Skip to main content

Advertisement

Log in

Examining mobile banking user adoption from the perspectives of trust and flow experience

  • Published:
Information Technology and Management Aims and scope Submit manuscript

Abstract

Due to the high perceived risk and poor experience associated with using mobile banking, it is critical for service providers to build users’ trust and improve their experience. Integrating both perspectives of trust and flow experience, this research examined the factors affecting mobile banking user adoption. The results indicate that structural assurance is the main factor affecting trust, whereas ubiquity and perceived ease of use are the main factors affecting flow experience. Trust has a significant effect on flow experience, and both factors determine usage intention, which in turn affects actual usage. Thus mobile service providers need to concern both trust and flow experience to facilitate user adoption and usage of mobile banking services.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. CNNIC (2011) 28th Statistical survey report on the internet development in China. China Internet Network Information Center, Beijing

    Google Scholar 

  2. iResearch (2009) China mobile payment research report

  3. Kim G, Shin B, Lee HG (2009) Understanding dynamics between initial trust and usage intentions of mobile banking. Inf Syst J 19(3):283–311

    Article  Google Scholar 

  4. Lee KC, Chung N (2009) Understanding factors affecting trust in and satisfaction with mobile banking in Korea: a modified DeLone and McLean’s model perspective. Interact Comput 21(5–6):385–392

    Article  Google Scholar 

  5. Luo X et al (2010) Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: an empirical study of mobile banking services. Decis Support Syst 49(2):222–234

    Article  Google Scholar 

  6. Hoffman DL, Novak TP (2009) Flow online: lessons learned and future prospects. J Interact Market 23(1):23–34

    Article  Google Scholar 

  7. Beldad A, de Jong M, Steehouder M (2010) How shall I trust the faceless and the intangible? A literature review on the antecedents of online trust. Comput Hum Behav 26(5):857–869

    Article  Google Scholar 

  8. Varnali K, Toker A (2010) Mobile marketing research: the-state-of-the-art. Int J Inf Manag 30(2):144–151

    Article  Google Scholar 

  9. Siau K, Shen Z (2003) Building customer trust in mobile commerce. Commun ACM 46(4):91–94

    Article  Google Scholar 

  10. Lin HH, Wang YS (2006) An examination of the determinants of customer loyalty in mobile commerce contexts. Inf Manag 43(3):271–282

    Article  Google Scholar 

  11. Li Y-M, Yeh Y-S (2010) Increasing trust in mobile commerce through design aesthetics. Comput Hum Behav 26(4):673–684

    Article  Google Scholar 

  12. Vance A, Christophe E-D-C, Straub DW (2008) Examining trust in information technology artifacts: the effects of system quality and culture. J Manag Inf Syst 24(4):73–100

    Google Scholar 

  13. Laforet S, Li X (2005) Consumers’ attitudes towards online and mobile banking in China. Int J Bank Market 23(5):362–380

    Article  Google Scholar 

  14. Lee KC, Kang IW, McKnight DH (2007) Transfer from offline trust to key online perceptions: an empirical study. IEEE Trans Eng Manag 54(4):729–741

    Article  Google Scholar 

  15. Lee K-W, Tsai M-T, Lanting MCL (2011) From marketplace to market space: investigating the consumer switch to online banking. Electron Commerc Res Appl 10(1):115–125

    Article  Google Scholar 

  16. Al-Somali SA, Gholami R, Clegg B (2009) An investigation into the acceptance of online banking in Saudi Arabia. Technovation 29(2):130–141

    Article  Google Scholar 

  17. Liao Z, Cheung MT (2008) Measuring consumer satisfaction in internet banking: a core framework. Commun ACM 51(4):47–51

    Article  Google Scholar 

  18. Yiu CS, Grant K, Edgar D (2007) Factors affecting the adoption of internet banking in Hong Kong—Implications for the banking sector. Int J Inf Manag 27(5):336–351

    Article  Google Scholar 

  19. Lin H-F (2011) An empirical investigation of mobile banking adoption: the effect of innovation attributes and knowledge-based trust. Int J Inf Manag 31(3):252–260

    Article  Google Scholar 

  20. Shen YC et al (2010) A benefit-cost perspective of the consumer adoption of the mobile banking system. Behav Inf Technol 29(5):497–511

    Article  Google Scholar 

  21. Csikszentmihalyi M, Csikszentmihalyi IS (1988) Optimal experience: psychological studies of flow in consciousness. Cambridge University Press, Cambridge, UK

    Google Scholar 

  22. Novak TP, Hoffman DL, Yung Y-F (2000) Measuring the customer experience in online environments: a structural modeling approach. Market Sci 19(1):22–42

    Article  Google Scholar 

  23. Huang M-H (2006) Flow, enduring, and situational involvement in the web environment: a tripartite second-order examination. Psychol Market 23(5):383–411

    Article  Google Scholar 

  24. Ho L-A, Kuo T-H (2010) How can one amplify the effect of e-learning? An examination of high-tech employees’ computer attitude and flow experience. Comput Hum Behav 26(1):23–31

    Article  Google Scholar 

  25. Chen K et al (2008) An exploratory study of the selection of communication media: the relationship between flow and communication outcomes. Decis Support Syst 45(4):822–832

    Article  Google Scholar 

  26. Wu J-J, Chang Y-S (2005) Towards understanding members’ interactivity, trust, and flow in online travel community. Ind Manag Data Syst 105(7):937–954

    Article  Google Scholar 

  27. Hausman AV, Siekpe JS (2009) The effect of web interface features on consumer online purchase intentions. J Bus Res 62(1):5–13

    Article  Google Scholar 

  28. O’Cass A, Carlson J (2010) Examining the effects of website induced flow in professional sporting team websites. Internet Res 20(2):115–134

    Article  Google Scholar 

  29. Chang HH, Wang IC (2008) An investigation of user communication behavior in computer mediated environments. Comput Hum Behav 24(5):2336–2356

    Article  Google Scholar 

  30. Guo YM, Klein BD (2009) Beyond the test of the four channel model of flow in the context of online shopping. Commun AIS 24(1):837–856

    Google Scholar 

  31. Guo YM, Poole MS (2009) Antecedents of flow in online shopping: a test of alternative models. Inf Syst J 19(4):369–390

    Article  Google Scholar 

  32. Zaman M, Anandarajan M, Dai Q (2010) Experiencing flow with instant messaging and its facilitating role on creative behaviors. Comput Hum Behav 26(5):1009–1018

    Article  Google Scholar 

  33. Deng L et al (2010) User experience, satisfaction, and continual usage intention of IT. Eur J Inf Syst 19(1):60–75

    Article  Google Scholar 

  34. Jung Y, Perez-Mira B, Wiley-Patton S (2009) Consumer adoption of mobile TV: examining psychological flow and media content. Comput Hum Behav 25(1):123–129

    Article  Google Scholar 

  35. Ha I, Yoon Y, Choi M (2007) Determinants of adoption of mobile games under mobile broadband wireless access environment. Inf Manag 44(3):276–286

    Article  Google Scholar 

  36. Pavlou PA, Gefen D (2004) Building effective online marketplaces with institution-based trust. Inf Syst Res 15(1):37–59

    Article  Google Scholar 

  37. Song J, Zahedi FM (2007) Trust in health infomediaries. Decis Support Syst 43(2):390–407

    Article  Google Scholar 

  38. Lee T (2005) The impact of perceptions of interactivity on customer trust and transaction intentions in mobile commerce. J Electron Commerc Res 6(3):165–180

    Google Scholar 

  39. Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quart 13(3):319–340

    Article  Google Scholar 

  40. Benamati JS et al (2010) Clarifying the integration of trust and TAM in e-commerce environments: implications for systems design and management. IEEE Trans Eng Manag 57(3):380–393

    Article  Google Scholar 

  41. Agarwal R, Karahanna E (2000) Time flies when you are having fun: cognitive absorption and beliefs about information technology usage. MIS Quart 24(4):665–694

    Article  Google Scholar 

  42. Mayer RC, Davis JH, Schoorman FD (1995) An integrative model of organizational trust. Acad Manag Rev 20(3):709–734

    Google Scholar 

  43. Zahedi FM, Song J (2008) Dynamics of trust revision: using health infomediaries. J Manag Inf Syst 24(4):225–248

    Google Scholar 

  44. Gefen D, Karahanna E, Straub DW (2003) Trust and TAM in online shopping: an integrated model. MIS Quart 27(1):51–90

    Google Scholar 

  45. Fishbein M, Ajzen I (1975) Belief, attitude, intention and behavior: an introduction to theory and research. Addison-Wesley, Reading

    Google Scholar 

  46. Straub D, Boudreau M-C, Gefen D (2004) Validation guidelines for IS positivist research. Commun AIS 13:380–427

    Google Scholar 

  47. McKnight DH, Choudhury V, Kacmar C (2002) Developing and validating trust measures for e-commerce: an integrative typology. Inf Syst Res 13(3):334–359

    Article  Google Scholar 

  48. Podsakoff PM et al (2003) Common method biases in behavioral research: a critical review of the literature and recommended remedies. J Appl Psychol 88(5):879–903

    Article  Google Scholar 

  49. Malhotra NK, Kim SS, Patil A (2006) Common method variance in IS research: a comparison of alternative approaches and a reanalysis of past research. Manage Sci 52(12):1865–1883

    Article  Google Scholar 

  50. Anderson JC, Gerbing DW (1988) Structural equation modeling in practice: a review and recommended two-step approach. Psychol Bull 103(3):411–423

    Article  Google Scholar 

  51. Gefen D, Straub DW, Boudreau MC (2000) Structural equation modeling and regression: guidelines for research practice. Commun Assoc Inf Syst 4(7):1–70

    Google Scholar 

  52. Bagozzi RP, Yi Y (1988) On the evaluation of structural equation models. J Acad Market Sci 16(1):74–94

    Article  Google Scholar 

  53. Nunnally JC (1978) Psychometric theory. McGraw-Hill, New York

    Google Scholar 

  54. Fornell C, Larcker DF (1981) Evaluating structural equation models with unobservable variables and measurement error. J Mark Res 18(1):39–50

    Article  Google Scholar 

  55. Baron RM, Kenny DA (1986) The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol 51(6):1173–1182

    Article  Google Scholar 

Download references

Acknowledgment

This work was partially supported by a grant from the National Natural Science Foundation of China (71001030), a grant from the Zhejiang Provincial Natural Science Foundation (Y7100057), and a grant from Zhijiang Social Science Young Scholar Plan (G94).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tao Zhou.

Appendix: measurement scales and items

Appendix: measurement scales and items

Structural assurance (SA) (adapted from McKnight et al. [47])

  • SA1: I feel confident that encryption and other technological advances on the mobile Internet make it safe for me to use mobile banking.

  • SA2: I feel assured that legal and technological structures adequately protect me from payment problems on the mobile Internet.

  • SA3: Mobile Internet is a robust and safe environment in which to use mobile banking.

Ubiquity (UBI) (adapted from Lee [38])

  • UBI1: I can use mobile banking from anywhere.

  • UBI2: I can use mobile banking at anytime.

  • UBI3: If needed, I can use mobile banking at anytime from anywhere.

Perceived ease of use (EOU) (adapted from Agarwal and Karahanna [41])

  • EOU1: Learning to use mobile banking is easy for me.

  • EOU2: Skillfully using mobile banking is easy for me.

  • EOU3: Overall, mobile banking is easy to use.

Personal innovativeness (PI) (adapted from Agarwal and Karahanna [41])

  • PI1: If I heard about a new information technology, I will look for ways to experiment with it.

  • PI2: Among my peers, I am usually the first to try out new information technologies.

  • PI3: I like to experiment with new information technologies.

Trust (TRU) (adapted from Lee [38])

  • TRU1: Mobile banking is trustworthy.

  • TRU2: Mobile banking keeps its promise.

  • TRU3: Mobile banking keeps customers’ interests in mind.

Flow experience (FLOW) (adapted from Lee et al. [14])

  • FLOW1: When using mobile banking, my attention was focused on the activity.

  • FLOW2: When using mobile banking, I felt in control.

  • FLOW3: When using mobile banking, I found a lot of pleasure.

Usage intention (USE) (adapted from Lee [38])

  • USE1: Given the chance, I intend to use mobile banking.

  • USE2: I expect my use of mobile banking to continue in future.

  • USE3: I have intention to use mobile banking to conduct payment.

Actual usage (ACTUSE)

  • How many times do you use mobile banking during a week?

  • Not at all; less than once a week; about once a week; 2–3 times a week; 4–5 times a week; about once a day; several times each day.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhou, T. Examining mobile banking user adoption from the perspectives of trust and flow experience. Inf Technol Manag 13, 27–37 (2012). https://doi.org/10.1007/s10799-011-0111-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10799-011-0111-8

Keywords

Navigation