What drives older adults’ use of mobile registration apps in Taiwan? An investigation using the extended UTAUT model

References

• Statista. Number of smartphone users in Taiwan from 2015 to 2020 (in millions)*, 2021; 2020. from https://www.statista.com/statistics/755288/taiwan-number-of-smartphone-users/.
   Google Scholar
• Liu HY, Lee WC, Sun YC, Fen JJ, Chen TJ, Chou LF, Hwang SJ. Hospital-owned apps in Taiwan: nationwide survey. JMIR mHealth uHealth. 2018;6(1):e22. doi:10.2196/mhealth.8636.
   PubMed Web of Science ®Google Scholar
• Akter S, Ray P, D’Ambra J. Continuance of mHealth services at the bottom of the pyramid: the roles of service quality and trust. Electron Markets. 2013;23(1):29–47. doi:10.1007/s12525-012-0091-5.
   Web of Science ®Google Scholar
• Lai YH, Huang FF, Yang HH. A study on the attitude of use the mobile clinic registration system in Taiwan. Technol Health Care. 2016;24(s1):S205–S211. doi:10.3233/THC-151076.
   Google Scholar
• Chen AN, McGaughey RE, Zeltmann SM, Lu H-K, Lee MR. How seniors in Taiwan use information technology: computer and cell phones. Int J Hum Comput Interact. 2018;34(2):166–76. doi:10.1080/10447318.2017.1335445.
   Web of Science ®Google Scholar
• Lin -Y-Y, Huang C-S. Aging in Taiwan: building a society for active aging and aging in place. Gerontologist. 2015;56(2):176–83. doi:10.1093/geront/gnv107.
   PubMed Web of Science ®Google Scholar
• Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of information technology: toward a unified view. MIS Quarterly. 2003;27(3):425–78. doi:10.2307/30036540.
   Web of Science ®Google Scholar
• Charness N, Boot WR. Aging and information technology use: potential and barriers. Curr Dir Psychol Sci. 2009;18(5):253–58. doi:10.1111/j.1467-8721.2009.01647.x.
   Web of Science ®Google Scholar
• Guo X, Sun Y, Wang N, Peng Z, Yan Z. The dark side of elderly acceptance of preventive mobile health services in China. Electron Markets. 2013;23(1):49–61. doi:10.1007/s12525-012-0112-4.
   Web of Science ®Google Scholar
• Peek ST, Wouters EJ, Van Hoof J, Luijkx KG, Boeije HR, Vrijhoef HJ. Factors influencing acceptance of technology for aging in place: a systematic review. Int J Med Inform. 2014;83(4):235–48. doi:10.1016/j.ijmedinf.2014.01.004.
   PubMed Web of Science ®Google Scholar
• Marangunić N, Granić A. Technology acceptance model: a literature review from 1986 to 2013. Universal Access Inf Soc. 2015;14(1):81–95. doi:10.1007/s10209-014-0348-1.
   Web of Science ®Google Scholar
• Cimperman M, Brenčič MM, Trkman P. Analyzing older users’ home telehealth services acceptance behavior—applying an Extended UTAUT model. Int J Med Inform. 2016;90:22–31. doi:10.1016/j.ijmedinf.2016.03.002.
   PubMed Web of Science ®Google Scholar
• Hoque R, Sorwar G. Understanding factors influencing the adoption of mHealth by the elderly: an extension of the UTAUT model. Int J Med Inform. 2017;101:75–84. doi:10.1016/j.ijmedinf.2017.02.002.
   PubMed Web of Science ®Google Scholar
• Šumak B, Šorgo A. The acceptance and use of interactive whiteboards among teachers: differences in UTAUT determinants between pre-and post-adopters. Comput Human Behav. 2016;64:602–20. doi:10.1016/j.chb.2016.07.037.
   Web of Science ®Google Scholar
• Venkatesh V, Thong JY, Chan FK, Hu PJH, Brown SA. Extending the two‐stage information systems continuance model: incorporating UTAUT predictors and the role of context. Inf Syst J. 2011;21(6):527–55. doi:10.1111/j.1365-2575.2011.00373.x.
   Web of Science ®Google Scholar
• Deng Z, Mo X, Liu S. Comparison of the middle-aged and older users’ adoption of mobile health services in China. Int J Med Inform. 2014;83(3):210–24. doi:10.1016/j.ijmedinf.2013.12.002.
   PubMed Web of Science ®Google Scholar
• Xue L, Yen CC, Chang L, Chan HC, Tai BC, Tan SB, … Choolani M. An exploratory study of ageing women’s perception on access to health informatics via a mobile phone-based intervention. Int J Med Inform. 2012;81(9):637–48. doi:10.1016/j.ijmedinf.2012.04.008.
   PubMed Web of Science ®Google Scholar
• Venkatesh V, Thong JY, Xu X. Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Quarterly. 2012;36(1):157–78. doi:10.2307/41410412.
   Web of Science ®Google Scholar
• Czaja SJ, Charness N, Fisk AD, Hertzog C, Nair SN, Rogers WA, Sharit J. Factors predicting the use of technology: findings from the center for research and education on aging and technology enhancement (CREATE). Psychol Aging. 2006;21(2):333–52. doi:10.1037/0882-7974.21.2.333.
   PubMed Web of Science ®Google Scholar
• Heart T, Kalderon E. Older adults: are they ready to adopt health-related ICT? Int J Med Inform. 2013;82(11):e209–e231. doi:10.1016/j.ijmedinf.2011.03.002.
   PubMed Web of Science ®Google Scholar
• Maslow, A. H. Motivation and Personality (2nd ed.). New York, NY: Harper & Row; 1995.
   Google Scholar
• Sun Y, Wang N, Guo X, Peng Z. Understanding the acceptance of mobile health services: a comparison and integration of alternative models. J Electron Commerce Res. 2013;14:183–200.
   Web of Science ®Google Scholar
• Bearden WO, Etzel MJ. Reference group influence on product and brand purchase decisions. J Consumer Res. 1982;9(2):183–94. doi:10.1086/208911.
   Web of Science ®Google Scholar
• Dwivedi YK, Shareef MA, Simintiras AC, Lal B, Weerakkody V. A generalised adoption model for services: a cross-country comparison of mobile health (m-health). Gov Inf Q. 2016;33(1):174–87. doi:10.1016/j.giq.2015.06.003.
   Web of Science ®Google Scholar
• Hsieh P-J. An empirical investigation of patients’ acceptance and resistance toward the health cloud: the dual factor perspective. Comput Human Behav. 2016;63:959–69. doi:10.1016/j.chb.2016.06.029.
   Web of Science ®Google Scholar
• Bandura A. Social foundations of thought and action: a social cognitive theory. Englewood Cliffs (NJ, US): Prentice-Hall, Inc; 1986.
   Google Scholar
• Hasan B, and Ahmed MU. A path analysis of the impact of application-specific perceptions of computer self-efficacy and anxiety on technology acceptance. Journal of Organizational and End User Computing (JOEUC). 2012;22(3):354–55.
   Web of Science ®Google Scholar
• Lim S, Xue L, Yen CC, Chang L, Chan HC, Tai BC, … Choolani M. A study on Singaporean women’s acceptance of using mobile phones to seek health information. Int J Med Inform. 2011;80(12):e189–e202. doi:10.1016/j.ijmedinf.2011.08.007.
   PubMed Web of Science ®Google Scholar
• Chen K, Chan AH. Predictors of gerontechnology acceptance by older Hong Kong Chinese. Technovation. 2014;34(2):126–35. doi:10.1016/j.technovation.2013.09.010.
   Web of Science ®Google Scholar
• Polites GL, Karahanna E. Shackled to the status quo: the inhibiting effects of incumbent system habit, switching costs, and inertia on new system acceptance. MIS Quarterly. 2012;36(1):21–42. doi:10.2307/41410404.
   Web of Science ®Google Scholar
• Samuelson W, Zeckhauser R. Status quo bias in decision making. J Risk Uncertain. 1988;1(1):7–59. doi:10.1007/BF00055564.
   Google Scholar
• Phang CW, Sutanto J, Kankanhalli A, Li Y, Tan BC, Teo -H-H. Senior citizens’ acceptance of information systems: a study in the context of e-government services. IEEE Trans Eng Manage. 2006;53(4):555–69. doi:10.1109/TEM.2006.883710.
   Web of Science ®Google Scholar
• Suki NM, Suki NM. Determining students’ behavioural intention to use animation and storytelling applying the UTAUT model: the moderating roles of gender and experience level. Int J Manage Educ. 2017;15(3):528–38. doi:10.1016/j.ijme.2017.10.002.
   Web of Science ®Google Scholar
• Moryson H, Moeser G. Consumer adoption of cloud computing services in Germany: investigation of moderating effects by applying an UTAUT model. Int J Marketing Stud. 2016;8(1):14–32. doi:10.5539/ijms.v8n1p14.
   Google Scholar
• Van de Vijver FJ, Leung K, and Leung K. Methods and data analysis for cross-cultural research , Cambridge, England: Cambridge University Press; 2021.
   Google Scholar
• Lian J-W, Yen DC. Online shopping drivers and barriers for older adults: age and gender differences. Comput Human Behav. 2014;37:133–43. doi:10.1016/j.chb.2014.04.028.
   Web of Science ®Google Scholar
• Anderson, James C., and David W. Gerbing. Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin. 1988; 103(3): 411–423.
   Web of Science ®Google Scholar
• Nunnally JC. Psychometric theory 3E. New York, NY: Tata McGraw-hill education; 1994.
   Google Scholar
• Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Marketing Res. 1981;18(1):39–50. doi:10.1177/002224378101800104.
   Web of Science ®Google Scholar
• Yu RP. Use of messaging apps and social network sites among older adults: a mixed-method study. Int J Commun. 2020;14:4453–73.
   Web of Science ®Google Scholar
• Zhou J, Rau P-LP, Salvendy GJB, Technology I. Older adults’ use of smart phones: an investigation of the factors influencing the acceptance of new functions. Behav Inf Technol. 2014;33(6):552–60. doi:10.1080/0144929X.2013.780637.
   Web of Science ®Google Scholar
• McDonald S, Chen F, Mair CA. Cross-national patterns of social capital accumulation: network resources and aging in China, Taiwan, and the United States. Am Behav Sci. 2015;59(8):914–30. doi:10.1177/0002764215580587.
   Web of Science ®Google Scholar
• Kim H-W, Kankanhalli A. Investigating user resistance to information systems implementation: a status quo bias perspective. MIS Quarterly. 2009;33(3):567–82. doi:10.2307/20650309.
   Web of Science ®Google Scholar
• Mulenga D, Liang J-S. Motivations for older adults’ participation in distance education: a study at the national open University of Taiwan. Int J Lifelong Educ. 2008;27(3):289–314. doi:10.1080/02601370802047791.
   Google Scholar
• Chiu CJ. Relationship between internet behaviors and social engagement in middle-aged and older adults in Taiwan. Int J Environ Res Public Health. 2019;16(3):416. doi:10.3390/ijerph16030416.
   Web of Science ®Google Scholar
• Hsu YC, Chang SJL. Understanding the public library’s internet services for elderly: the internet behavior of baby boomers in Taiwan. J Lib Inf Sci Res. 2013;8:147–83.
   Google Scholar
• Su SP, Tsai CH, and Chen YK (2012). Applying the technology acceptance model to explore intention to use telecare system in Taiwan. Paper presented at the 2012 13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, Kyoto, Japan.
   Google Scholar
• Yang HH, Yu C, Huang CH, and Yang HJ (2010). Elder participation in information technology: a qualitative analysis of Taiwan retirees. Paper presented at the Proceedings of the 10th WSEAS international conference on applied informatics and communications, Taipei Taiwan.
   Google Scholar
• Yu TK, Chao CM. Assessing older adults’ information technology ability: the development of a multiple item scale. Int J Hum Comput Interact. 2014;30(6):435–45. doi:10.1080/10447318.2014.880141.
   Web of Science ®Google Scholar
• Hsiao CH, Chen MC, and Tang KY (2013). Investigating the success factors for the acceptance of mobile healthcare technology. Paper presented at the PACIS 2013, Jeju Island, Korea.
   Google Scholar
• Alsswey A, Al-Samarraie H. Elderly users’ acceptance of mHealth user interface (UI) design-based culture: the moderator role of age. J Multimodal User Interfaces. 2020;14(1):49–59. doi:10.1007/s12193-019-00307-w.
   Web of Science ®Google Scholar