Information Technology and Management

, Volume 13, Issue 1, pp 27–37 | Cite as

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

  • Tao ZhouEmail author


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.


Trust Flow experience Mobile banking Structural assurance 



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).


  1. 1.
    CNNIC (2011) 28th Statistical survey report on the internet development in China. China Internet Network Information Center, BeijingGoogle Scholar
  2. 2.
    iResearch (2009) China mobile payment research reportGoogle Scholar
  3. 3.
    Kim G, Shin B, Lee HG (2009) Understanding dynamics between initial trust and usage intentions of mobile banking. Inf Syst J 19(3):283–311CrossRefGoogle Scholar
  4. 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):385–392CrossRefGoogle Scholar
  5. 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):222–234CrossRefGoogle Scholar
  6. 6.
    Hoffman DL, Novak TP (2009) Flow online: lessons learned and future prospects. J Interact Market 23(1):23–34CrossRefGoogle Scholar
  7. 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):857–869CrossRefGoogle Scholar
  8. 8.
    Varnali K, Toker A (2010) Mobile marketing research: the-state-of-the-art. Int J Inf Manag 30(2):144–151CrossRefGoogle Scholar
  9. 9.
    Siau K, Shen Z (2003) Building customer trust in mobile commerce. Commun ACM 46(4):91–94CrossRefGoogle Scholar
  10. 10.
    Lin HH, Wang YS (2006) An examination of the determinants of customer loyalty in mobile commerce contexts. Inf Manag 43(3):271–282CrossRefGoogle Scholar
  11. 11.
    Li Y-M, Yeh Y-S (2010) Increasing trust in mobile commerce through design aesthetics. Comput Hum Behav 26(4):673–684CrossRefGoogle Scholar
  12. 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):73–100Google Scholar
  13. 13.
    Laforet S, Li X (2005) Consumers’ attitudes towards online and mobile banking in China. Int J Bank Market 23(5):362–380CrossRefGoogle Scholar
  14. 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):729–741CrossRefGoogle Scholar
  15. 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):115–125CrossRefGoogle Scholar
  16. 16.
    Al-Somali SA, Gholami R, Clegg B (2009) An investigation into the acceptance of online banking in Saudi Arabia. Technovation 29(2):130–141CrossRefGoogle Scholar
  17. 17.
    Liao Z, Cheung MT (2008) Measuring consumer satisfaction in internet banking: a core framework. Commun ACM 51(4):47–51CrossRefGoogle Scholar
  18. 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):336–351CrossRefGoogle Scholar
  19. 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):252–260CrossRefGoogle Scholar
  20. 20.
    Shen YC et al (2010) A benefit-cost perspective of the consumer adoption of the mobile banking system. Behav Inf Technol 29(5):497–511CrossRefGoogle Scholar
  21. 21.
    Csikszentmihalyi M, Csikszentmihalyi IS (1988) Optimal experience: psychological studies of flow in consciousness. Cambridge University Press, Cambridge, UKGoogle Scholar
  22. 22.
    Novak TP, Hoffman DL, Yung Y-F (2000) Measuring the customer experience in online environments: a structural modeling approach. Market Sci 19(1):22–42CrossRefGoogle Scholar
  23. 23.
    Huang M-H (2006) Flow, enduring, and situational involvement in the web environment: a tripartite second-order examination. Psychol Market 23(5):383–411CrossRefGoogle Scholar
  24. 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):23–31CrossRefGoogle Scholar
  25. 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):822–832CrossRefGoogle Scholar
  26. 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):937–954CrossRefGoogle Scholar
  27. 27.
    Hausman AV, Siekpe JS (2009) The effect of web interface features on consumer online purchase intentions. J Bus Res 62(1):5–13CrossRefGoogle Scholar
  28. 28.
    O’Cass A, Carlson J (2010) Examining the effects of website induced flow in professional sporting team websites. Internet Res 20(2):115–134CrossRefGoogle Scholar
  29. 29.
    Chang HH, Wang IC (2008) An investigation of user communication behavior in computer mediated environments. Comput Hum Behav 24(5):2336–2356CrossRefGoogle Scholar
  30. 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):837–856Google Scholar
  31. 31.
    Guo YM, Poole MS (2009) Antecedents of flow in online shopping: a test of alternative models. Inf Syst J 19(4):369–390CrossRefGoogle Scholar
  32. 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):1009–1018CrossRefGoogle Scholar
  33. 33.
    Deng L et al (2010) User experience, satisfaction, and continual usage intention of IT. Eur J Inf Syst 19(1):60–75CrossRefGoogle Scholar
  34. 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):123–129CrossRefGoogle Scholar
  35. 35.
    Ha I, Yoon Y, Choi M (2007) Determinants of adoption of mobile games under mobile broadband wireless access environment. Inf Manag 44(3):276–286CrossRefGoogle Scholar
  36. 36.
    Pavlou PA, Gefen D (2004) Building effective online marketplaces with institution-based trust. Inf Syst Res 15(1):37–59CrossRefGoogle Scholar
  37. 37.
    Song J, Zahedi FM (2007) Trust in health infomediaries. Decis Support Syst 43(2):390–407CrossRefGoogle Scholar
  38. 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):165–180Google Scholar
  39. 39.
    Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quart 13(3):319–340CrossRefGoogle Scholar
  40. 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):380–393CrossRefGoogle Scholar
  41. 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):665–694CrossRefGoogle Scholar
  42. 42.
    Mayer RC, Davis JH, Schoorman FD (1995) An integrative model of organizational trust. Acad Manag Rev 20(3):709–734Google Scholar
  43. 43.
    Zahedi FM, Song J (2008) Dynamics of trust revision: using health infomediaries. J Manag Inf Syst 24(4):225–248Google Scholar
  44. 44.
    Gefen D, Karahanna E, Straub DW (2003) Trust and TAM in online shopping: an integrated model. MIS Quart 27(1):51–90Google Scholar
  45. 45.
    Fishbein M, Ajzen I (1975) Belief, attitude, intention and behavior: an introduction to theory and research. Addison-Wesley, ReadingGoogle Scholar
  46. 46.
    Straub D, Boudreau M-C, Gefen D (2004) Validation guidelines for IS positivist research. Commun AIS 13:380–427Google Scholar
  47. 47.
    McKnight DH, Choudhury V, Kacmar C (2002) Developing and validating trust measures for e-commerce: an integrative typology. Inf Syst Res 13(3):334–359CrossRefGoogle Scholar
  48. 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):879–903CrossRefGoogle Scholar
  49. 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):1865–1883CrossRefGoogle Scholar
  50. 50.
    Anderson JC, Gerbing DW (1988) Structural equation modeling in practice: a review and recommended two-step approach. Psychol Bull 103(3):411–423CrossRefGoogle Scholar
  51. 51.
    Gefen D, Straub DW, Boudreau MC (2000) Structural equation modeling and regression: guidelines for research practice. Commun Assoc Inf Syst 4(7):1–70Google Scholar
  52. 52.
    Bagozzi RP, Yi Y (1988) On the evaluation of structural equation models. J Acad Market Sci 16(1):74–94CrossRefGoogle Scholar
  53. 53.
    Nunnally JC (1978) Psychometric theory. McGraw-Hill, New YorkGoogle Scholar
  54. 54.
    Fornell C, Larcker DF (1981) Evaluating structural equation models with unobservable variables and measurement error. J Mark Res 18(1):39–50CrossRefGoogle Scholar
  55. 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):1173–1182CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.School of ManagementHangzhou Dianzi UniversityHangzhouPeople’s Republic of China

Personalised recommendations