研究生: |
傅佳柔 Fu, Jia-Rou |
---|---|
論文名稱: |
以隱私計算理論探討消費者對於智慧穿戴裝置的持續使用意圖及幸福感 Examining consumer continuance intention and well-being of smart wearable device:A privacy calculus theory approach. |
指導教授: |
盧筱涵
Lu, Hsiao-Han |
學位類別: |
碩士 Master |
系所名稱: |
管理學院 - 電信管理研究所 Institute of Telecommunications Management |
論文出版年: | 2024 |
畢業學年度: | 112 |
語文別: | 中文 |
論文頁數: | 131 |
中文關鍵詞: | 智慧穿戴裝置 、功利價值 、享樂價值 、隱私計算理論 、持續使用意圖 、享樂幸福感 、生活意義幸福感 |
外文關鍵詞: | Smart wearable devices, utilitarian value, hedonic value, privacy calculus theory, continuance intention, hedonic well-being, eudaimonic well-being |
相關次數: | 點閱:60 下載:0 |
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網路文獻
Statista(2023)。Number of connected wearable devices worldwide from 2019 to 2022。2023年5月15日,取自:https://www.statista.com/statistics/487291/global-connected-wearable-devices/
Statista(2023)。Revenue of the smartwatches market worldwide from 2018 to 2027。2023年8月9日,取自:https://www.statista.com/forecasts/1314322/worldwide-revenue-of-smartwatch-market
OUTLOOK科技發展觀測平台(2020):預測至2025年全球穿戴式健康照護裝置市場。2020年9月26日,取自:https://outlook.stpi.narl.org.tw/index/focus-news/4b11410074b45a860174c813404365de
IEK產業情報網(2022):蓋德獲利創新高 迎智慧穿戴商機。2022年6月23日,取自https://ieknet.iek.org.tw/ieknews/news_detail.aspx?actiontype=ieknews&indu_idno=1&nsl_id=963063b0deb74aa380d3051a3639b142
數位時代(2015):Apple Watch三大殺手應用搶先看。2015年1月21日,取自: https://www.bnext.com.tw/article/35068/BN-ARTICLE-35068
數位時代(2023):華為Watch Buds內藏超迷你耳機、小米手環打Switch拳擊,新款智慧錶亮點一次看。2023年6月9日,取自:https://www.bnext.com.tw/article/75557/smart-watch-huawei-xiaomi
iThome(2016):改變生活的16個IoT應用。2016年6月12日,取自:https://www.ithome.com.tw/news/106444
英文文獻
Acquisti, A., Adjerid, I., & Brandimarte, L. (2013). Gone in 15 seconds: The limits of privacy transparency and control. IEEE Security & Privacy, 11(4), 72–74.
Agarwal, H., & Karim, S. F. (2015). An investigation into the factors affecting the consumer’s behavioral intention towards mobile coupon redemption. Advances in Economic and Business Management (AEBM), 2(13), 1311-1315.
Ahn, H., & Park, E. (2022). Determinants of consumer acceptance of mobile healthcare devices: An application of the concepts of technology acceptance and coolness. Telematics and Informatics, 70, 101810.
Alalwan, A. A., Baabdullah, A. M., Rana, N. P., Tamilmani, K., & Dwivedi, Y. K. (2018). Examining adoption of mobile internet in Saudi Arabia: Extending TAM with perceived enjoyment, innovativeness and trust. Technology in Society, 55, 100-110.
Alemany, J., Del Val, E., & Garcia-Fornes, A. M. (2021). “Who should I grant access to my post?”: Identifying the most suitable privacy decisions on online social networks. Internet Research, 31(4), 1290-1317.
Al-Emran, M., Al-Maroof, R., Al-Sharafi, M.A. and Arpaci, I. (2020), “What impacts learning with wearables? An integrated theoretical model”, Interactive Learning Environments, pp. 1-21.
Al‐Nabhani, K., Wilson, A., & McLean, G. (2022). Examining consumers' continuous usage of multichannel retailers' mobile applications. Psychology & Marketing, 39(1), 168-195.
Allmendinger, G., & Lombreglia, R. (2005). Four strategies for the age of smart services. Harvard Business Review, 83(10), 131.
Altman, Irwin. "The environment and social behavior: privacy, personal space, territory, and crowding." (1975).
Altmann, S., Milsom, L., Zillessen, H., Blasone, R., Gerdon, F., Bach, R., ... & Abeler, J. (2020). Acceptability of app-based contact tracing for COVID-19: Cross-country survey study. JMIR mHealth and uHealth, 8(8), e19857.
Ameen, N., Hosany, S., & Taheri, B. (2023). Generation Z's psychology and new‐age technologies: Implications for future research. Psychology & Marketing, 40(10), 2029-2040.
Anderson, C.L., and Agarwal, R. Practicing safe computing: A multimethod empirical examination of home computer user security behavioral intentions. MIS Quarterly, 34, 3(2010), 613–643.
Anderson, C. L., & Agarwal, R. (2011). The digitization of healthcare: boundary risks, emotion, and consumer willingness to disclose personal health information. Information Systems Research, 22(3), 469-490.
Arnold, M. J., & Reynolds, K. E. (2003). Hedonic shopping motivations. Journal of Retailing, 79(2), 77-95.
Ashfaq, M., Yun, J., & Yu, S. (2021). My smart speaker is cool! perceived coolness, perceived values, and users’ attitude toward smart speakers. International Journal of Human–Computer Interaction, 37(6), 560-573
Attié, E., & Meyer-Waarden, L. (2022). The acceptance and usage of smart connected objects according to adoption stages: an enhanced technology acceptance model integrating the diffusion of innovation, uses and gratification and privacy calculus theories. Technological Forecasting and Social Change, 176, 121485.
Aw, E. C. X., Tan, G. W. H., Chuah, S. H. W., Ooi, K. B., & Hajli, N. (2022). Be my friend! Cultivating parasocial relationships with social media influencers: findings from PLS-SEM and fsQCA. Information Technology & People, 36(1), 66-94.
Ayadi, N., Paraschiv, C., & Vernette, E. (2017). Increasing consumer well-being: Risk as potential driver of happiness. Applied Economics, 49(43), 4321-4335.
Babin, B. J., Darden, W. R., & Griffin, M. (1994). Work and/or fun: measuring hedonic and utilitarian shopping value. Journal of Consumer Research, 20(4), 644-656.
Batra, R., & Ahtola, O. T. (1991). Measuring the hedonic and utilitarian sources of consumer attitudes. Marketing Letters, 2, 159-170.
Benlian, A., Klumpe, J., & Hinz, O. (2020). Mitigating the intrusive effects of smart home assistants by using anthropomorphic design features: A multimethod investigation. Information Systems Journal, 30(6), 1010-1042.
Berridge, K. C., & Kringelbach, M. L. (2008). Affective neuroscience of pleasure: reward in humans and animals. Psychopharmacology, 199, 457-480.
Bhandari, U., Chang, K., & Neben, T. (2019). Understanding the impact of perceived visual aesthetics on user evaluations: An emotional perspective. Information & Management, 56(1), 85-93.
Bhatia, J., & Breaux, T. D. (2018). Empirical measurement of perceived privacy risk. ACM Transactions on Computer-Human Interaction (TOCHI), 25(6), 1-47.
Bhattacherjee, A., & Lin, C. P. (2015). A unified model of IT continuance: three complementary perspectives and crossover effects. European Journal of Information Systems, 24(4), 364-373.
Biswas, B., & Mukhopadhyay, A. (2018). G-RAM framework for software risk assessment and mitigation strategies in organisations. Journal of Enterprise Information Management, 31(2), 276–299.
Bloch, P. H., Brunel, F. F., & Arnold, T. J. (2003). Individual differences in the centrality of visual product aesthetics: Concept and measurement. Journal of Consumer Research, 29(4), 551-565.
Brown, G., Lawrence, T. B., and Robinson, S. L. 2005. “Territoriality in Organizations,” Academy of Management Review (30:3), pp. 577-594
Cazier, J. A., Jensen, A. S., & Dave, D. S. (2008). The impact of consumer perceptions of information privacy and security risks on the adoption of residual RFID technologies. Communications of the Association for Information Systems, 23(1), 14.
Chen, C. C., Han, J., & Wang, Y. C. (2022). A hotel stay for a respite from work? Examining recovery experience, rumination and well-being among hotel and bed-and-breakfast guests. International Journal of Contemporary Hospitality Management, 34(4), 1270-1289.
Cheng, X., Hou, T., & Mou, J. (2021). Investigating perceived risks and benefits of information privacy disclosure in IT-enabled ride-sharing. Information & Management, 58(6), 103450.
Cheng, X., Su, L., Luo, X., Benitez, J., & Cai, S. (2022). The good, the bad, and the ugly: Impact of analytics and artificial intelligence-enabled personal information collection on privacy and participation in ridesharing. European Journal of Information Systems, 31(3), 339-363.
Cheng, Y. M. (2015). Towards an understanding of the factors affecting m-learning acceptance: Roles of technological characteristics and compatibility. Asia Pacific Management Review, 20(3), 109–119.
Chi, O. H., Denton, G., & Gursoy, D. (2020). Artificially intelligent device use in service delivery: A systematic review, synthesis, and research agenda. Journal of Hospitality Marketing & Management, 29(7), 757-786.
Chiu, C. M., Cheng, H. L., Huang, H. Y., & Chen, C. F. (2013). Exploring individuals’ subjective well-being and loyalty towards social network sites from the perspective of network externalities: The Facebook case. International Journal of Information Management, 33(3), 539-552.
Cho, H., Ippolito, D. and Yu, Y.W. (2020), Contact Tracing Mobile Apps for COVID-19: Privacy Considerations and Related Trade-Offs, ArXiv Preprint ArXiv:2003.11511.
Cho, W. C., Lee, K. Y., & Yang, S. B. (2019). What makes you feel attached to smartwatches? The stimulus–organism–response (S–O–R) perspectives. Information Technology & People, 32(2), 319-343.
Choi J., Kim S. (2016). Is the smartwatch an IT product or a fashion product? A study on factors affecting the intention to use smartwatches. Computers in Human Behavior, 63, 777–786.
Chuah, S. H. W. (2019). You inspire me and make my life better: Investigating a multiple sequential mediation model of smartwatch continuance intention. Telematics and Informatics, 43, 101245.
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.
Cichy, P., Salge, T. O., & Kohli, R. (2021). Privacy concerns and data sharing in the internet of things:mixed methods evidence from connected cars. MIS Quarterly, 45(4).
Culnan, M. J. (1993). " How did they get my name?": An exploratory investigation of consumer attitudes toward secondary information use. MIS Quarterly, 341-363.
Culnan, M. J., & Armstrong, P. K. (1999). Information privacy concerns, procedural fairness, and impersonal trust: An empirical investigation. Organization Science, 10(1), 104-115.
Culnan, M. J., & Bies, R. J. (2003). Consumer privacy: Balancing economic and justice considerations. Journal of Social Issues, 59(2), 323-342.
Cyr, D. (2008). Modeling web site design across cultures: relationships to trust, satisfaction, and e-loyalty. Journal of Management Information Systems, 24(4), 47-72.
Cyr, D., Head, M., & Ivanov, A. (2006). Design aesthetics leading to m-loyalty in mobile commerce. Information & Management, 43(8), 950-963.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319-340.
Dehghani, M., & Kim, K. J. (2019). Past and present research on wearable technologies: bibliometric and cluster analyses of published research from 2000 to 2016. International Journal of Innovation and Technology Management, 16(01), 1950007.
Dehghani, M., Kim, K. J., & Dangelico, R. M. (2018). Will smartwatches last? Factors contributing to intention to keep using smart wearable technology. Telematics and Informatics, 35(2), 480-490.
Delgosha, M. S., & Hajiheydari, N. (2021). How human users engage with consumer robots? A dual model of psychological ownership and trust to explain post-adoption behaviours. Computers in Human Behavior, 117, 106660.
Dimitropoulos, P. E., & Asteriou, D. (2010). The effect of board composition on the informativeness and quality of annual earnings: Empirical evidence from Greece. Research in International Business and Finance, 24(2), 190-205.
Duan, S. X., & Deng, H. (2022). Exploring privacy paradox in contact tracing apps adoption. Internet Research, 32(5), 1725-1750.
Ernst, C. P., & Ernst, A. (2016). The Influence of Privacy Risk on Smartwatch Usage. In: Americas Conference on Information Systems.
Etkin, J. (2016). The hidden cost of personal quantification. Journal of Consumer Research, 42(6), 967-984.
Evelina, T. Y., Kusumawati, A., & Nimran, U. (2020). The influence of utilitarian value, hedonic value, social value, and perceived risk on customer satisfaction: survey of e-commerce customers in Indonesia. Business: Theory and Practice, 21(2), 613-622.
Fiss, P. C. (2011). Building better causal theories: A fuzzy set approach to typologies in organization research. Academy of Management Journal, 54(2), 393-420.
Gao, Y., Li, H., & Luo, Y. (2015). An empirical study of wearable technology acceptance in healthcare. Industrial Management & Data Systems, 115(9), 1704-1723.
Gu, J., Tian, J., & Xu, Y. C. (2022). Private or not? The categorical differences in mobile users’ privacy decision-making. Electronic Commerce Research and Applications, 52, 101122.
Guo, X., Zhang, X., & Sun, Y. (2016). The privacy–personalization paradox in mHealth services acceptance of different age groups. Electronic Commerce Research and Applications, 16, 55-65.
Gupta, A., Dhiman, N., Yousaf, A., & Arora, N. (2020). Social comparison and continuance intention of smart fitness wearables: an extended expectation confirmation theory perspective. Behaviour & Information Technology, 1-14.
Guzzo, R. F., Wang, X., & Abbott, J. (2022). Corporate social responsibility and individual outcomes: the mediating role of gratitude and compassion at work. Cornell Hospitality Quarterly, 63(3), 350-368.
Hasan, R., Shams, R., & Rahman, M. (2021). Consumer trust and perceived risk for voice-controlled artificial intelligence: The case of Siri. Journal of Business Research, 131, 591-597.
Hayes, D. R., Snow, C., & Altuwayjiri, S. (2017). Geolocation tracking and privacy issues associated with the uber mobile application. In Proceedings of The Conference on Information Systems Applied Research ISSN .
Hirschman, E. C., & Holbrook, M. B. (1982). Hedonic consumption: emerging concepts, methods and propositions. Journal of Marketing, 46(3), 92-101.
Hoadley, C. M., Xu, H., Lee, J. J., & Rosson, M. B. (2010). Privacy as information access and illusory control: The case of the Facebook News Feed privacy outcry. Electronic Commerce Rresearch and Applications, 9(1), 50-60.
Hofstede, G., & Bond, M. H. (1984). Hofstede's culture dimensions: An independent validation using Rokeach's value survey. Journal of Cross-Cultural Psychology, 15(4), 417-433.
Hong, J. C., Lin, P. H., & Hsieh, P. C. (2017). The effect of consumer innovativeness on perceived value and continuance intention to use smartwatch. Computers in Human Behavior, 67, 264-272.
Horton, M., Read, J. C., Fitton, D., Little, L., & Toth, N. (2012). Too cool at school-understanding cool teenagers. PsychNology Journal, 10(2), 73-91.
Hsee, C. K., Yang, Y., Li, N., & Shen, L. (2009). Wealth, warmth, and well-being: Whether happiness is relative or absolute depends on whether it is about money, acquisition, or consumption. Journal of Marketing Research, 46(3), 396-409.
Hsiao, K. L. (2013). Android smartphone adoption and intention to pay for mobile internet: Perspectives from software, hardware, design, and value. Library Hi Tech, 31(2), 216-235.
Hsiao, K. L., & Chen, C. C. (2018). What drives smartwatch purchase intention? Perspectives from hardware, software, design, and value. Telematics and Informatics, 35(1), 103-113.
Hsu, C. L., & Lin, J. C. C. (2016). An empirical examination of consumer adoption of Internet of Things services: Network externalities and concern for information privacy perspectives. Computers in Human Behavior, 62, 516-527.
Hsu, C. L., & Lin, J. C. C. (2018). Exploring factors affecting the adoption of internet of things services. Journal of Computer Information Systems, 58(1), 49-57.
Jian, Y., Zhou, Z., & Zhou, N. (2019). Brand cultural symbolism, brand authenticity, and consumer well-being: the moderating role of cultural involvement. Journal of Product & Brand Management, 28(4), 529-539.
Karapanos, E., Gouveia, R., Hassenzahl, M., & Forlizzi, J. (2016). Wellbeing in the making: Peoples’ experiences with wearable activity trackers. Psychology of Well-Being, 6(1), 4.
Keith, M. J., Thompson, S. C., Hale, J., Lowry, P. B., & Greer, C. (2013). Information disclosure on mobile devices: Re-examining privacy calculus with actual user behavior. International Journal of Human-Computer Studies, 71(12), 1163-1173.
Ketelaar, P. E., and M. van Balen. 2018. The smartphone as your follower: The role of smartphone literacy in the relation between privacy concerns, attitude and behaviour towards phoneembedded tracking. Computers in Human Behavior 78: 174–82.
Kim, B. (2010). An empirical investigation of mobile data service continuance: Incorporating the theory of planned behavior into the expectation–confirmation model. Expert Systems with Applications, 37(10), 7033-7039.
Kim, B., & Han, I. (2009). What drives the adoption of mobile data services? An approach from a value perspective. Journal of Information Technology, 24(1), 35-45.
Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44(2), 544-564.
Kim, D., Park, K., Park, Y., & Ahn, J. H. (2019). Willingness to provide personal information: Perspective of privacy calculus in IoT services. Computers in Human Behavior, 92, 273-281.
Kim, H. W., Chan, H. C., & Gupta, S. (2007). Value-based adoption of mobile internet: an empirical investigation. Decision Support Systems, 43(1), 111–126.
Kim, H. W., Kankanhalli, A., & Lee, H. L. (2016). Investigating decision factors in mobile application purchase: A mixed-methods approach. Information & Management, 53(6), 727-739.
Kim, J., & Park, E. (2019). Beyond coolness: Predicting the technology adoption of interactive wearable devices. Journal of Retailing and Consumer Services, 49, 114-119.
Kim, K. J., & Shin, D. H. (2015). An acceptance model for smart watches: Implications for the adoption of future wearable technology. Internet Research, 25(4), 527-541.
Kim, M. (2021). Conceptualization of e-servicescapes in the fitness applications and wearable devices context: Multi-dimensions, consumer satisfaction, and behavioral intention. Journal of Retailing and Consumer Services, 61, 102562.
Kim, Y. J., & Sim, J. B. (2012). Acceptance‐Diffusion Strategies for Tablet‐PCs: Focused on Acceptance Factors of Non‐Users and Satisfaction Factors of Users. Etri Journal, 34(2), 245-255.
Kim, D., Park, K., Park, Y., & Ahn, J. H. (2019). Willingness to provide personal information: Perspective of privacy calculus in IoT services. Computers in Human Behavior, 92, 273-281.
Kordzadeh, N. (2014). Communicating personal health information in virtual health communities: An integration of privacy calculus model and affective commitment. The University of Texas at San Antonio.
Korman, A. K. 1970. “Toward an Hypothesis of Work Behavior,” Journal of Applied Psychology (54:1), pp. 31-43.
Krey, N., Chuah, S., Ramayah, T., & Rauschnabel, P. (2019). How functional and emotional ads drive smartwatch adoption: the moderating role of consumer innovativeness and extraversion. Internet Research, 29(3), 578–602.
Laufer, R. S., & Wolfe, M. (1977). Privacy as a concept and a social issue: A multidimensional developmental theory. Journal of Social Issues, 33(3), 22-42.
Lavado-Nalvaiz, N., Lucia-Palacios, L., & Pérez-López, R. (2022). The role of the humanisation of smart home speakers in the personalisation–privacy paradox. Electronic Commerce Research and Applications, 53, 101146.
Lee, E. J. (2022). Do tech products have a beauty premium? The effect of visual aesthetics of wearables on willingness-to-pay premium and the role of product category involvement. Journal of Retailing and Consumer Services, 65, 102872.
Lee, K. Y., Sheehan, L., Lee, K., & Chang, Y. (2021). The continuation and recommendation intention of artificial intelligence-based voice assistant systems (AIVAS): the influence of personal traits. Internet Research, 31(5), 1899-1939.
Li, C., Shi, X., & Dang, J. (2014). Online communication and subjective well-being in Chinese college students: The mediating role of shyness and social self-efficacy. Computers in Human Behavior, 34, 89-95.
Li, H., Wu, J., Gao, Y., & Shi, Y. (2016). Examining individuals’ adoption of healthcare wearable devices: An empirical study from privacy calculus perspective. International Journal of Medical Informatics, 88, 8-17.
Li, M., Yin, D., Qiu, H., & Bai, B. (2022). Examining the effects of AI contactless services on customer psychological safety, perceived value, and hospitality service quality during the COVID‐19 pandemic. Journal of Hospitality Marketing & Management, 31(1), 24-48.
Li, H., Sarathy, R., & Xu, H. (2011). The role of affect and cognition on online consumers' decision to disclose personal information to unfamiliar online vendors. Decision Support Systems, 51(3), 434-445.
Li, T., Cobb, C., Yang, J. J., Baviskar, S., Agarwal, Y., Li, B., ... & Hong, J. I. (2021). What makes people install a COVID-19 contact-tracing app? Understanding the influence of app design and individual difference on contact-tracing app adoption intention. Pervasive and Mobile Computing, 75, 101439.
Lin, F. R., & Windasari, N. A. (2019). Continued use of wearables for wellbeing with a cultural probe. The Service Industries Journal, 39(15-16), 1140-1166.
Lu, H. H., & Chen, C. F. (2023). How do influencers’ characteristics affect followers’ stickiness and well-being in the social media context?. Journal of Services Marketing, 37(8), 1046-1058.
Magni, D., Scuotto, V., Pezzi, A., & Del Giudice, M. (2021). Employees’ acceptance of wearable devices: Towards a predictive model. Technological Forecasting and Social Change, 172, 121022.
Malhotra, N. K., Kim, S. S., & Agarwal, J. (2004). Internet users' information privacy concerns (IUIPC): The construct, the scale, and a causal model. Information Systems Research, 15(4), 336–355.
McAlister, L., & Pessemier, E. (1982). Variety seeking behavior: An interdisciplinary review. Journal of Consumer research, 9(3), 311-322.
McLean, G., Al-Nabhani, K., & Marriott, H. (2022). Regrettable-escapism- the negative effects of mobile app use: A retail perspective. Psychology & Marketing, 39(1), 150-167.
Merhi, M., Hone, K., Tarhini, A., & Ameen, N. (2021). An empirical examination of the moderating role of age and gender in consumer mobile banking use: a cross-national, quantitative study. Journal of Enterprise Information Management, 34(4), 1144-1168.
Mills, A. J., Watson, R. T., Pitt, L., & Kietzmann, J. (2016). Wearing safe: Physical and informational security in the age of the wearable device. Business Horizons, 59(6), 615-622.
Nascimento, B., Oliveira, T., & Tam, C. (2018). Wearable technology: what explains continuance intention in smartwatches? Journal of Retailing and Consumer Services, 43, 157–169.
Olivero, N., & Lunt, P. (2004). Privacy versus willingness to disclose in e-commerce exchanges: The effect of risk awareness on the relative role of trust and control. Journal of Economic Psychology, 25(2), 243–262.
Palmer, J. W. (2002). Web site usability, design, and performance metrics. Information Systems Research, 13(2), 151-167.
Papa, A., Mital, M., Pisano, P., & Del Giudice, M. (2020). E-health and wellbeing monitoring using smart healthcare devices: An empirical investigation. Technological Forecasting and Social Change, 153, 119226.
Park, K., Kwak, C., Lee, J., & Ahn, J. H. (2018). The effect of platform characteristics on the adoption of smart speakers: Empirical evidence in South Korea. Telematics and Informatics, 35(8), 2118-2132.
Patel, M. S., Asch, D. A., & Volpp, K. G. (2015). Wearable devices as facilitators, not drivers, of health behavior change. Jama, 313(5), 459-460.
Pentina, I., Zhang, L., Bata, H., & Chen, Y. (2016). Exploring privacy paradox in information-sensitive mobile app adoption: A cross-cultural comparison. Computers in Human Behavior, 65, 409-419.
Phelps, J., G. Nowak, and E. Ferrell. 2000. Privacy concerns and consumer willingness to provide personal information. Journal of Public Policy & Marketing 19, no. 1: 27–41.
Pierce, J. L., Kostova, T., and Dirks, K. T. 2003. “The State of Psychological Ownership: Integrating and Extending a Century of Research,” Review of General Psychology (7:1), pp. 84-107
Ragin, C. C., Strand, S. I., & Rubinson, C. (2008). User’s guide to fuzzy-set/qualitative comparative analysis. University of Arizona, 87, 1-87.
Rasoolimanesh, S. M., Ringle, C. M., Sarstedt, M., & Olya, H. (2021). The combined use of symmetric and asymmetric approaches: partial least squares-structural equation modeling and fuzzy-set qualitative comparative analysis. International Journal of Contemporary Hospitality Management, 33(5), 1571-1592.
Ratneshwar, S., Shocker, A. D., Cotte, J., & Srivastava, R. K. (1999). Product, person, and purpose: putting the consumer back into theories of dynamic market behaviour. Journal of Strategic Marketing, 7(3), 191-208.
Rauschnabel, P. A., He, J., & Ro, Y. K. (2018). Antecedents to the adoption of augmented reality smart glasses: A closer look at privacy risks. Journal of Business Research, 92, 374-384.
Rauschnabel, P. A., Hein, D. W., He, J., Ro, Y. K., Rawashdeh, S., & Krulikowski, B. (2016). Fashion or technology? A fashnology perspective on the perception and adoption of augmented reality smart glasses. I-Com, 15(2), 179-194.
Rogers, E. M. (1995). Diffusion of innovations (4th ed.). Free Press.
Rosenfeld, L. and Morville, P. (2002), Information Architecture for the World Wide Web, 2nd ed., O'Reilly & Associates, Sebastopol, California.
Rozanski, A., & Kubzansky, L. D. (2005). Psychologic functioning and physical health: a paradigm of flexibility. Psychosomatic medicine, 67, S47-S53.
Seiderer, A., Ritschel, H., & André, E. (2020, September). Development of a privacy-by-design speech assistant providing nutrient information for German seniors. In Proceedings of the 6th EAI International Conference on Smart Objects and Technologies for Social Good (pp. 114-119).
Sheng, H., Nah, F. F. H., & Siau, K. (2008). An experimental study on ubiquitous commerce adoption: Impact of personalization and privacy concerns. Journal of the Association for Information Systems, 9(6), 1.
Siepmann, C., & Kowalczuk, P. (2021). Understanding continued smartwatch usage: the role of emotional as well as health and fitness factors. Electronic Markets, 31(4), 795-809.
Smith, H. J., Dinev, T., & Xu, H. (2011). Information privacy research: an interdisciplinary review. MIS Quarterly, 989-1015.
Smith, H. J., Milberg, S. J., and Burke, S. J. 1996. “Information Privacy: Measuring Individuals’ Concerns about Organizational Practices,” MIS Quarterly (20:2), pp. 167-196.
Srivastava, N. K., Chatterjee, N., Subramani, A. K., Akbar Jan, N., & Singh, P. K. (2022). Is health consciousness and perceived privacy protection critical to use wearable health devices? Extending the model of goal-directed behavior. Benchmarking: An International Journal, 29(10), 3079-3096.
Su, R., Tay, L., & Diener, E. (2014). The development and validation of the Comprehensive Inventory of Thriving (CIT) and the Brief Inventory of Thriving (BIT). Applied Psychology: Health and Well‐Being, 6(3), 251-279.
Talukder, M. S., Laato, S., Islam, A. N., & Bao, Y. (2021). Continued use intention of wearable health technologies among the elderly: an enablers and inhibitors perspective. Internet Research, 31(5), 1611-1640.
Talukder, M. S., Sorwar, G., Bao, Y., Ahmed, J. U., & Palash, M. A. S. (2020). Predicting antecedents of wearable healthcare technology acceptance by elderly: A combined SEM-Neural Network approach. Technological Forecasting and Social Change, 150, 119793.
Tarafdar, M., Tu, Q., & Ragu-Nathan, T. S. (2010). Impact of technostress on end-user satisfaction and performance. Journal of Management Information Systems, 27(3), 303–334.
Turhan, G. (2013). An assessment towards the acceptance of wearable technology to consumers in Turkey: the application to smart bra and t-shirt products. Journal of the Textile Institute, 104(4), 375-395.
Venkatesh, V., Thong, J. Y., & Xu, X. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of The Association for Information Systems, 17(5), 328-376.
Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Quarterly, 157-178.
Verkijika, S. F. (2018). Factors influencing the adoption of mobile commerce applications in Cameroon. Telematics and Informatics, 35(6), 1665-1674.
Wang, T., Duong, T. D., & Chen, C. C. (2016). Intention to disclose personal information via mobile applications: A privacy calculus perspective. International Journal of Information Management, 36(4), 531-542.
Wang, X., White, L., Chen, X., Gao, Y., Li, H. and Luo, Y. (2015), “An empirical study of wearable technology acceptance in healthcare”, Industrial Management and Data Systems, 115(9), 1704-1723.
Waterman, A. S., Schwartz, S. J., & Conti, R. (2008). The implications of two conceptions of happiness (hedonic enjoyment and eudaimonia) for the understanding of intrinsic motivation. Journal of Happiness Studies, 9, 41-79.
Whelan, E., & Clohessy, T. (2021). How the social dimension of fitness apps can enhance and undermine wellbeing: A dual model of passion perspective. Information Technology & People, 34(1), 68-92.
Wiegard, R. B., & Breitner, M. H. (2019). Smart services in healthcare: A risk-benefit-analysis of pay-as-you-live services from customer perspective in Germany. Electronic Markets, 29, 107-123.
Wu, L. H., Wu, L. C., & Chang, S. C. (2016). Exploring consumers’ intention to accept smartwatch. Computers in Human Behavior, 64, 383–392.
Xu, F., Michael, K., & Chen, X. (2013). Factors affecting privacy disclosure on social network sites: an integrated model. Electronic Commerce Research, 13(2), 151-168.
Xu, H., Dinev, T., Smith, J., & Hart, P. (2011). Information privacy concerns: Linking individual perceptions with institutional privacy assurances. Journal of the Association for Information Systems, 12(12), 1.
Xu, H., Teo, H. H., Tan, B. C., & Agarwal, R. (2009). The role of push-pull technology in privacy calculus: the case of location-based services. Journal of Management Information Systems, 26(3), 135-174.
Xu, H., Teo, H. H., Tan, B. C., & Agarwal, R. (2012). Research note—Effects of individual self-protection, industry self-regulation, and government regulation on privacy concerns: a study of location-based services. Information Systems Research, 23(4), 1342–1363.
Xu, H., Luo, X. R., Carroll, J. M., & Rosson, M. B. (2011). The personalization privacy paradox: An exploratory study of decision making process for location-aware marketing. Decision Support Systems, 51(1), 42-52.
Xu, H., Teo, H.-H., Tan, B.C.Y. and Agarwal, R. (2012b), “Effects of individual self-protection, industry self-regulation, and government regulation on privacy concerns: a study of location-based services”, Information Systems Research, 23(4), 1342-1363.
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.
Yoon, S. J. (2014). Does social capital affect SNS usage? A look at the roles of subjective well-being and social identity. Computers in Human Behavior, 41, 295-303.
Zhan, G., & Zhou, Z. (2018). Mobile internet and consumer happiness: the role of risk. Internet Research, 28(3), 785-803.
Zhang, X., Liu, S., Chen, X., Wang, L., Gao, B., & Zhu, Q. (2018). Health information privacy concerns, antecedents, and information disclosure intention in online health communities. Information & Management, 55(4), 482-493.
Zhu, M., Wu, C., Huang, S., Zheng, K., Young, S. D., Yan, X., & Yuan, Q. (2021). Privacy paradox in mHealth applications: An integrated elaboration likelihood model incorporating privacy calculus and privacy fatigue. Telematics and Informatics, 61, 101601.
Zhu, Y., Lu, Y., Gupta, S., Wang, J., & Hu, P. (2023). Promoting smart wearable devices in the health-AI market: the role of health consciousness and privacy protection. Journal of Research in Interactive Marketing, 17(2), 257-272.
Ziamou, P., & Ratneshwar, S. (2002). Promoting consumer adoption of high‐technology products: Is more information always better?. Journal of Consumer Psychology, 12(4), 341-351