Exploring facets of trust in older adult decisions to adopt mobile commerce
-
2018-11-05 https://doi.org/10.14419/ijet.v7i4.20658 -
Mobile Commerce Adoption, Mobile Device Technology, Older Adult Trust, Smartphone Usability, Technology Acceptance Model. -
Abstract
Mobile commerce currently suffers from low adoption rates even though mobile devices are seemingly everywhere. Retailers have not fully tapped the older adult consumer market, a market framed by two significant attributes. Firstly, older adults are currently the largest segment of the USA population and will be for many years. Secondly, older adults are already known to be a lucrative market for low debt their spending power make them a primary interest to online retailers. While research exists for mobile commerce technology, the older adult age group has not yet been a primary focus of exploration. This quantitative study specifically examined aspects of mobile device usage, privacy, and internet trust factors of mobile commerce adoption among older adults by adapting modern technology acceptance theory as the frame-work for the research. This study determined that older adults have similar levels of interest in mobile commerce technology as compared to younger consumers but approach new technology cautiously, with a deeper consideration of risks and consequences.
Â
Â
-
References
[1] Khalifa, M., Cheng, S. K. N., & Shen, K. N. (2012). Adoption of mobile commerce: A confidence model. The Journal of Computer Information Systems, 53(1), 14-22. Web Accessed on September 30, 2018. Retrieved from http://www.iacis.org/jcis/jcis_toc.php?volume=53&issue=1.
[2] Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. Retrieved from https://doi.org/10.2307/249008.
[3] Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-T.
[4] Chan, F. T. S., & Chong, A. Y. (2013). Analysis of the determinants of consumer’s' m-commerce usage activities. Online Information Review, 37(3), 443-461. https://doi.org/10.1108/OIR-01-2012-0012.
[5] Chang, J. M., Williams, J., & Hurlburt, G. (2014). Mobile commerce. IT Professional, 16(3), 4-5. https://doi.org/10.1109/MITP.2014.36.
[6] Chong, A. Y. (2013). Mobile commerce usage activities: The roles of demographic and motivation variables. Technological Forecasting & Social Change, 80(7), 1350–1359. https://doi.org/10.1016/j.techfore.2012.12.011.
[7] Eastin, M. S., Brinson, N. H., Doorey, A., & Wilcox, G. (2016). Living in a big data world: Predicting mobile commerce activity through privacy concerns, Computers in Human Behavior, 58, 214-220. https://doi.org/10.1016/j.chb.2015.12.050.
[8] Faqih, K., & Jaradat, M. (2015). Assessing the moderating effect of gender differences and individualism-collectivism at individual-level on the adoption of mobile commerce technology: TAM3 perspective. Journal of Retailing and Consumer Services, 22, 37-52, https://doi.org/10.1016/j.jretconser.2014.09.006.
[9] Gale, S. F. (2012). Retail apps target mobile shoppers. PM Network, 26(2), 14-15. Web Accessed on September 30, 2018. Retrieved from http://www.pmi.org/learning/publications-online-library/pm-network-past-issues.aspx
[10] GAO, S., Krogstie, J., & Gransaether, P. A. (2008). Mobile services acceptance model. Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology. https://doi.org/10.1109/ICHIT.2008.252.
[11] GAO, S., Krogstie, J., & Siau, K. (2011). Developing an instrument to measure the adoption of mobile services. Mobile Information Systems, 7(1), 45–67. https://doi.org/10.1155/2011/831018.
[12] Heery, M. (2011). Baby boomers on conscious aging. Journal of Transpersonal Psychology, 43(2), 256-259. Web Accessed on September 30, 2018. Retrieved from http://atpweb.org/Default.aspx
[13] Heinz, M., Martin, P., Margrett, J. A., Yearns, M., Franke, W., Yang, H., & Chang, C. K. (2013). Perceptions of technology among older adults. Journal of Gerontological Nursing, 39(1), 42-51. https://doi.org/10.3928/00989134-20121204-04.
[14] Hernandez, B., Jimenez, J., & Martin, M. J. (2011). Age, gender and income: Do they really moderate online shopping behaviour? Online Information Review, 35(1), 113-133. https://doi.org/10.1108/14684521111113614.
[15] Hoeg, G. (2011). Post-boomer wealth. Best's Review, 112(4), 64. Web Accessed on September 30, 2018. Retrieved from http://www3.ambest.com/review/archive.asp
[16] Khalifa, M., & Shen, K. N. (2008). Drivers for transactional B2C m-commerce adoption: Extended theory of planned behavior. The Journal of Computer Information Systems, 48(3), 111-117. Web Accessed on September 30, 2018. Retrieved from http://www.iacis.org/jcis/index.htm
[17] Kim, J. B. (2012). An empirical study on consumer first purchase intention in online shopping: Integrating initial trust and TAM. Electronic Commerce Research, 12(2), 125-150. https://doi.org/10.1007/s10660-012-9089-5.
[18] Kourouthanassis, P. E., & Giaglis, G. M. (2012). Introduction to the special issue mobile commerce: The past, present, and future of mobile commerce research. International Journal of Electronic Commerce, 16(4), 5-18. https://doi.org/10.2753/JEC1086-4415160401.
[19] Kumar, A., & Lim, H. (2008). Age differences in mobile service perceptions: Comparison of generation Y and baby boomers. The Journal of Services Marketing, 22(7), 568-577. https://doi.org/10.1108/08876040810909695.
[20] LeRouge, C., Van Slyke, C., Seale, D., & Wright, K. (2014). Baby boomers’ adoption of consumer health technologies: Survey on readiness and barriers. Journal of Medical Internet Research, 16(9), e200. https://doi.org/10.2196/jmir.3049.
[21] Liebana-Cabanillas, F., Munoz-Leiva, F., & Sanchez-Fernandez, J. (2015). Influence of age in the adoption of new mobile payment systems. Revista Brasileira De Gestão De Negócios, 17(58), 1390-1407. https://doi.org/10.7819/rbgn.v17i58.1989.
[22] Lu, J. (2014). Are personal innovativeness and social influence critical to continue with mobile commerce? Internet Research, 24(2), 134-159. https://doi.org/10.1108/IntR-05-2012-0100.
[23] Luo, C. (2014). Study on mobile commerce customer based on value adoption. Journal of Applied Sciences, 14(9), 901-909. https://doi.org/10.3923/jas.2014.901.909.
[24] MacMillan, D., & Galante, J. (2010). EBay emerging as mobile commerce market leader. Bloomberg Businessweek. Web Accessed on September 30, 2018. Retrieved from http://www.telecomasia.net/content/ebay-emerging-mobile-commerce-market-leader
[25] Nassuora, A. B. (2013). Understanding factors affecting the adoption of m-commerce by consumers. Journal of Applied Sciences, 13(6), 913-918. https://doi.org/10.3923/jas.2013.913.918.
[26] Ramon-Jeronimo, M. A., Peral-Peral, B., & Arenas-Gaitan, J. (2013). Elderly persons and internet use. Social Science Computer Review, 31(4), 389–403. https://doi.org/10.1177/0894439312473421.
[27] Rogers, E. M. (2003). Diffusion of innovations (5th Ed.). New York: Free Press.
[28] Salz, P. A. (2014). Monitoring mobile app performance. Journal of Direct, Data and Digital Marketing Practice, 15(3), 219-221. https://doi.org/10.1057/dddmp.2014.9.
[29] Shankar, K. (2010). Pervasive computing and an aging populace. Journal of Information, Communication & Ethics in Society, 8(3), 236-248. https://doi.org/10.1108/14779961011071051.
[30] Siau, K., & Shen, Z. (2003). Building customer trust in mobile commerce. Communications of the ACM, 46(4), 91-94. https://doi.org/10.1145/641205.641211.
[31] U.S. Census. (2010). Age and sex composition: 2010. Web Accessed on September 30, 2018. Retrieved from: http://www.census.gov/prod/cen2010/briefs/c2010br-03.pdf
[32] Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. Web Accessed on September 30, 2018. Retrieved from http://www.misq.org/contents-27-3/.
[33] 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. Retrieved from https://doi.org/10.2307/41410412.
[34] Volkom, M. V., Stapley, J. C., & Amaturo, V. (2014). Revisiting the digital divide: Generational differences in technology use in everyday life. North American Journal of Psychology, 16(3), 557-574. Retrieved from http://najp.8m.com/index.html
[35] Wan, Y., Nakayama, M., & Sutcliffe, N. (2012). The impact of age and shopping experiences on the classification of search, experience, and credence goods in online shopping. Information Systems and eBusiness Management, 10(1), 135-148. https://doi.org/10.1007/s10257-010-0156-y.
[36] Wang, L., Rau, P. P., & Salvendy, G. (2011). Older adults' acceptance of information technology. Educational Gerontology, 37(12), 1081-1099. https://doi.org/10.1080/03601277.2010.500588.
[37] Zhang, R., Chen, J. Q., & Lee, C. J. (2013). Mobile commerce and consumer privacy concerns. The Journal of Computer Information Systems, 53(4), 31-38. Retrieved from https://doi.org/10.1080/08874417.2013.11645648.
[38] Zickuhr, K., & Madden, M. (2012). Older adults and internet use. Pew Research Center’s Internet and American Life Project. Web Accessed on September 30, 2018. http://pewinternet.org/Reports/2012/Older-adults- and-internet-use.aspx.
[39] Rahman, Mohammed and Sloan, Terry; Opportunities and Challenges of M-commerce Adoption in Bangladesh: An Empirical Study, Journal of Internet Banking and Commerce 20(3), https://doi.org/10.4172/1204-5357.1000124.
[40] Alqatan, S., Noor, N.M., operate, M., & Mohemad, R. (2016). An Empirical Study on Success Factors to Enhance Customer Trust for Mobile Commerce in Small and Medium-sized Tourism Enterprises ( Smtes ) in Jordan. Journal of Theoretical and Applied Information Technology 31 January 2016. Vol.83. No.3.
-
Downloads
-
How to Cite
J. Morga Ph. D, J., & S. M. Rahman Ph. D, S. (2018). Exploring facets of trust in older adult decisions to adopt mobile commerce. International Journal of Engineering & Technology, 7(4), 4954-4961. https://doi.org/10.14419/ijet.v7i4.20658