Skip to main content
SpringerLink
Log in

Understanding continuance usage intention of mobile internet sites

  • Long paper
  • Published:
Universal Access in the Information Society Aims and scope Submit manuscript

Abstract

Due to the high acquisition costs and low switching costs, retaining users and facilitating their continuance usage are crucial for mobile service providers. Integrating both perspectives of perceived utility and flow experience, this research identifies the factors affecting continuance usage intention of mobile internet sites. Data were collected through a survey, and data analysis was then conducted with structural equation modeling. The results indicated that system quality and information quality affect perceived usefulness, satisfaction and flow. And these three factors determine continuance usage intention. Among them, flow has the largest effect on continuance usage intention. The results imply that service providers need to improve users’ experience in order to facilitate their continuance usage of mobile internet sites.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Anderson, J.C., Gerbing, D.W.: Structural equation modeling in practice: a review and recommended two-step approach. Psychol. Bull. 103(3), 411–423 (1988)

    Article  Google Scholar 

  2. Animesh, A., Pinsonneault, A., Yang, S.B., Oh, W.: An odyssey into virtual worlds: exploring the impacts of technological and spatial environments on intention to purchase virtual products. MIS Q 35(3), 789–810 (2011)

    Google Scholar 

  3. Beaudry, A., Pinsonneault, A.: The other side of acceptance: studying the direct and indirect effects of emotions on information technology use. MIS Q 34(4), 689–710 (2010)

    Google Scholar 

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

    Article  Google Scholar 

  5. Chatterjee, S., Chakraborty, S., Sarker, S., Sarker, S., Lau, F.Y.: Examining the success factors for mobile work in healthcare: a deductive study. Decis. Support Syst. 46(3), 620–633 (2009)

    Article  Google Scholar 

  6. Chung, N., Kwon, S.J.: Effect of trust level on mobile banking satisfaction: a multi-group analysis of information system success instruments. Behav. Inf. Technol 28(6), 549–562 (2009)

    Article  Google Scholar 

  7. CNNIC, 30th Statistical Survey Report on the Internet Development in China. China Internet Network Information Center (2012)

  8. CNNIC, China Mobile Browser User Behavior Report. China Internet Network Information Center (2012)

  9. Csikszentmihalyi, M., Csikszentmihalyi, I.S.: Optimal experience: psychological studies of flow in consciousness. Cambridge University Press, Cambridge (1988)

    Book  Google Scholar 

  10. Davis, F.D.: Perceived usefulness, Perceived ease of use, and user acceptance of information technology. MIS Q 13(3), 319–340 (1989)

    Article  Google Scholar 

  11. Davis, F.D., Bagozzi, R.P., Warshaw, P.R.: Extrinsic and intrinsic motivation to use computers in the workplace. J. App. Soc. Psychol 22(14), 1111–1132 (1992)

    Article  Google Scholar 

  12. DeLone, W.H., McLean, E.R.: Measuring e-Commerce success: applying the DeLone and McLean information systems success model. Int. J. Electron. Commer 9(1), 31–47 (2004)

    Google Scholar 

  13. Deng, L., Turner, D.E., Gehling, R., Prince, B.: User experience, satisfaction, and continual usage intention of IT. Eur. J. Inf. Syst 19(1), 60–75 (2010)

    Article  Google Scholar 

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

    Google Scholar 

  15. Goel, L., Johnson, N.A., Junglas, I., Ives, B.: From space to place: predicting users’ intentions to return to virtual worlds. MIS Q 35(3), 749–771 (2011)

    Google Scholar 

  16. Goodhue, D.L., Thompson, R.L.: Task-technology fit and individual performance. MIS Q 19(2), 213–236 (1995)

    Article  Google Scholar 

  17. Guo, Y.M., Poole, M.S.: Antecedents of flow in online shopping: a test of alternative models. Inf. Syst. J 19(4), 369–390 (2009)

    Article  Google Scholar 

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

    Article  Google Scholar 

  19. Hausman, A.V., Siekpe, J.S.: The effect of web interface features on consumer online purchase intentions. J. Bus. Res. 62(1), 5–13 (2009)

    Article  Google Scholar 

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

    Article  Google Scholar 

  21. Hoffman, D.L., Novak, T.P.: Marketing in hypermedia computer-mediated environments: conceptual foundations. J. Mark 60(3), 50–68 (1996)

    Article  Google Scholar 

  22. Hsu, C.-L., Lu, H.-P., Hsu, H-.H.: Adoption of the mobile Internet: an empirical study of multimedia message service (MMS). Omega 35(6), 715–726 (2007)

    Article  Google Scholar 

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

    Article  Google Scholar 

  24. Junglas, I., Abraham, C., Watson, R.T.: Task-technology fit for mobile locatable information systems. Decis. Support Syst. 45(4), 1046–1057 (2008)

    Article  Google Scholar 

  25. Kim, B., Oh, J.: The difference of determinants of acceptance and continuance of mobile data services: a value perspective. Expert Syst. Appl. 38(3), 1798–1804 (2010)

    Article  Google Scholar 

  26. Kim, D.J., Hwang, Y.: A study of mobile internet user’s service quality perceptions from a user’s utilitarian and hedonic value tendency perspectives. Inf. Syst. Frontier 14(2), 409–421 (2012)

    Article  Google Scholar 

  27. Kim, H.W., Xu, Y., Koh, J.: A comparison of online trust building factors between potential customers and repeat customers. J. Assoc. Inf. Syst 5(10), 392–420 (2004)

    Google Scholar 

  28. Kuo, Y.-F., Wu, C.-M., Deng, W.-J.: The relationships among service quality, perceived value, customer satisfaction, and post-purchase intention in mobile value-added services. Comput. Human Behav 25(4), 887–896 (2009)

    Article  Google Scholar 

  29. Lee, K.C., Chung, N.: 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 (2009)

    Article  Google Scholar 

  30. Lee, K.C., Kang, I.W., McKnight, D.H.: Transfer from offline trust to key online perceptions: an empirical study. IEEE Trans. Eng. Manag 54(4), 729–741 (2007)

    Article  Google Scholar 

  31. Lee, S., Shin, B., Lee, H.G.: Understanding post-adoption usage of mobile data services: the role of supplier-side variables. J. Assoc. Inf. Syst 10(12), 860–888 (2009)

    Google Scholar 

  32. Liang, T.P., Yeh, Y.H.: Effect of use contexts on the continuous use of mobile services: the case of mobile games. Pers. Ubiquitous Comput 15(2), 187–196 (2011)

    Article  Google Scholar 

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

    Article  Google Scholar 

  34. Liu, C.T., Guo, Y.M., Lee, C.H.: The effects of relationship quality and switching barriers on customer loyalty. Int. J. Inf. Manag 31(1), 71–79 (2011)

    Article  Google Scholar 

  35. Malhotra, N.K., Kim, S.S., Patil, A.: Common method variance in IS research: a comparison of alternative approaches and a reanalysis of past research. Manag. Sci 52(12), 1865–1883 (2006)

    Article  Google Scholar 

  36. Mallat, N.: Exploring consumer adoption of mobile payments—A qualitative study. J. Strateg. Inf. Syst 16(4), 413–432 (2007)

    Article  Google Scholar 

  37. Ngai, E.W.T., Gunasekaran, A.: A review for mobile commerce research and applications. Decis. Support Syst. 43(1), 3–15 (2007)

    Article  Google Scholar 

  38. Nunnally, J.C.: Psychometric theory. McGraw-Hill, New York (1978)

    Google Scholar 

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

    Article  Google Scholar 

  40. Park, J., Yang, S., Lehto, X.: Adoption of mobile technologies for Chinese consumers. J. Electron. Commer. Res 8(3), 196–206 (2007)

    Google Scholar 

  41. Podsakoff, P.M., Organ, D.W.: Self-reports in organizational research: problems and prospects. J. Manag 12(4), 531–544 (1986)

    Google Scholar 

  42. Reichheld, F.F., Schefter, P.: E-loyalty: your secret weapon on the Web. Harv. Bus. Rev 7–8, 105–113 (2000)

    Google Scholar 

  43. Rogers, E.M.: Diffusion of Innovations. The Free Press, New York (1983)

    Google Scholar 

  44. Schierz, P.G., Schilke, O., Wirtz, B.W.: Understanding consumer acceptance of mobile payment services: an empirical analysis. Electron. Commer. Res. Appl. 9(3), 209–216 (2010)

    Article  Google Scholar 

  45. Shin, Y.M., Lee, S.C., Shin, B., Lee, H.G.: Examining influencing factors of post-adoption usage of mobile internet: focus on the user perception of supplier-side attributes. Inf. Syst. Frontier 12(5), 595–606 (2010)

    Article  Google Scholar 

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

    Google Scholar 

  47. Suki, N.M., Ramayah, T., Ly, K.K.: Empirical investigation on factors influencing the behavioral intention to use Facebook. Univers. Access Inf. Soc 11(2), 223–231 (2012)

    Article  Google Scholar 

  48. Teo, T.S.H., Srivastava, S.C., Jiang, L.: Trust and electronic government success: an Empirical Study. J. Manag. Inf. Syst 25(3), 99–131 (2009)

    Article  Google Scholar 

  49. Thong, J.Y.L., Venkatesh, V., Xu, X., Hong, S.-J., Tam, K.Y.: Consumer acceptance of personal information and communication technology services. IEEE Trans. Eng. Manag 58(4), 613–625 (2011)

    Article  Google Scholar 

  50. Van der Heijden, H.: User acceptance of hedonic information systems. MIS Q 28(4), 695–704 (2004)

    Google Scholar 

  51. Venkatesh, V., Davis, F.D.: A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag. Sci 46(2), 186–204 (2000)

    Article  Google Scholar 

  52. 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)

    Google Scholar 

  53. Wang, L.C., Baker, J., Wagner, J.A., Wakefield, K.: Can a retail web site be social? J. Mark 71, 143–157 (2007)

    Article  Google Scholar 

  54. Wixom, B.H., Todd, P.A.: A Theoretical Integration of user satisfaction and technology acceptance. Inf. Syst. Res 16(1), 85–102 (2005)

    Article  Google Scholar 

  55. Wu, I.-L., Li, J.-Y., Fu, C.-Y.: The adoption of mobile healthcare by hospital’s professionals: an integrative perspective. Decis. Support Syst. 51(3), 587–596 (2011)

    Article  Google Scholar 

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

    Article  Google Scholar 

  57. Yuan, Y., Archer, N., Connelly, C.E., Zheng, W.: Identifying the ideal fit between mobile work and mobile work support. Inf. Manag 47(3), 125–137 (2010)

    Article  Google Scholar 

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

    Article  Google Scholar 

  59. Zhang, Y., Fang, Y., Wei, K-.K., Ramsey, E., McCole, P., Chen, H.: Repurchase intention in B2C e-commerce—A relationship quality perspective. Inf. Manag 48(6), 192–200 (2011)

    Article  Google Scholar 

  60. Zhou, T.: Examining the critical success factors of mobile website adoption. Online Inf. Rev 35(4), 636–652 (2011)

    Article  Google Scholar 

  61. Zhou, T.: Understanding mobile Internet continuance usage from the perspectives of UTAUT and flow. Inf. Dev 27(3), 207–218 (2011)

    Article  Google Scholar 

  62. Zhou, T., Lu, Y.: Examining mobile instant messaging user loyalty from the perspectives of network externalities and flow experience. Comput. Human Behav 27(2), 883–889 (2011)

    Article  Google Scholar 

Download references

Acknowledgments

This work was partially supported by grants from the National Natural Science Foundation of China (71371004, 71001030), and a grant from the Research Center of Information Technology & Economic and Social Development in Zhejiang Province.

Author information

Authors and Affiliations

  1. School of Management, Hangzhou Dianzi University, Hangzhou, 310018, People’s Republic of China

    Tao Zhou

Authors
  1. Tao Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tao Zhou.

Appendix A: Measurement scale and items

Appendix A: Measurement scale and items

1.1 System quality (SYS) (adapted from [27])

  • SYS1: This mobile internet site quickly loads all the text and graphics.

  • SYS2: This mobile internet site is easy to use.

  • SYS3: This mobile internet site is easy to navigate.

  • SYS4: This mobile internet site is visually attractive.

1.2 Information quality (INF) (adapted from [27])

  • INF1: This mobile internet site provides me with information relevant to my needs.

  • INF2: This mobile internet site provides me with sufficient information.

  • INF3: This mobile internet site provides me with accurate information.

  • INF4: This mobile internet site provides me with up-to-date information.

1.3 Perceived usefulness (PU) (adapted from [4])

  • PU1: This mobile internet site can improve my living and working performance.

  • PU2: This mobile internet site can increase my living and working effectiveness.

  • PU3: I feel that this mobile internet site is useful.

1.4 Satisfaction (SAT) (adapted from [4])

  • SAT1: I feel satisfied with using this mobile internet site.

  • SAT2: I feel contented with using this mobile internet site.

  • SAT3: I feel pleased with using this mobile internet site.

1.5 Flow (FLOW) (adapted from [30])

  • FLOW1: When using this mobile internet site, my attention is focused on the activity.

  • FLOW2: When using this mobile internet site, I feel in control.

  • FLOW3: When using this mobile internet site, I find a lot of pleasure.

1.6 Continuance intention (INT) (adapted from [4])

  • INT1: I intend to continue using this mobile internet site rather than discontinue its use.

  • INT2: My intentions are to continue using this mobile internet site than use any alternative sites.

  • INT3: If I could, I would like to discontinue my use of this mobile internet site (reversed item).

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhou, T. Understanding continuance usage intention of mobile internet sites. Univ Access Inf Soc 13, 329–337 (2014). https://doi.org/10.1007/s10209-013-0313-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10209-013-0313-4

Keywords

Search

Navigation