Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Self-efficacy and anxiety as determinants of older adults’ use of Internet Banking Services


The second-level digital divide presents differences in people’s capabilities of using information and communication technologies, especially in older adults. This paper focuses on exploring self-efficacy and anxiety in this group concerning the use of a specific e-service, Internet banking service. Considering the triadic relation proposed in social cognitive theory, we include in the model of IBS use by older adults personal characteristics, such as self-efficacy, anxiety, perceived usefulness and gender with respect to the e-service chosen. We analyse the effect of perceived risks and social influence on these self-perceptions as environmental factors. This study is centred on a survey of 474 older adults and tests the structural model proposed using PLS-SEM. The results show that there are important differences between self-efficacy and anxiety when we refer to technology in general compared with a specific e-service. Furthermore, self-efficacy positively influences the perceived usefulness and the use of IBS. We note an important role of the environment as a booster to overcome the barriers which may appear due to these self-perceptions. Finally, we find influences of older adults’ gender in the relationship put forward in the causal model.

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

Fig. 1
Fig. 2


  1. 1.

    Agarwal, R., Sambamurthy, V., Stair, R.: The evolving relationship between general and specific computer self-efficacy: an empirical investigation. Inf. Syst. Res. 11(4), 418–430 (2000)

  2. 2.

    Akhter, S.H.: Privacy concern and online transactions: the impact of internet self-efficacy and internet involvement. J. Consum. Mark. 31(2), 118–125 (2014). https://doi.org/10.1108/JCM-06-2013-0606

  3. 3.

    Bandura, A.: Reflections on self-efficacy. In: Rachman, S. (ed.) Advances in Behavioral Research and Therapy, 1, pp. 237–269. Pergamon, Oxford (1978)

  4. 4.

    Bandura, A.: Social Foundations of Thought and Action: A Social Cognitive Theory. Prentice-Hall Inc, Eaglewood Cliffs (1986)

  5. 5.

    Bandura, A.: Self-efficacy conception of anxiety. Anxiety Res. 1(2), 77–98 (1988). https://doi.org/10.1080/10615808808248222

  6. 6.

    Bandura, A.: Human agency in social cognitive theory. Am. Psychol. 44(9), 1175–1184 (1989)

  7. 7.

    Bandura, A.: Self-Efficacy: The Exercise of Control. Macmillan, New York (1997)

  8. 8.

    Barbeite, F.G., Weiss, E.M.: Computer self-efficacy and anxiety scales for an Internet sample: testing measurement equivalence of existing measures and development of new scales. Comput. Human Behav. 20(1), 1–15 (2004)

  9. 9.

    Barth, M., Veit, D. J. (2011). How Digital Divide affects Public E-Services: The Role of Migration Background. In: Wirtschaftinformatik Proceedings 2011. Paper 118

  10. 10.

    Bauer, R.A.: Consumer behavior as risk taking. In: Hancock, R.S. (ed.) Dynamic Marketing for a Changing World, p. 398. American Marketing Association, Chicago (1960)

  11. 11.

    Bergström, A.: Online privacy concerns: A broad approach to understanding the concerns of different groups for different uses. Comput. Hum. Behav. 53, 419–426 (2015)

  12. 12.

    Bhattacherjee, A.: Understanding information systems continuance: an expectation-confirmation model. MIS Q. 25(3), 351–370 (2001)

  13. 13.

    Blank, G., Bolsover, G., Dubois, E.: A New Privacy Paradox: Young People and Privacy on Social Network Sites. Oxford Internet Institute, University of Oxford, Oxford (2014)

  14. 14.

    Büchi, M., Just, N., Latzer, M.: Modeling the second-level digital divide: a five-country study of social differences in Internet use. N. Media Soc. 18, 9 (2015)

  15. 15.

    Cazan, A.M., Cocoradã, E., Maican, C.I.: Computer anxiety and attitudes towards the computer and the internet with Romanian high-school and university students. Comput. Hum. Behav. 55, 258–267 (2016)

  16. 16.

    Çelik, H.: Influence of social norms, perceived playfulness and online shopping anxiety on customers’ adoption of online retail shopping: an empirical study in the Turkish context. Int. J. Retail Distrib. Manag. 39(6), 390–413 (2011). https://doi.org/10.1108/09590551111137967

  17. 17.

    Charness, N., Boot, W.R.: Aging and information technology use potential and barriers. Curr. Dir. Psychol. Sci. 18(5), 253–258 (2009)

  18. 18.

    Chen, L.Y., Hsiao, B., Chern, C.C., Chen, H.G.: Affective mechanisms linking Internet use to learning performance in high school students: a moderated mediation study. Comput. Hum. Behav. 35, 431–443 (2014). https://doi.org/10.1016/j.chb.2014.03.025

  19. 19.

    Chen, K., Chan, A.H.: Predictors of gerontechnology acceptance by older Hong Kong Chinese. Technovation 34(2), 126–135 (2014)

  20. 20.

    Chen, R., He, F.: Examination of brand knowledge, perceived risk and consumers’ intention to adopt an online retailer. Total Qual. Manag. Bus. Excell. 14(6), 677–693 (2003)

  21. 21.

    Chu, R.J.C.: How family support and Internet self-efficacy influence the effects of e-learning among higher aged adults–analyses of gender and age differences. Comput. Educ. 55(1), 255–264 (2010)

  22. 22.

    Chua, S.L., Chen, D.-T., Wong, A.F.: Computer anxiety and its correlates: a meta-analysis. Comput. Hum. Behav. 15(5), 609–623 (1999)

  23. 23.

    Chung, J., Park, N., Wang, H., Fulk, J., McLaughlin, M.: Age differences in perceptions of online community participation among non-users: an extension of the technology acceptance model. Comput. Hum. Behav. 26, 1674–1684 (2010). https://doi.org/10.1016/j.chb.2010.06.016

  24. 24.

    Compeau, D.R., Higgins, C.A.: Computer self-efficacy: development of a measure and initial test. MIS Q. 1, 189–211 (1995)

  25. 25.

    Compeau, D., Higgins, C.A., Huff, S.: Social cognitive theory and individual reactions to computing technology: a longitudinal study. MIS Q. 23(2), 145–158 (1999)

  26. 26.

    Czaja, S.J., Charness, N., Fisk, A.D., Hertzog, C., Nair, S.N., Rogers, W.A., Sharit, J.: Factors predicting the use of technology: findings from the Center for Research and Education on Aging and Technology Enhancement (CREATE). Psychol. Aging 21(2), 333 (2006)

  27. 27.

    Damant, J., Knapp, M.: What are the Likely Changes in Society and Technology Which will Impact upon the Ability of Older Adults to Maintain Social (extra-familial) Networks of Support Now, in 2025 and in 2040? Future of Ageing: Evidence Review. Government Office for Science, London (2015)

  28. 28.

    Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1, 319–340 (1989)

  29. 29.

    Dewan, S., Riggins, F.J.: The digital divide: current and future research directions. J. Assoc. Inf. Syst. 6(12), 298–337 (2005)

  30. 30.

    Doyle, J., Bailey, C., Scanaill, C.N., van den Berg, F.: Lessons learned in deploying independent living technologies to older adults’ homes. Univ. Access Inf. Soc. 13(2), 191–204 (2014). https://doi.org/10.1007/s10209-013-0308-1

  31. 31.

    Eastin, M.A.: Diffusion of e-commerce: an analysis of the adoption of four e-commerce activities. Telemat. Inf. 19(3), 251–267 (2002)

  32. 32.

    Eastin, M.A., LaRose, R.L.: Internet self-efficacy and the psychology of the digital divide. J. Comput. Med. Commun. 6(1), JCMC611 (2000)

  33. 33.

    European Commission: Growing the European Silver Economy. Background paper (2015). Retrieved April 2019 http://ec.europa.eu/research/innovation-union/pdf/active-healthy-ageing/silvereco.pdf

  34. 34.

    European Commission: Independent living in an ageing society through innovative ICT solutions (2016). http://cordis.europa.eu/article/id/400060-independent-living-in-an-ageing-society-through-ict_es.html. Accessed 15 Oct 2019

  35. 35.

    Eurostat: Information Society Statistics (2016). https://www.ontsi.red.es/index.php/es/indicadores. Accessed 15 Oct 2019

  36. 36.

    Featherman, M.S., Hajli, N.: Self-Service technologies and e-services risks in social commerce Era. J. Bus. Eth. 139, 1–19 (2015)

  37. 37.

    Featherman, M.S., Pavlou, P.A.: Predicting e-Services adoption: a perceived risk facets perspective. Int. J. Hum. Comput. Stud. 59(4), 451–474 (2003)

  38. 38.

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

  39. 39.

    Fornell, C., Larcker, D.F.: Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 18, 39–50 (1981)

  40. 40.

    Forsythe, S., Liu, C., Shannon, D., Gardner, L.C.: Development of a scale to measure the perceived benefits and risks of online shopping. J. Interact. Mark. 20(2), 55–75 (2006). https://doi.org/10.1002/dir.20061

  41. 41.

    Friemel, T.N.: The digital divide has grown old: Determinants of a digital divide among seniors. N. Media Soc. 18, 313–331 (2014)

  42. 42.

    Gelbrich, K., Sattler, B.: Anxiety, crowding, and time pressure in public self-service technology acceptance. J. Serv. Mark. 28(1), 82–94 (2014)

  43. 43.

    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. (2018). https://doi.org/10.1007/s10209-018-0642-4

  44. 44.

    Guo, X., Sun, Y., Wang, N., Peng, Z., Yan, Z.: The dark side of elderly acceptance of preventive mobile health services in China. Electron. Mark. 23(1), 49–61 (2013)

  45. 45.

    Hair Jr., F., Sarstedt, J.M., Hopkins, L., Kuppelwieser, G.V.: Partial least squares structural equation modeling (PLS-SEM) An emerging tool in business research. Eur. Bus. Rev. 26(2), 106–121 (2014)

  46. 46.

    Henseler, J.: PLS-MGA: A non-parametric approach to partial least squares-based multi-group analysis. In: Challenges at the Interface of Data Analysis, Computer Science, and Optimization, pp. 495–501. Springer, Berlin (2012)

  47. 47.

    Henseler, J., Hubona, G., Ray, A.: Using PLS path modeling in new technology research: updated guidelines. Ind. Manag. Data Syst. 116(1), 2–20 (2015)

  48. 48.

    Henseler, J., Ringle, C.M., Sarstedt, M.: A new criterion for assessing discriminant validity in variance-based structural equation modeling. J. Acad. Mark. Sci. 43, 115–135 (2015)

  49. 49.

    Hernández, B., Jiménez, J., Martín, M.J.: Age, gender and income: do they really moderate online shopping behaviour? Online Inf. Rev. 35(1), 113–133 (2011)

  50. 50.

    Hill, W.W., Beatty, S.E., Walsh, G.: A segmentation of adolescent online users and shoppers. J. Serv. Mark. 27(5), 347–360 (2013)

  51. 51.

    Hsu, M.H., Chiu, C.M.: Internet self-efficacy and electronic service acceptance. Decis. Support Syst. 38(3), 369–381 (2004). https://doi.org/10.1016/j.dss.2003.08.001

  52. 52.

    International Telecommunication Union, ITU: Measuring the Information Society Report (2015). http://www.itu.int/en/ITUD/Statistics/Documents/publications/misr2015/MISR2015-w5.pdf. Accessed 15 Oct 2019

  53. 53.

    Karavidas, M., Lim, N.K., Katsikas, S.L.: The effects of computers on older adult users. Comput. Hum. Behav. 21(5), 697–711 (2005)

  54. 54.

    Kavathatzopoulos, I.: ICT and sustainability: skills and methods for dialogue and policy making. J. Inf. Commun. Ethics Soc. 13(1), 13–18 (2015)

  55. 55.

    Kulviwat, S., Bruner II, C.G., Neelankavil, P.J.: Self-efficacy as an antecedent of cognition and affect in technology acceptance. J. Consum. Mark. 31(3), 190–199 (2014)

  56. 56.

    Kwon, O., Wen, Y.: An empirical study of the factors affecting social network service use. Comput. Hum. Behav. 26(2), 254–263 (2010)

  57. 57.

    Lam, J.C., Lee, M.K.: Digital inclusiveness–longitudinal study of Internet adoption by older adults. J. Manag. Inf. Syst. 22(4), 177–206 (2006)

  58. 58.

    Lankton, N.K., Wilson, E.V.: Factors influencing expectations of e-health services within a direct-effects model of user satisfaction. e-Serv. J. 5(2), 85–111 (2007)

  59. 59.

    Lee, C.L., Huang, M.K.: The influence of computer literacy and computer anxiety on computer self-efficacy: the moderating effect of gender. Cyberpsychol. Behav. Soc. Netw. 17(3), 172–180 (2014)

  60. 60.

    Lee, M.-C.: Factors influencing the adoption of internet banking: an integration of TAM and TPB with perceived risk and perceived benefit. Electron. Commer. Res. Appl. 8(3), 130–141 (2009)

  61. 61.

    Lee, C., Coughlin, J.F.: PERSPECTIVE: older adults’ adoption of technology: an integrated approach to identifying determinants and barriers. J. Prod. Innov. Manag. 32(5), 747–759 (2015)

  62. 62.

    Leppel, K., McCloskey, D.W.: A cross-generational examination of electronic commerce adoption. J. Consum. Mark. 28(4), 261–268 (2011)

  63. 63.

    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

  64. 64.

    Marakas, G.M., Johnson, R.D., Palmer, J.W.: A theoretical model of differential social attributions toward computing technology: when the metaphor becomes the model. Int. J. Hum. Comput. Stud. 52(4), 719–750 (2000)

  65. 65.

    Meuter, M.L., Ostrom, A.L., Bitner, M.J., Roundtree, R.: The influence of technology anxiety on consumer use and experiences with self-service technologies. J. Bus. Res. 56(11), 899–906 (2003)

  66. 66.

    Nayak, L.U., 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(4), 367–374 (2010)

  67. 67.

    Neill, W.D., Richard, J.E.: Intranet portals: marketing and managing individuals’ acceptance and use. Australas. Mark. J. 20(2), 147–157 (2012). https://doi.org/10.1016/j.ausmj.2011.10.003

  68. 68.

    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(6), 708–726 (2014)

  69. 69.

    Niemelä-Nyrhinen, J.: Baby boom consumers and technology: shooting down stereotypes. J. Consum. Market. 24(5), 305–312 (2007)

  70. 70.

    Organisation for Economic Cooperation and Development (OECD): Understanding the digital divide. Paris (2001). http://www.oecd.org/dataoecd/38/57/1888451.pdf. Accessed 22 Jan 2015

  71. 71.

    Page, K.L., Robson, M.J., Uncles, M.D.: Perceptions of web knowledge and usability: when sex and experience matter. Int. J. Hum. Comput. Stud. 70(12), 907–919 (2012)

  72. 72.

    Pajares, F.: Overview of social cognitive theory and of self-efficacy (2002). Retrieved Oct 2015, from http://www.emory.edu/EDUCATION/mfp/eff.html

  73. 73.

    Peral-Peral, B., Arenas-Gaitán, J., Villarejo-Ramos, Á.F.: From digital divide to psycho-digital divide: elders and online social networks. Comunicar 23(45), 57–64 (2015)

  74. 74.

    Powell, A.L.: Computer anxiety: comparison of research from the 1990s and 2000s. Comput. Hum. Behav. 29, 2337–2381 (2013)

  75. 75.

    Ringle, C.M., Wende, S. Becker, J.-M.: SmartPLS 3.2.3 Boenningstedt: SmartPLS GmbH (2015). http://www.smartpls.com. Accessed 15 Oct 2019

  76. 76.

    Rowley, J.: Understanding digital content marketing. J. Mark. Manag. 24(5–6), 517–540 (2008). https://doi.org/10.1362/026725708X325977

  77. 77.

    Scherer, R., Siddiq, F., Teo, T.: Becoming more specific: Measuring and modeling teachers’ perceived usefulness of ICT in the context of teaching and learning. Comput. Educ. 88, 202–214 (2015)

  78. 78.

    Sum, S., Mathews, R.M., Hughes, I., Campbell, A.: Internet use and loneliness in older adults. CyberPsychol. Behav. 11(2), 208–211 (2008). https://doi.org/10.1089/cpb.2007.0010

  79. 79.

    Sun, H., Zhang, P.: The role of moderating factors in user technology acceptance. Int. J. Hum. Comput. Stud. 64(2), 53–78 (2006)

  80. 80.

    Thatcher, J.B., Perrewé, P.L.: An empirical examination of individual traits as antecedents to computer anxiety and computer self-efficacy. MIS Q. 26(4), 381–396 (2002)

  81. 81.

    Thatcher, J., Loughry, M., Lim, J., McKnight, H.: Internet anxiety: an empirical study of the effects of personality, beliefs, and social support. Inf. Manag. 44(4), 353–363 (2007)

  82. 82.

    Torkzadeh, G., Van Dyke, T.P.: Effects of training on Internet self-efficacy and computer user attitudes. Int. J. Hum. Comput. Stud. 18(5), 479–494 (2002)

  83. 83.

    Tsai, C.H.: Integrating social capital theory, social cognitive theory, and the technology acceptance model to explore a behavioral model of telehealth systems. Int. J. Environ. Res. Public Health 11(5), 4905–4925 (2014)

  84. 84.

    Tsai, H.Y.S., Shillair, R., Cotten, S.R., Winstead, V., Yost, E.: Getting grandma online: are tablets the answer for increasing digital inclusion for older adults in the US? Educ. Gerontol. 41(10), 695–709 (2015)

  85. 85.

    United Nations: World Population Prospects. The 2017 Revision (2017). https://esa.un.org/unpd/wpp/Publications/Files/WPP2017_KeyFindings.pdf. Accessed 15 Oct 2019

  86. 86.

    Valenduc, G., Brotcorne, P., Damhuis, L., Laurent, V., Vendramin, P.: The second order digital divide. Synthesis of the research report, Programme “Society and Future”, FTU–Fondation Travail-Université (Namur) (2010). https://pdfs.semanticscholar.org/a9ca/1e36925dab7bccab514ae0523754e15565b5.pdf. Accessed 22 Jan 2015

  87. 87.

    Van Deursen, A., Van Dijk, J.: Internet skills and the digital divide. N. Media Soc. 13(6), 893–911 (2011)

  88. 88.

    Venkatesh, V.: Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance model. Inf. Syst. Res. 11(4), 342–365 (2000)

  89. 89.

    Venkatesh, V., Morris, M.G.: Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Q. 24(1), 115–139 (2000)

  90. 90.

    Venkatesh, V., Davis, F.D.: A model of the antecedents of perceived ease of use: development and test. Decis. Sci. 27(3), 451–481 (1996)

  91. 91.

    Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: User acceptance of information technology: toward a unified view. MIS Q. 27(3), 425–478 (2003)

  92. 92.

    Venkatesh, V., Thong, J.Y., Xu, X.: Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Q. 36(1), 157–178 (2012)

  93. 93.

    Vošner, H.B., Bobek, S., Kokol, P., Krečič, M.J.: Attitudes of active older Internet users towards online social networking. Comput. Hum. Behav. 55, 230–241 (2016)

  94. 94.

    Vroman, K.G., Arthanat, S., Lysack, C.: “Who over 65 is online?” Older adults’ dispositions toward information communication technology. Comput. Hum. Behav. 43, 156–166 (2015)

  95. 95.

    Wagner, N., Hassanein, K., Head, M.: Computer use by older adults: a multi-disciplinary review. Comput. Hum. Behav. 26(5), 870–882 (2010)

  96. 96.

    Walker, R.H., Johnson, L.W.: Why consumers use and do not use technology-enabled services. J. Serv. Mark. 20(2), 125–135 (2006)

  97. 97.

    Wei, K.K., Teo, H.H., Chan, H.C., Tan, B.C.: Conceptualizing and testing a social cognitive model of the digital divide. Inf. Syst. Res. 22(1), 170–187 (2011)

  98. 98.

    World Economic Forum: The Global Information Technology Report 2016. Innovating in the Digital Economy (2016). http://goo.gl/pivGLm. Accessed 15 Oct 2019

  99. 99.

    Wu, Y.T., Tsai, C.C.: University students’ internet attitudes and Internet self-efficacy: a study at three universities in Taiwan. CyberPsychol. Behav. 9(4), 441–450 (2006)

  100. 100.

    Yang, Y., Liu, Y., Li, H., Yu, B.: Understanding perceived risks in mobile payment acceptance. Ind. Manag Data Syst. 115(2), 253–269 (2015)

  101. 101.

    Yao, C., Liao, S.: Measuring the antecedent effects of service cognition and internet shopping anxiety on consumer satisfaction with e-tailing service. Manag. Mark. 6(1), 59–78 (2011)

  102. 102.

    Zhao, X., Mattila, A.S., Tao, L.-S.E.: The role of post-training self-efficacy in customers’ use of self-service technologies. Int. J. Serv. Ind. Manag. 19(4), 492–505 (2008)

Download references

Author information

Correspondence to Jorge Arenas-Gaitán.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Peral-Peral, B., Villarejo-Ramos, Á.F. & Arenas-Gaitán, J. Self-efficacy and anxiety as determinants of older adults’ use of Internet Banking Services. Univ Access Inf Soc (2019). https://doi.org/10.1007/s10209-019-00691-w

Download citation