Bulletin, 95(2), pp.334~ (1984)[DOI]
- Talukder, M. S., "Acceptance and use predictors of fitness wearable technology and intention to recommend : An empirical study", Industrial Management and Data Systems, 119(1), pp.170~188 (2019)[DOI]
- Tanner, C., "Promoting sustainable consumption : Determinants of green purchases by Swiss consumers", Psychology & Marketing, 20(10), pp.883~902 (2003)
- Tischleder, B. B., "Cultures of obsolescence: History, materiality, and the digital age" (2015), Palgrave Macmillan
- To, A. T., "Understanding behavioral intention to use mobile wallets in Vietnam : Extending the tam model with trust and enjoyment", Cogent Business & Management, 8(1), pp.1891661~ (2021)[DOI]
- Trabelsi, I., "FMECA-based risk assessment approach for proactive obsolescence management", IFIP International Conference on Product Lifecycle Management, pp.215~226 (2020), Springer
- Urbach, N., "Structural equation modeling in information systems research using partial least squares", JITTA : Journal of Information Technology Theory and Application, 11(2), pp.5~ (2010)
- Venkatesh, V., "Determinants of perceived ease of use : Integrating control, intrinsic motivation, and emotion into the technology acceptance model", Information Systems Research, 11(4), pp.342~365 (2000)[DOI]
- Venkatesh, V., "User acceptance of information technology : Toward a unified view", MIS Quarterly, 27(3), pp.425~478 (2003)[DOI]
- Venkatesh, V., "Consumer acceptance and use of information technology : Extending the unified theory of acceptance and use of technology", MIS Quarterly, 36(1), pp.157~178 (2012)[DOI]
- Vermeir, I., "Sustainable food consumption : Exploring the consumer"attitude–behavioral intention"gap", Journal of Agricultural & Environmental Ethics, 19, pp.169~194 (2006)
- Wang, Y. S., "Why do people use information kiosks? A validation of the unified theory of acceptance and use of technology", Government Information Quarterly, 26(1), pp.158~165 (2009)[DOI]
- Wang, J., "Structural equation modeling: Applications using M plus" (2012), John Wiley & Sons Ltd
- Wang, Y. S., "Determinants of user acceptance of Internet banking : An empirical study", International Journal of Service Industry Management, 14(5), pp.501~519 (2003)[DOI]
- Wu, J., "Toward a better understanding of behavioral intention and system, usage constructs", European Journal of Information Systems, 21(6), pp.680~698 (2012)[DOI]
- Yap, S. F., "Coping with crisis : The paradox of technology and consumer vulnerability", International Journal of Consumer Studies, 45(6), pp.1239~1257 (2021)[DOI]
- Yeoh, S. Y., "Exploring home health-care robots adoption in Malaysia : Extending the UTAUT model", International Journal of Pharmaceutical and Healthcare Marketing, 16(3), pp.392~411 (2022)[DOI]
- Yoganathan, D., "Creating value for all through IT conference", pp.179~196 (2014), Springer
- Zhang, T., "Analyzing the diffusion of competitive smart wearable devices : An agent-based multi-dimensional relative agreement model", Journal of Business Research, 139, pp.90~105 (2022)[DOI]
- Zhao, X., Jr, "Reconsidering Baron and Kenny : Myths and truths about mediation analysis", The Journal of Consumer Research, 37(2), pp.197~206 (2010)[DOI]
- Zhao, Y., "What factors influence the mobile health service adoption? A meta-analysis and the moderating role of age", International Journal of Information Management, 43, pp.342~350 (2018)
