Advertisement

Information Technology and Management

, Volume 15, Issue 1, pp 37–49 | Cite as

Understanding the evolution of consumer trust in mobile commerce: a longitudinal study

  • Jiabao LinEmail author
  • Bin Wang
  • Na Wang
  • Yaobin Lu
Article

Abstract

Consumer trust in mobile commerce (m-commerce) is dynamic. However, little research has examined how consumer trust in m-commerce evolves over time. Based on the extended valence theory, the self-perception theory, and the information systems expectation confirmation theory, this study examines a three-stage theoretical model of consumer trust evolution in mobile banking. We focus on the formation mechanisms of a consumer’s decision in the pre-usage stage, the feedback mechanisms of usage behavior in the usage stage, and the evaluation mechanisms in the post-usage stage. By analyzing longitudinal data collected from 332 individuals through two rounds of surveys, we find that pre-use trust has both direct and indirect influences on mobile banking usage behavior. Usage behavior provides significant feedbacks on cognitive or psychological factors, and customers’ evaluations have significant impacts on satisfaction. Satisfaction enhances post-use trust, which in turn affects future usage behavior. We also find that pre-use trust has a long term impact on post-use trust. Together, these results illustrate the dynamic process through which m-commerce consumer trust transforms.

Keywords

Mobile commerce Mobile banking Pre-use trust Post-use trust 

Notes

Acknowledgments

We thank the Editors-in-Chief and the anonymous reviewers for their valuable comments and suggestions on this research. This work was substantially supported by a Grant from the Humanities and Social Sciences Foundation of the Ministry of Education (11YJC630115), a Grant from the Foundation for Distinguished Young Talents in Higher Education of Guangdong (wym11029), the Grants from the NSFC (71333004, 71332001 and 71061160505) and the Specialized Research Fund for the Doctoral Program of Higher Education (20120142110042). This work was also supported by the Modern Information Management Research Centre at HUST, National 985 Project of Non-traditional Security at HUST and TD-SCDMA Joint Innovation Lab, Hubei Mobile Co., China Mobile Group.

References

  1. 1.
    3G Portal (2011) China’s mobile banking user research reports. Available at www.3g.cn
  2. 2.
    Awad NF, Ragowsky A (2008) Establishing trust in electronic commerce through online word of mouth: an examination across genders. J Manag Inform Syst 24(2):101–121CrossRefGoogle Scholar
  3. 3.
    Bagozzi R, Yi Y (1998) On the evaluation of structural equation models. J Acad Mark Sci 16(1):74–94CrossRefGoogle Scholar
  4. 4.
    Balasubramanian S, Peterson RA, Jarvenpaa SL (2002) Exploring the implications of m-commerce for markets and marketing. J Acad Mark Sci 30(4):348–361CrossRefGoogle Scholar
  5. 5.
    Bem D (1972) Self-perception theory. In: Berkowitz L (ed) Advances in experimental social psychology. Academic Press, New YorkGoogle Scholar
  6. 6.
    Bhattacherjee A (2001) Understanding information systems continuance: an expectation-confirmation model. MIS Q 25(3):351–370CrossRefGoogle Scholar
  7. 7.
    Bhattacherjee A (2001) An empirical analysis of the antecedents of electronic commerce service continuance. Decis Support Syst 32(2):201–214CrossRefGoogle Scholar
  8. 8.
    Butner OB, Goitz AS (2008) Perceived trustworthiness of online shops. J Consumer Behav 7(1):35–50CrossRefGoogle Scholar
  9. 9.
    Campbell DT, Fiske DW (1959) Convergent and discriminant validation by the multitrait-multimethod matrix. Psychol Bull 56(2):81–105CrossRefGoogle Scholar
  10. 10.
    CNNIC (2012) The 29th statistical survey report on Internet development in China. China Internet Network Information Center, Available at www.cnnic.net.cn
  11. 11.
    Cook TD, Campbell DT, Day A (1979) Quasi-experimentation: design & analysis issues for field settings. Houghton Mifflin, BostonGoogle Scholar
  12. 12.
    Cunningham SM (1967) The major dimensions of perceived risk. In: Cox DF (ed) Risk taking and information handling in consumer behavior. Harvard University Press, BostonGoogle Scholar
  13. 13.
    Davis F (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 13(3):319–340CrossRefGoogle Scholar
  14. 14.
    Doney PM, Cannon JP (1997) An examination of the nature of trust in buyer-seller relationships. J Mark 61(2):35–51CrossRefGoogle Scholar
  15. 15.
    Featherman M, Pavlou P (2003) Predicting e-services adoption: a perceived risk facets perspective. Int J Hum Comput Stud 59(4):451–474CrossRefGoogle Scholar
  16. 16.
    Fishbein M, Ajzen I (1975) Belief, attitude, intention, and behavior: an introduction to theory and research. Addison-Wesley, ReadingGoogle Scholar
  17. 17.
    Fornell C, Larcker DF (1981) Evaluating structural equation models with unobservable variables and measurement error. J Mark Res 18(1):39–50CrossRefGoogle Scholar
  18. 18.
    Ganesan S (1994) Determinants of long-term orientation in buyer-seller relationships. J Mark 58(2):1–19CrossRefGoogle Scholar
  19. 19.
    Garbarino E, Johnson M (1999) The different roles of satisfaction, trust, and commitment in customer relationships. J Mark 63(2):70–87CrossRefGoogle Scholar
  20. 20.
    Gefen D, Karahanna E, Straub DW (2003) Trust and TAM in online shopping: an integrated model. MIS Q 27(1):51–90Google Scholar
  21. 21.
    Gefen D, Karahanna E, Straub DW (2003) Inexperience and experience with online stores: the importance of TAM and trust. IEEE Trans Eng Manage 50(3):307–321CrossRefGoogle Scholar
  22. 22.
    Hu X, Wu G, Wu Y, Zhang H (2010) The effects of web assurance seals on consumers’ initial trust in an online vendor: a functional perspective. Decis Support Syst 48(2):407–418CrossRefGoogle Scholar
  23. 23.
    Jones K, Leonard LNK (2008) Trust in consumer-to-consumer electronic commerce. Inform Manag 45(2):88–95CrossRefGoogle Scholar
  24. 24.
    Khansa L, Zobel CW, Goicochea G (2012) Creating a taxonomy for mobile commerce innovations using social network and cluster analyses. Int J Elect Commer 16(4):19–52CrossRefGoogle Scholar
  25. 25.
    Kim DJ, Ferrin DL, Rao HR (2008) A trust-based consumer decision-making model in electronic commerce: the role of trust, perceived risk, and their antecedents. Decis Support Syst 44(2):544–564CrossRefGoogle Scholar
  26. 26.
    Kim DJ, Ferrin DL, Rao HR (2009) Trust and satisfaction, two stepping stones for successful e-commerce relationships: a longitudinal exploration. Inform Syst Res 20(2):237–257CrossRefGoogle Scholar
  27. 27.
    Kim G, Shin B, Lee HG (2009) Understanding dynamics between initial trust and usage intentions of mobile banking. Inform Syst J 19(3):283–311CrossRefGoogle Scholar
  28. 28.
    Kim SS, Malhotra NK (2005) A longitudinal model of continued IS use: an integrative view of four mechanisms underlying postadoption phenomena. Manage Sci 51(5):741–755CrossRefGoogle Scholar
  29. 29.
    Kim SS, Malhotra NK, Narasimhan S (2005) Two competing perspectives on automatic use: a theoretical and empirical comparison. Inform Syst Res 16(4):418–432CrossRefGoogle Scholar
  30. 30.
    Lee JN, Choi B (2011) Effects of initial and ongoing trust in IT outsourcing: a bilateral perspective. Inform Manag 48(2–3):96–105CrossRefGoogle Scholar
  31. 31.
    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
  32. 32.
    Lee MC (2009) Predicting and explaining the adoption of online trading: an empirical study in Taiwan. Decis Support Syst 47(2):133–142CrossRefGoogle Scholar
  33. 33.
    Lowry PB, Vance A, Moody G, Beckman B, Read A (2008) Explaining and predicting the impact of branding alliances and web site quality on initial consumer trust of e- commerce web sites. J Manag Inform Syst 24(4):199–224CrossRefGoogle Scholar
  34. 34.
    Luarn P, Lin HH (2005) Toward an understanding of the behavioral intention to use mobile banking. Comput Hum Behav 21(6):873–891CrossRefGoogle Scholar
  35. 35.
    Mayer RC, Davis JH, Schoorman FD (1995) An integrative model of organizational trust. Acad Manag Rev 20(3):709–734Google Scholar
  36. 36.
    McKnight DH, Choudhury V, Kacmar C (2002) The impact of initial consumer trust on intentions to transact with a web site: a trust building model. J Strateg Inf Syst 11(3/4):297–323CrossRefGoogle Scholar
  37. 37.
    Melone NP (1990) A theoretical assessment of the user-satisfaction construct in information systems research. Manage Sci 36(1):76–91CrossRefGoogle Scholar
  38. 38.
    Moorman C, Zaltman G, Deshpande R (1992) Relationships between providers and users of market research: the dynamics of trust within and between organizations. J Mark Res 29(3):314–328CrossRefGoogle Scholar
  39. 39.
    Nunally JC (1978) Psychometric theory. McGraw-Hill, New YorkGoogle Scholar
  40. 40.
    Oliver R, Burke R (1999) Expectation processes in satisfaction formation: a field study. J Serv Res 1(3):196–214CrossRefGoogle Scholar
  41. 41.
    Oliver R, DeSarbo W (1988) Response determinants in satisfaction judgments. J Consumer Res 14(4):495CrossRefGoogle Scholar
  42. 42.
    Ouellette J, Wood W (1998) Habit and intention in everyday life: the multiple processes by which past behavior predicts future behavior. Psychol Bull 124(1):54–74CrossRefGoogle Scholar
  43. 43.
    Pavlou PA (2003) Consumer acceptance of electronic commerce: integrating trust and risk with the technology acceptance model. Int J Elect Commer 7(3):69–103Google Scholar
  44. 44.
    Peter J, Ryan M (1976) An investigation of perceived risk at the brand level. J Mark Res 13(2):184–188CrossRefGoogle Scholar
  45. 45.
    Peter JP, Tarpey LX (1975) A comparative analysis of three consumer decisions strategies. J Consumer Res 2(1):29–37CrossRefGoogle Scholar
  46. 46.
    Podsakoff PM, MacKenzie SB, Lee J-Y, Podsakoff NP (2003) Common method biases in behavioral research: a critical review of the literature and recommended remedies. J Appl Psychol 88(5):879–903CrossRefGoogle Scholar
  47. 47.
    Premkumar G, Bhattacherjee A (2008) Explaining information technology usage: a test of competing models. Omega 36(1):64–75CrossRefGoogle Scholar
  48. 48.
    Rousseau D, Sitkin S, Burt R, Camerer C (1998) Not so different after all: a cross-discipline view of trust. Acad Manag Rev 23(3):393–404CrossRefGoogle Scholar
  49. 49.
    Serenko A, Bontis N (2004) A model of user adoption of mobile portals. Q J Electron Commer 4(1):69–98Google Scholar
  50. 50.
    Siau K, Lim EP, Shen Z (2001) Mobile commerce: promises, challenges, and research agenda. J Database Manag 12(3):4–5CrossRefGoogle Scholar
  51. 51.
    Siau K, Shen Z (2003) Building customer trust in mobile commerce. Commun ACM 46(4):91–94CrossRefGoogle Scholar
  52. 52.
    Singh J, Sirdeshmukh D (2000) Agency and trust mechanisms in consumer satisfaction and loyalty judgments. J Acad Mark Sci 28(1):150–167CrossRefGoogle Scholar
  53. 53.
    Song P, Zhang C, Chen W, Huang L (2009) Understanding usage-transfer behavior between nonsubstitutable technologies: evidence from instant messenger and portal. IEEE Trans Eng Manag 56(3):412–424CrossRefGoogle Scholar
  54. 54.
    Urban GL, Amyx C, Lorenzon A (2009) Online trust: state of the art, new frontiers, and research potential. J Interact Mark 2(2):179–190CrossRefGoogle Scholar
  55. 55.
    Vance A, Cosaque CED, Straub DW (2008) Examining trust in information technology artifacts: the effects of system quality and culture. J Manag Inform Syst 24(4):73–100CrossRefGoogle Scholar
  56. 56.
    Vatanasombut B, Igbaria M, Stylianou AC, Rodgers W (2008) Information systems continuance intention of web-based applications customers: the case of online banking. Inform Manag 45(7):419–428CrossRefGoogle Scholar
  57. 57.
    Yeh Y, Li Y (2009) Building trust in m-commerce: contributions from quality and satisfaction. Online Inform Rev 33(6):1066–1086CrossRefGoogle Scholar
  58. 58.
    Yousafzai SY, Pallister JG, Foxal GR (2005) Strategies for building and communicating trust in electronic banking: a field experiment. Psychol Mark 22(2):181–201CrossRefGoogle Scholar
  59. 59.
    Zhang L, Zhu J, Liu Q (2012) A meta-analysis of mobile commerce adoption and the moderating effect of culture. Comput Hum Behav 28(5):1902–1911CrossRefGoogle Scholar
  60. 60.
    Zucker LG (1986) Production of trust: institutional sources of economic structure. JAI Press, GreenwichGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.College of Economics and ManagementSouth China Agricultural UniversityGuangzhouChina
  2. 2.College of Business AdministrationUniversity of Texas-Pan AmericanEdinburgUSA
  3. 3.College of Information Sciences and TechnologyThe Pennsylvania State UniversityUniversity ParkUSA
  4. 4.School of ManagementHuazhong University of Science and TechnologyWuhanChina

Personalised recommendations