Abstract
The recent boom in wearable technologies generates enormous vital data sets, which are the ideal starting point for new service offers by Big Data Analytics. In a Pay-As-You-Live (PAYL) service, insured track activities, transfer current data on the lifestyles of users, who receive rewards from their insurance companies. The aim of this study is to investigate the readiness of customers to adopt PAYL services using wearable technology by comparing perceived privacy risks and perceived benefits. The research model is developed on a basis of a literature review and expert interviews. By conducting an online survey involving 353 participants, a structural equation modelling approach is used to test the research model. The results show that current privacy risk factors dominate the perceived value of an individual to use PAYL services. Insurance companies, service providers and manufacturers of wearables must therefore primarily work together and offer solutions for greater data security and data protection before focusing on gamification and functional congruence.
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References
Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
Allmendinger, G., & Lombreglia, R. (2005). Four strategies for the age of smart services. Harvard Business Review, 83(10), 131.
Alt, R. (2016). Electronic Markets on customer-orientation. Electronic Markets, 26(3), 195–198.
Anderson, C. L., & Agarwal, R. (2010). Practicing Safe Computing: A multimethod empirical examination of home computer user behavioral intentions. MIS Quarterly, 34(3), 613–643.
Angst, C. M., & Agarwal, R. (2009). Adoption of electronic health records in the presence of privacy concerns: The elaboration likelihood model and individual persuasion. MIS Quarterly, 33(2), 339–370.
Bauer, W. (2015). Digitalisierung und Dienstleistungen als Innovationstreiber für die Wirtschaft. Fraunhofer-Institut für Arbeitswirtschaft und Organisation IAO, Stuttgart. http://pt-ad.pt-dlr.de/_media/vortrag_bauer-iao.pdf. Accessed 16 Jan 2017.
Berglund, M. E., Duvall, J., & Dunne, L. E. (2016). A survey of the historical scope and current trends of wearable technology applications. In Proceedings of the ACM International Symposium on Wearable Computers, pp. 40–43.
Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. MIS Quarterly, 28, 229–254.
BITKOM (2015). Zukunft der Consumer Electronics – 2015 Marktentwicklung, Schlüsseltrends, Mediennutzung Konsumentenverhalten, Neue Technologien. https://www.bitkom.org/noindex/Publikationen/2015/Studien/CE-Studie-2015/150901-CE-Studie-2015-online.pdf. Accessed 27 Sept 2016.
Boontarig, W., Chutimaskul, W., Chongsuphajaisiddhi, V., & Papasratorn, B. (2012). Factors influencing the Thai elderly intention to use smartphone for e-Health services. In IEEE Symposium on Humanities, Science and Engineering Research, pp. 479–483.
Chen, C. F. (2008). Investigating structural relationships between service quality, perceived value, satisfaction, and behavioral intentions for air passengers: Evidence from Taiwan. Transportation Research Part A: Policy and Practice, 42(4), 709–717.
Chen, C.-C. & Shih, H.-S. (2014). A study of the acceptance of wearable technology for consumers: An analytical network process perspective, Proceedings of the Thirteenth International Symposium on the Analytic Hierarchy/Network Process, ISAHP 2014, 1–5.
Chin, W. W. (1998). Issues and Opinion on Structural Equation Modeling. MIS Quarterly, 29(3), viixvi.
Ching, K. W., & Singh, M. M. (2016). Wearable technology devices security and privacy vulnerability analysis. International Journal of Network Security and its Applications, 8(3), 19–30.
CSS Insight (2016). Wearable momentum continues. http://www.ccsinsight.com/press/company-news/2516-wearables-momentum-continues. Accessed 2 Sept 2016.
Culnan, M. J., & Armstrong, P. K. (1999). Information privacy concerns, procedural fairness, and impersonal trust: An empirical investigation. Organization Science, 10(1), 104–115. https://doi.org/10.1287/orsc.10.1.104.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of Information Technology . MIS quarterly, 13(3), 319–340.
Degirmenci, K., Guhr, N., & Breitner, M. H. (2013). Mobile applications and access to personal information: A discussion of users' privacy concerns. In International Conference on Information Systems, pp. 15–18.
Diamantopoulos, A., Riefler, P., & Roth, K. P. (2008). Advancing formative measurement models. Journal of Business Research, 61(12), 1203–1218.
Dinev, T., & Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61–80.
Dinev, T., Xu, H., Smith, J. H., & Hart, P. (2013). Information privacy and correlates: an empirical attempt to bridge and distinguish privacy-related concepts. European Journal of Information Systems, 22(3), 295–316.
Eduard, M. N. (2007). Development Directions Of Services And Products In Insurances. Revista Tinerilor Economisti (The Young Economists Journal), 1(8), 89–92.
Ernst & Young (2015). Introducing "Pay As You Live" (PAYL) Insurance: Insurance that rewards a healthier lifestyle. http://www.ey.com/Publication/vwLUAssets/EY-introducing-pay-as-you-live-payl-insurance/$FILE/EY-introducing-pay-as-you-live-payl-insurance.pdf. Accessed 29 June 2016.
Ernst, C. P., & Ernst, A. (2016). The Influence of Privacy Risk on Smartwatch Usage. In: Americas Conference on Information Systems.
Fishbein, M. (1979). A theory of reasoned action: some applications and implications. In H. Howe, & M. Page (Eds.), Nebraska Symposium on Motivation (pp. 65–116). Lincoln: University of Nebraska Press.
Fornell, C., & Bookstein, F. L. (1982). Two Structural Equation Models: LISREL and PLS Applied to Consumer Exit-Voice Theory. Journal of Marketing Research, 19(4), 440–452.
Gao, Y., Li, H., & Luo, Y. (2015). An empirical study of wearable technology acceptance in healthcare. Industrial Management & Data Systems, 115(9), 1704–1723.
Gefen, D., Rigdon, E. E., & Straub, D. (2011). An Update and Extension to SEM Guidlines for Administrative and Social Science Research. MIS Quarterly, 35(2), iii–xiv.
Gu, Z., Wei, J., & Xu, F. (2015). An Empirical Study on Factors Influencing Consumers' Initial Trust in Wearable Commerce. The Journal of Computer Information Systems, 56(1), 79–85.
Hew, J. J., Lee, V. H., Ooi, K. B., & Wei, J. (2015). What catalyses mobile apps usage intention: an empirical analysis. Industrial Management & Data Systems, 115(7), 1269–1291.
Johnston, A. C., & Warkentin, M. (2010). Fear Appeals and Information Security Behaviors: An Empirical Study. MIS Quarterly, 34(3), 549–566.
Kagermann, H., Riemensperger, F., Hoke, D., Helbig, J. Schuh, G., Scheer, A. W., Spath, D., ... & Schweer, D. (2014). Smart Service Welt: Umsetzungsempfehlungen für das Zukunftsprojekt Internetbasierte Dienste für die Wirtschaft. Berlin: acatech. http://www.acatech.de/fileadmin/user_upload/Baumstruktur_nach_Website/Acatech/root/de/Projekte/Laufende_Projekte/Smart_Service_Welt/Smart_Service_Welt_2015/BerichtSmartService2015_D_lang_bf.pdf. Accessed 7 Jan 2017.
Kim, D. J. (2005). An Investigation on the New Mobile Service/Technology Adoption. In AMCIS 2005 Proceedings, p. 326.
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), 527–554.
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.
Kolany-Raiser, B. (2016). Der Verbraucher als Datenlieferant. Unter Mitarbeit von Consumer Association of North Rhine-Westphalia. Beiträge zur Verbraucherforschung, Verbraucherzentrale NRW. Hg. v. Bala, C und Schuldzinski, W.
Lee, A. S., & Baskerville, R. L. (2003). Generalizing generalizability in information systems research. Information Systems Research, 14(3), 221–243.
Leimeister, J. M., Österle, H., & Alter, S. (2014). Digital services for consumers. Electronic Markets, 24(4), 255.
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.
Limayem, M., & Hirt, S. G. (2003). Force of habit and information systems usage: Theory and initial validation. Journal of the Association for Information Systems, 4(1), 3.
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.
Mayring, P. (2010). Qualitative Inhaltsanalyse. Grundlagen und Techniken (p. 11). Beltz Deutscher Studien Verlag: Weinheim.
McAdams, E., Krupaviciute, A., Gehin, C., Grenier, E., Massot, B., Dittmar, A., & Fayn, J. (2011). Wearable sensor systems: The challenges. In Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE, pp. 3648–3651.
Nürnberg, V. (2015). E-Health und M(obile)- Health: Chancen und Risiken-das Aus für die Solidargemeinschaft. Zeitschrift für Versicherungswesen: ZfV, 66(8), 246–250.
Parasuraman, A., & Colby, C. L. (2015). An updated and streamlined technology readiness index: TRI 2.0. Journal of Service Research, 18(1), 59–74.
Pfeiffer, J., von Entress-Fuersteneck, M., Urbach, N., & Buchwald, A. (2016). Quantify-Me: Consumer Acceptance of Wearable Self-Tracking Devices. In Proceedings of the European Conference on Information Systems.
Polites, G. L., Roberts, N., & Thatcher, J. (2012). Conceptualizing Models Using Multidimensional Constructs: A Review and Guidelines for Their Use. European Journal of Information Systems, 21(1), 22–48.
PWC (2016). The Wearable Life 2.0 Connected living in a wearable world. Consumer Intelligence Series, pp. 1–23.
Rogers, E. M. (1995). Diffusion of innovations, 4th Edn. New York: Free Press.
Rundshagen, M. (2015). Versicherungsrisiken leichter bewerten dank medizinischer Innovation. Zeitschrift für Versicherungswesen: ZfV, 17, 560–562.
Schröder, S., & Schloss, M. (2015). Zwischen Self Tracking und Pay as you live: Die Herausforderungen neuer digitaler Geschäftsmodelle. https://www.it-finanzmagazin.de/zwischen-self-tracking-und-pay-as-you-live-die-herausforderungen-neuer-digitaler-geschaeftsmodelle-20726/. Accessed 15 Jan 2017.
Siponen, M. T., & Vance, A. O. (2010). Neutralization: New Insights into the Problem of Employee Systems Security Policy Violations. MIS Quarterly, 34(3), 487–502.
Smith, H. J., Milberg, S. J., & Burke, S. J. (1996). Information privacy: measuring individuals’ concerns about organizational practices. MIS quarterly, 20(2), 167–196.
Stewart, K. A., & Segars, A. H. (2002). An empirical examination of the concern for information privacy instrument. Information Systems Research, 13(1), 36–49.
Straub, D., Boudreau, M. C., & Gefen, D. (2004). Validation guidelines for IS positivist research. The Communications of the Association for Information Systems, 13(1), 63.
Sultan, N. (2015). Reflective thoughts on the potential and challenges of wearable technology for healthcare provision and medical education. International Journal of Information Management, 35(5), 521–526.
Sun, H. (2012). Understanding User Revisions when Using Information System Features: Adaptive System Use and Triggers. MIS Quarterly, 36(2), 453–478.
Tao, D. (2009). Intention to use and actual use of electronic information resources: Further exploring Technology Acceptance Model. In AMIA Annual Symposium Proceedings, pp. 629–633.
Trommsdorff, V. (2004). Konsumentenverhalten (6th ed.). Stuttgart: Kohlhammer.
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. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342–365.
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, 36(1), 157–178.
Webster, J., & Watson, R. T. (2002). Analyzing the Past to Prepare for the Future: Writing a Literature Review. MIS Quarterly, 26(2), xiii–xxiii.
Wei, J. (2014). How Wearables Intersect with the Cloud and the Internet of Things: Considerations for the developers of wearables. IEEE Consumer Electronics Magazine, 3(3), 53–56.
Wetzels, M., Odekerken-Schroder, G., & van Oppen, C. (2009). Using PLS path modeling for assessing hierachical construct models: guidlines and empirical illustration. MIS Quarterly, 33(1), 177–195.
Xu, H., Dinev, T., Smith, H. J., & Hart, P. (2008). Examining the formation of individual's privacy concerns: Toward an integrative view. In Proceedings of the International Conference on Information Systems, p. 6.
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., Gupta, S., Rosson, M. B., & Carroll, J. M. (2012). Measuring mobile users’ concerns for information privacy. International Conference on Information Systems, ICIS 2012 3, 2278–2293.
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, H., Shin, D. H., & Kim, H. (2015). Health information tailoring and data privacy in a smart watch as a preventive health tool. In M. Kurosu (Ed.), Human-computer interaction: users and Contexts. HCI 2015. Lecture Notes in Computer Science, 9171 (pp. 537–548). Cham: Springer.
Yuan, S., Ma, W., Kanthawala, S., & Peng, W. (2015). Keep using my health apps: Discover users' perception of health and fitness apps with the UTAUT2 model. Telemedicine and e-Health., 21(9), 735–741.
Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. The Journal of marketing., 52, 2–22.
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Wiegard, RB., Breitner, M.H. Smart services in healthcare: A risk-benefit-analysis of pay-as-you-live services from customer perspective in Germany. Electron Markets 29, 107–123 (2019). https://doi.org/10.1007/s12525-017-0274-1
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DOI: https://doi.org/10.1007/s12525-017-0274-1