Personal and Ubiquitous Computing

, Volume 12, Issue 1, pp 57–65 | Cite as

An empirical investigation of mobile ticketing service adoption in public transportation

  • Niina Mallat
  • Matti Rossi
  • Virpi Kristiina Tuunainen
  • Anssi Öörni
Original Article

Abstract

In this paper, we present results from a study of mobile ticketing service adoption in public transportation. The theoretical background of the study is based on technology adoption and trust theories, which are augmented with concepts of mobile use context and mobility. Our empirical findings from analyses of a survey data suggest that compatibility of the mobile ticketing service with consumer behavior is a major determinant of adoption. Mobility and contextual factors, including budget constraints, availability of other alternatives, and time pressure in the service use situation were also found to have a strong effect on the adoption decision. Our findings suggest that contextual and mobile service-specific features are important determinants of mobile service adoption and should thus be integrated into the traditional adoption models.

Keywords

Mobile commerce Mobile ticketing adoption Use context Mobility Mobile user behavior Technology adoption 

References

  1. 1.
    Anckar B, D’Incau D (2002) Value creation in mobile commerce: findings from a consumer survey. JITTA J Inf Technol Theory Appl 4:43–64Google Scholar
  2. 2.
    Herzberg A (2003) Payments and banking with mobile personal devices. Commun ACM 46:53–58CrossRefGoogle Scholar
  3. 3.
    Stafford TF, Gilleson ML (2003) Mobile commerce: what it is and what it could be. Commun ACM 46:33–34CrossRefGoogle Scholar
  4. 4.
    Frolick MN, Chen L-d (2004) Assessing m-commerce opportunities. Inf Syst Manage 21:53–61CrossRefGoogle Scholar
  5. 5.
    Siau K, Shen Z (2003) Building customer trust in mobile commerce. Commun ACM 46:91–94CrossRefGoogle Scholar
  6. 6.
    Hung S-Y, Ku C-Y, Chang C-M (2003) Critical factors of WAP services adoption: an empirical study. Electron Commer Res Appl 2:42–60CrossRefGoogle Scholar
  7. 7.
    Teo TSH, Pok SH (2003) Adoption of WAP-enabled mobile phones among Internet users. Omega 31:483–498CrossRefGoogle Scholar
  8. 8.
    Coursaris C, Hassanein K (2002) Understanding m-commerce—a consumer centric model. Q J Electron Commer 3:247–271Google Scholar
  9. 9.
    Lyytinen K, Yoo Y (2002) Research commentary: the next wave of nomadic computing. Inf Syst Res 13:377–388CrossRefGoogle Scholar
  10. 10.
    Weilenmann A (2003) Doing mobility: towards a new perspective on mobility. In: Proceedings of the 26th information systems research seminar in Scandinavia, Haikko, FinlandGoogle Scholar
  11. 11.
    Weiser M (1991) The computer for the twenty-first century, in scientific American, pp 94–104Google Scholar
  12. 12.
    Kleinrock L (1996) Nomadicity: anytime, anywhere in a disconnected world. Mobile Netw Appl 1:351–357Google Scholar
  13. 13.
    Jarvenpaa SL, Lang KR (2005) Managing the paradoxes of mobile technology. Inf Syst Manage 22:7–23CrossRefGoogle Scholar
  14. 14.
    Luff P, Heath C (1998) Mobility in collaboration. In: Proceedings of CSCW ’98Google Scholar
  15. 15.
    Perry M, O’hara K, Sellen A, Brown B, Harper R (2001) “Dealing with mobility: understanding access anytime, anywhere.” ACM Trans Comput–Hum Interact 8:323–347CrossRefGoogle Scholar
  16. 16.
    Kakihara M, Sørensen C (2004) Practicing mobile professional work: tales of locational, operational, and interactional mobility. INFO J Policy Regul Strategy Telecommun 6:180–186CrossRefGoogle Scholar
  17. 17.
    Kristoffersen S, Ljungberg F (1998) Representing modalitites in mobile computing. In: Proceedings of interactive applications of mobile computing, (IMC’98), Rostock, GermanyGoogle Scholar
  18. 18.
    Dourish P (2004) What we talk about when we talk about context. Pers Ubiquit Comput 8:19–30CrossRefGoogle Scholar
  19. 19.
    Dey AK, Abowd GD, Salber D (2001) A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications. Hum–Comput Interact 16:97–166CrossRefGoogle Scholar
  20. 20.
    Kakihara M, Sørensen C (2001) Expanding the ‘Mobility’ concept. ACM SIGGROUP Bull 22:33–37Google Scholar
  21. 21.
    Lee I, Kim J, Kim J (2005) Use contexts for the mobile internet: a longitudinal study monitoring actual use of mobile internet services. Int J Hum–Comput Interact 18:269–292CrossRefGoogle Scholar
  22. 22.
    Schmidt A, Beigl M, Gellersen H-W (1999) There is more to context than location. Comput Graph 23:893–901CrossRefGoogle Scholar
  23. 23.
    Belk RW (1975) Situational variables and consumer behavior. J Consum Res 2:157–164CrossRefGoogle Scholar
  24. 24.
    Sinha I (1994) A conceptual model of the role of situational type on consumer choice behavior and consideration set. Adv Consum Res 21:477–482Google Scholar
  25. 25.
    Dabholkar PA, Bagozzi RP (2002) An attitudinal model of technology-based self-service: Moderating effects of consumer traits and situational factors. J Academy Market Sci 30:184–201Google Scholar
  26. 26.
    Gehrt KC, Yan R-N (2004) Situational, consumer, and retailer factors affecting Internet, catalog, and store shopping. Int J Retail Distrib Manage 32:5–18CrossRefGoogle Scholar
  27. 27.
    Belk RW (1974) An exploratory assessment of situational effects in buyer behavior. J Market Res 11:156–163CrossRefGoogle Scholar
  28. 28.
    Mattson BE (1982) Situational influences on store choice. J Retail 58:46–58Google Scholar
  29. 29.
    Hirschman EC (1982) Situational perception of product prototypes within the product class of consumer payment systems. J Gen Psychol 106:123–140CrossRefGoogle Scholar
  30. 30.
    Wendel S, Dellaert BGC (2005) Situation variation in consumers’ media channel consideration. J Academy Market Sci 33:575–584CrossRefGoogle Scholar
  31. 31.
    Harrison S, Dourish P (1996) Re-placeing space: the roles of place and space in collaborative systems. In: Proceedings of CSCW’96. BostonGoogle Scholar
  32. 32.
    Tamminen S, Oulasvirta A, Toiskallio K, Kankainen A (2004) Understanding mobile contexts. Pers Ubiquit Comput 8:135–143CrossRefGoogle Scholar
  33. 33.
    Davis FD, Bagozzi RP, Warshaw PR (1989) User acceptance of computer-technology—a comparison of two theoretical-models. Manage Sci 35:982–1003Google Scholar
  34. 34.
    Fishbein M, Ajzen I (1975) Belief, attitude, intention and behavior: an introduction to theory and research. Addison-Wesley, ReadingGoogle Scholar
  35. 35.
    Mathieson K (1991) Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior. Inf Syst Res 2:173–191Google Scholar
  36. 36.
    Agarwal R, Prasad J (1999) Are individual differences germane to the acceptance of new information technologies? Decis Sci 30:361–391CrossRefGoogle Scholar
  37. 37.
    Moon JW, Kim YG (2001) Extending the TAM for a world-wide-Web context. Inf Manage 38:217–230CrossRefGoogle Scholar
  38. 38.
    Bruner II GC, Kumar A (2005) Explaining consumer acceptance of handheld Internet devices. J Bus Res 58:553–558CrossRefGoogle Scholar
  39. 39.
    Han S, Harkke V, Mustonen P, Seppänen M, Kallio M (2004) Mobilizing medical information and knowledge: some insights from a survey. In: Proceedings of 12th European conference on information systems, Turku, FinlandGoogle Scholar
  40. 40.
    Kleijnen M, Wetzels M, de Ruyter K (2004) Consumer acceptance of wireless finance. J Fin Serv Market 8:206–217CrossRefGoogle Scholar
  41. 41.
    Rogers EM (1995) Diffusion of innovations. Free Press, New YorkGoogle Scholar
  42. 42.
    Tornatzky LG, Klein KJ (1982) Innovation characteristics and innovation adoption implementation: a meta-analysis of findings. IEEE Trans Eng Manage 29:28–44Google Scholar
  43. 43.
    Moore GC, Benbasat I (1991) Development of an instrument to measure the perceptions of adopting an information technology innovation. Inf Syst Res 2:192–223CrossRefGoogle Scholar
  44. 44.
    Wu J-H, Wang S-C (2005) What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Inf Manage 42:719–729CrossRefGoogle Scholar
  45. 45.
    Kim H-W, Chan HC, Gupta S (2005) Value-based adoption of mobile internet: an empirical investigation. Decision Support Systems (in press)Google Scholar
  46. 46.
    Luarn P, Lin H-H (2005) Toward an understanding of the behavioral intention to use mobile banking. Comput Hum Behav 21:873–891CrossRefGoogle Scholar
  47. 47.
    Lee MSY, McGoldrick PJ, Keeling KA, Doherty J (2003) Using ZMET to explore barriers to the adoption of 3G mobile banking services. Int J Retail Distrib Manage 31:340–348CrossRefGoogle Scholar
  48. 48.
    Jarvenpaa SL, Tractinsky N, Vitale M (2000) Consumer trust in an Internet store. Inf Technol Manage 1:45–71CrossRefGoogle Scholar
  49. 49.
    Pavlou PA (2003) Consumer acceptance of electronic commerce: integrating trust and risk with the technology acceptance model. Int J Electron Commer 7:101–134Google Scholar
  50. 50.
    Featherman MS, Pavlou PA (2003) Predicting e-services adoption: a perceived risk facets perspective. Int J Hum–Comput Stud 59:451–474CrossRefGoogle Scholar
  51. 51.
    Bhattacherjee A (2002) Individual trust in online firms: scale development and initial test. J Manage Inf Syst 19:211–242Google Scholar
  52. 52.
    Grabner-Kräuter S, Kaluscha EA (2003) Empirical research in on-line trust: a review and critical assessment. Int J Hum–Comput Stud 58:783–812CrossRefGoogle Scholar
  53. 53.
    Gefen D, Karahanna E, Straub DW (2003) Trust and TAM in online shopping: an integrated model. MIS Q 27:51–90Google Scholar
  54. 54.
    Gefen D, Straub DW (2004) Consumer trust in B2C e-commerce and the importance of social presence: experiments in e-products and e-services. Omega 32:407–424CrossRefGoogle Scholar
  55. 55.
    McKnight HD, Choudhury V, Kacmar C (2002) Developing and validating trust measures for e-commerce: an integrative typology. Inf Syst Res 13:334–359CrossRefGoogle Scholar
  56. 56.
    Ghosh K, Swaminatha TM (2001) Software security and privacy risks in mobile e-commerce. Commun ACM 44:51–57CrossRefGoogle Scholar
  57. 57.
    Dahlberg T, Mallat N, Öörni A (2003) Consumer acceptance of mobile payment solutions—ease of use, usefulness and trust. In: Proceedings of 2nd international conference on mobile business, Vienna, AustriaGoogle Scholar
  58. 58.
    Hair Jr JF, Anderson RE, Tatham RL, Black WC (1998) Multivariate data analysis, Upper Saddle River. Prentice-Hall NJGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2006

Authors and Affiliations

  • Niina Mallat
    • 2
  • Matti Rossi
    • 1
  • Virpi Kristiina Tuunainen
    • 1
  • Anssi Öörni
    • 1
  1. 1.Helsinki School of EconomicsHelsinkiFinland
  2. 2.Accenture, SITE practiceHelsinkiFinland

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