Skip to main content
SpringerLink
Log in

Evolution of Applied Variables in the Research on Technology Acceptance of the Elderly

  • Conference paper
  • First Online:
Human Aspects of IT for the Aged Population. Design, Interaction and Technology Acceptance (HCII 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13330))

Included in the following conference series:

  • 1552 Accesses

Abstract

Since entering the 21st century, the problem of social aging has become increasingly prominent. At the same time, more and more elderly people begin to try to use intelligent technology with the rapid development of science and technology. Many studies have used different models to study the technology acceptance of the elderly. This study reviewed literature on the elderly’s acceptance of technologies from 2008 to 2021, and found that the variables in the model change with the development of time and technology. We divided the literature into three main periods and found that the variables in the model gradually changed from focusing on technology to focusing on the social factors, as well as the emotions and feelings of the elderly. The degree of attention to the elderly gradually increased in this process.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. https://ourworldindata.org/grapher/size-of-young-working-elderly-populations?country=~OWID_WRL

  2. https://ourworldindata.org/grapher/population-by-age-group-to-2100?country=~OWID_WRL

  3. Ning, J.Z.: Report on main data of the Seventh National Census (2021)

    Google Scholar 

  4. Mostaghel, R.: Innovation and technology for the elderly: systematic literature review. J. Bus. Res. 69, 4896–4900 (2016). https://doi.org/10.1016/j.jbusres.2016.04.049

    Article  Google Scholar 

  5. Plaza, I., Martín, L., Martin, S., Medrano, C.: Mobile applications in an aging society: status and trends. J. Syst. Softw. 84, 1977–1988 (2011). https://doi.org/10.1016/j.jss.2011.05.035

    Article  Google Scholar 

  6. Klimova, B., Simonova, I., Poulova, P., Truhlarova, Z., Kuca, K.: Older people and their attitude to the use of information and communication technologies – a review study with special focus on the Czech Republic (older people and their attitude to ICT), Educational Gerontology, vol. 42 (2016). https://doi.org/10.1080/03601277.2015.1122447

  7. Ma, Q., Chan, A.H., Chen, K.: Personal and other factors affecting acceptance of smartphone technology by older Chinese adults. Appl. Ergon. 54, 62–71 (2016). https://doi.org/10.1016/j.apergo.2015.11.015

    Article  Google Scholar 

  8. Iancu, I., Iancu, B.: Designing mobile technology for elderly. A theoretical overview. Technol. Forecast. Soc. Change 155 (2020). https://doi.org/10.1016/j.techfore.2020.119977

  9. Chen, K., Chan, A.H.: Gerontechnology acceptance by elderly Hong Kong Chinese: a senior technology acceptance model (STAM). Ergonomics 57, 635–652 (2014). https://doi.org/10.1080/00140139.2014.895855

    Article  Google Scholar 

  10. Guner, H., Acarturk, C.: The use and acceptance of ICT by senior citizens: a comparison of technology acceptance model (TAM) for elderly and young adults. Univ. Access Inf. Soc. 19(2), 311–330 (2018). https://doi.org/10.1007/s10209-018-0642-4

    Article  Google Scholar 

  11. Li, J., Ma, Q., Chan, A.H., Man, S.S.: Health monitoring through wearable technologies for older adults: smart wearables acceptance model. Appl. Ergon. 75, 162–169 (2019). https://doi.org/10.1016/j.apergo.2018.10.006

    Article  Google Scholar 

  12. He, J., Huang, X.: Smart phone use and well-being of urban elderly: based on intergenerational support theory and technology acceptance model. Chin. J. Journalism Commun. 42, 49–73 (2020). https://doi.org/10.13495/j.cnki.cjjc.20200409.003

    Article  Google Scholar 

  13. Fishbein, M., Ajzen, I.: Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Addison-Wesley Publishing Company, Reading, MA (1975)

    Google Scholar 

  14. Bian, P.: Review on technology acceptance model. Res. Libr. Sci. (2012). https://doi.org/10.15941/j.cnki.issn1001-0424.2012.01.022

    Article  Google Scholar 

  15. Sun, J., Cheng, Y., Ke, Q.: Advances of research on technology acceptance model. Inf. Sci. 25, 1121–1127 (2007)

    Google Scholar 

  16. Davis, F.D., Bagozzi, R.P., Warshaw, P.R.: User acceptance of computer technology: A Comparison of two theoretical models. Manage. Sci. 35 (1989). 0025–1909/89/3508/0982$01.25

    Google Scholar 

  17. Yavuz, M., Çorbacıoğlu, E., Başoğlu, A.N., Daim, T.U., Shaygan, A.: Augmented reality technology adoption: case of a mobile application in Turkey. Technol. Soc. 66 (2021). https://doi.org/10.1016/j.techsoc.2021.101598

  18. Do, H.N., Shih, W., Ha, Q.A.: Effects of mobile augmented reality apps on impulse buying behavior: an investigation in the tourism field. Heliyon 6, e04667. https://doi.org/10.1016/j.heliyon.2020.e04667

  19. Jin, C.-H.: Adoption of e-book among college students: the perspective of an integrated TAM. Comput. Hum. Behav. 41, 471–477 (2014). https://doi.org/10.1016/j.chb.2014.09.056

    Article  Google Scholar 

  20. Aharony, N.: The effect of personal and situational factors on LIS students’ and professionals’ intentions to use e-books. Libr. Inf. Sci. Res. 36, 106–113 (2014). https://doi.org/10.1016/j.lisr.2014.01.001

    Article  Google Scholar 

  21. Hassan, H.E., Wood, V.R.: Does country culture influence consumers’ perceptions toward mobile banking? A comparison between Egypt and the United States. Telemat. Inform. 46 (2020). https://doi.org/10.1016/j.tele.2019.101312

  22. Ho, J.C., Wu, C.G., Lee, C.S., Pham, T-T.T.: Factors affecting the behavioral intention to adopt mobile banking: an international comparison. Technol. Soc. 63 (2020). https://doi.org/10.1016/j.techsoc.2020.101360

  23. Dutot, V., Bhatiasevi, V., Bellallahom, N.: Applying the technology acceptance model in a three-countries study of smartwatch adoption. J. High Technol. Manage. Res 30, 1–14 (2019). https://doi.org/10.1016/j.hitech.2019.02.001

    Article  Google Scholar 

  24. Bölen, M.C.: Exploring the determinants of users’ continuance intention in smart-watches. Technol. Soc. 60 (2020). https://doi.org/10.1016/j.techsoc.2019.101209

  25. Barrett, A.J., Pack, A., Quaid, E.D.: Understanding learners’ acceptance of high-immersion virtual reality systems: insights from confirmatory and exploratory PLS-SEM analyses. Comput. Educ. 169 (2021). https://doi.org/10.1016/j.compedu.2021.104214

  26. Schiopu, A.F., Hornoiu, R.I., Padurean, M.A., Nica, A-M.: Virus tinged exploring the facets of virtual reality use in tourism as a result of the COVID-19 pandemic. Telemat. Inform. 69 (2021). https://doi.org/10.1016/j.tele.2021.101575

  27. Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: A theoretical extension of the technology acceptance model: four longitudinal field studies. MIS Q. 27, 425–478 (2003)

    Article  Google Scholar 

  28. Macedo, I.M.: Predicting the acceptance and use of information and communication technology by older adults: an empirical examination of the revised UTAUT2. Comput. Hum. Behav. 75, 935–948 (2017). https://doi.org/10.1016/j.chb.2017.06.013

    Article  Google Scholar 

  29. Venkatesh, V., Thong, J.Y.L., Xu, X: Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Q. 36, 157–178 (2012)

    Google Scholar 

  30. Zaad, L., Allouch, S.B.: The influence of control on the acceptance of ambient in-telligence by elderly people: an explorative study. Lecture Notes in Computer Science, pp. 58–74 (2008)

    Google Scholar 

  31. Ryu, M.-H., Kim, S., Lee, E.: Understanding the factors affecting online elderly user’s participation in video UCC services. Comput. Hum. Behav. 25, 619–632 (2009). https://doi.org/10.1016/j.chb.2008.08.013

    Article  Google Scholar 

  32. Conci, M., Pianesi, F., Zancanaro, M.: Useful, Social and Enjoyable: Mobile Phone Adoption by Older People (2009)

    Google Scholar 

  33. Pan, S., Jordan-M, M.: Internet use intention and adoption among Chinese older adults: from the expanded technology acceptance model perspective. Comput. Hum. Behav. 26, 1111–1119 (2010). https://doi.org/10.1016/j.chb.2010.03.015

  34. Tsai, T.-H., Chang, H.-T., Chang, Y.-M., Huang, G.-S.: Sharetouch: a system to enrich social network experiences for the elderly. J. Syst. Softw. 85, 1363–1369 (2012). https://doi.org/10.1016/j.jss.2012.01.023

    Article  Google Scholar 

  35. Chen, K., Chan, A.H.S.: Predictors of gerontechnology acceptance by older Hong Kong Chinese. Technovation 34, 126–135 (2014). https://doi.org/10.1016/j.technovation.2013.09.010

    Article  Google Scholar 

  36. Hsiao, C.-H., Tang, K.-Y.: Examining a model of mobile healthcare technology acceptance by the elderly in Taiwan. J. Glob. Inf. Technol. Manag. 18, 292–311 (2015). https://doi.org/10.1080/1097198x.2015.1108099

    Article  Google Scholar 

  37. Cimperman, M., Makovec, B.M., Trkman, P.: Analyzing older users’ home tele-health services acceptance behavior-applying an extended UTAUT model. Int. J. Med. Inform. 90, 22–31 (2016). https://doi.org/10.1016/j.ijmedinf.2016.03.002

    Article  Google Scholar 

  38. Hoque, R., Sorwar, G.: Understanding factors influencing the adoption of mHealth by the elderly: an extension of the UTAUT model. Int. J. Med. Inform. 101, 75–84 (2017). https://doi.org/10.1016/j.ijmedinf.2017.02.002

    Article  Google Scholar 

  39. Xia, P.: Construction of Intelligent Health Service Model for Elderly People in Community Based on the Theory of Information Technology Adoption. Zhejiang Chinese Medical University, Degree of Master (2017)

    Google Scholar 

  40. Luo, S., et al.: Analysis on demand factors of urban community intelligent elderly care service project based on TAM theory. Chin. J. Health Stat. 35, 372–379 (2018)

    Google Scholar 

  41. Talukder, M.S., Sorwar, G., Bao, Y., Ahmed, J.U., Palash, M.A.S.: Predicting ante-cedents of wearable healthcare technology acceptance by elderly: a combined SEM-Neural Network approach, vol. 150. Technological Forecasting and Social Change (2020). https://doi.org/10.1016/j.techfore.2019.119793

  42. Lazaro, M.J.S., Lim, J., Kim, S.H., Yun, M.H.: Wearable technologies: acceptance model for smartwatch adoption among older adults. In: Gao, Q., Zhou, J. (eds.) HCII 2020. LNCS, vol. 12207, pp. 303–315. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-50252-2_23

    Chapter  Google Scholar 

  43. Soh, P.Y., et al.: 2020 Perception, acceptance and willingness of older adults in Malaysia towards online shopping: a study using the UTAUT and IRT models. J. Ambient. Intell. Humaniz. Comput. 1–13https://doi.org/10.1007/s12652-020-01718-4

  44. Wu, J., Song, S.: Older adults’ online shopping continuance intentions: applying the technology acceptance model and the theory of planned behavior. Int. J. Hum. Comput. Interact. 37, 938–948 (2020). https://doi.org/10.1080/10447318.2020.1861419

    Article  Google Scholar 

  45. Ojiako, U., Choudrie, J., Nwanekezie, U., Chikelue, C.-O.: Adoption and use of tablet devices by older adults: a quantitative study. In: Pappas, I.O., Mikalef, P., Dwivedi, Y.K., Jaccheri, L., Krogstie, J., Mäntymäki, M. (eds.) I3E 2019. LNCS, vol. 11701, pp. 545–558. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-29374-1_44

    Chapter  Google Scholar 

  46. Theng, L.Y., Dahlan, A.B., Akmal, M.L., Myint, T.Z.: An Exploratory Study on Senior Citizens’ Perceptions of the Nintendo Wii: The Case of Singapore (2009)

    Google Scholar 

  47. Nayak, L.U.S., Priest, L., White, A.P.: An application of the technology acceptance model to the level of Internet usage by older adults. Univ. Access Inf. Soc. 9, 367–374 (2010). https://doi.org/10.1007/s10209-009-0178-8

    Article  Google Scholar 

  48. Huang, J.-C., Lee, Y.-C.: Predicting telecare adoption on senior citizens in institution: application of the technology acceptance model. J. Stat. Manage. Syst. 15, 81–92 (2012). https://doi.org/10.1080/09720510.2012.10701614

    Article  Google Scholar 

  49. Barnard, Y., Bradley, M.D., Hodgson, F., Ashley, D.L.: Learning to use new technologies by older adults: perceived difficulties, experimentation behaviour and usability. Comput. Hum. Behav. 29, 1715–1724 (2013). https://doi.org/10.1016/j.chb.2013.02.006

  50. Kivimäki, T., et al.: User interface for social networking application for the elderly. In: Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments - PETRA 2013, pp. 1–8 (2013). https://doi.org/10.1145/2504335.2504358

  51. Niehaves, B., Plattfaut, R.: Internet adoption by the elderly: employing IS technology acceptance theories for understanding the age-related digital divide. Eur. J. Inf. Syst. 23, 708–726 (2017). https://doi.org/10.1057/ejis.2013.19

    Article  Google Scholar 

  52. Wang, Q.F., Sun, X.: Investigating gameplay intention of the elderly using an Extended Technology Acceptance Model (ETAM). Technol. Forecast. Soc. Chang. 107, 59–68 (2016). https://doi.org/10.1016/j.techfore.2015.10.024

    Article  Google Scholar 

  53. Qiao, Y.: Research on digital reading behavior and acceptance among the elderly. Shanghai Jiao Tong University, De-gree of Master (2017)

    Google Scholar 

  54. Zhang, Y.: Research on the influence of aging characteristics and perceived risks on smart home adoption by elderly. Zhejiang Chinese Medical University, Dalian University of Technology, Degree of Master (2020)

    Google Scholar 

  55. Zhan, J., Sun, T.: An empirical study on the impact of urban elderly on elderly care services. Theor. Modern. 2, 117–128 (2021)

    Google Scholar 

  56. Judges, A., Laanemets, C., Stern, A., Baecker, M.: “In Touch” with senior: exploring option of a simplified interface for social communication and related social outcomes. Comput. Hum. Behav. 75, 912–921 (2017). https://dx.doi.org/10.1016/j.chb.2017.07.004

Download references

Author information

Authors and Affiliations

  1. Ocean University of China, Qingdao, 266100, China

    Ruisi Liu & Junjie Chu

  2. Peking University, Beijing, 102627, China

    Xueai Li

Authors
  1. Ruisi Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xueai Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Junjie Chu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Junjie Chu .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Qin Gao

  2. Chongqing University, Chongqing, China

    Jia Zhou

Appendix. The Authors, Research Contents, and Results of the Studies.

Appendix. The Authors, Research Contents, and Results of the Studies.

figure a
figure b
figure c
figure d
figure e
figure f
figure g
figure h
figure i

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Liu, R., Li, X., Chu, J. (2022). Evolution of Applied Variables in the Research on Technology Acceptance of the Elderly. In: Gao, Q., Zhou, J. (eds) Human Aspects of IT for the Aged Population. Design, Interaction and Technology Acceptance. HCII 2022. Lecture Notes in Computer Science, vol 13330. Springer, Cham. https://doi.org/10.1007/978-3-031-05581-2_35

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-05581-2_35

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-05580-5

  • Online ISBN: 978-3-031-05581-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation