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Personal and Ubiquitous Computing

, Volume 15, Issue 2, pp 187–196 | Cite as

Effect of use contexts on the continuous use of mobile services: the case of mobile games

  • Ting-Peng Liang
  • Yi-Hsuan Yeh
Original Article

Abstract

As mobile services become more popular and people can use them virtually anywhere, research on the effect of use contexts is gaining more attention. This research presents results from a study of continuous use of mobile services in different use contexts as defined by task and consumption place. Using mobile games as an example, the authors proposed a research model that augments current technology adoption theories to fit the hedonic nature of mobile games. The results from conducting an online survey indicate that contextual factors have significant moderating effect on the intention to play mobile games. The diverse lifestyles of users also have different attitudes and concerns regarding using mobile services. The findings suggest that service providers need to take into account the impact of use contexts and the needs of specific users when they design mobile services.

Keywords

Mobile services Mobile games Use contexts Technology acceptance model Theory of reasoned action 

References

  1. 1.
    Ajzen I, Fishbein M (1980) Understanding attitudes and predicting social behavior. Prentice-Hall, Englewood CliffsGoogle Scholar
  2. 2.
    Baber C, Westmancott O (2004) Social networks and mobile games: the use of bluetooth for a multiplayer card game. MobileHCI2004, pp 98–107Google Scholar
  3. 3.
    Barnard L, Yi JS, Jacko JA, Sears A (2007) Capturing the effects of context on human performance in mobile computing systems. Pers Ubiquitous Comput 11:81–96CrossRefGoogle Scholar
  4. 4.
    Barnes SJ (2002) The mobile commerce value chain: analysis and future developments. Int J Inf Manag 22:91–108Google Scholar
  5. 5.
    Belk RW (1974) An exploratory assessment of situational effects in buyer behavior. J Mark Res 11(2):156–163CrossRefGoogle Scholar
  6. 6.
    Chen LD (2008) A model of consumer acceptance of mobile payment. Int J Mobile Commun 6(1):32–52CrossRefGoogle Scholar
  7. 7.
    Choi J, Seol H, Lee S, Cho H, Park Y (2008) Customer satisfaction factors of mobile commerce in Korea. Internet Res 18(3):313–335CrossRefGoogle Scholar
  8. 8.
    Csikzentmihalyi M (1990) Flow, the psychology of optimal experience. Harper & Row, New YorkGoogle Scholar
  9. 9.
    Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 13(3):319–340CrossRefGoogle Scholar
  10. 10.
    Davis FD, Bagozzi RP, Warshaw PR (1989) User acceptance of computer technology: a comparison of two theoretical models. Manag Sci 35(8):982–1003CrossRefGoogle Scholar
  11. 11.
    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
  12. 12.
    Fang X, Chan S, Brzezinski J, Xu S (2005–2006) Moderating effects of task type on wireless technology acceptance. J Manag Inf Syst 22(3):123–157Google Scholar
  13. 13.
    Fishbein M, Ajzen I (1975) Belief, attitude, intentions and behavior: an introduction to theory and research. Addison-Wesley, MAGoogle Scholar
  14. 14.
    Gebauer J, Shaw MJ (2004) Success factors and impacts of mobile business applications: results from a mobile e-procurement study. Int J Electron Commun 8(3):19–42Google Scholar
  15. 15.
    Ha I, Yoon YS, Choi MK (2007) Determinants of adoption of mobile games under mobile broadband wireless access environment. Inf Manag-Amst 44(3):276–286CrossRefGoogle Scholar
  16. 16.
    Hansen F (1972) Consumer choice behavior: a cognitive theory. Free Press, New YorkGoogle Scholar
  17. 17.
    Herzberg A (2003) Payments and banking with mobile personal devices. Commun ACM 46(5):53–58CrossRefGoogle Scholar
  18. 18.
    Jaeger SR, Rose JM (2008) Stated choice experimentation, contextual influences and food choice: a case study. Food Qual Prefer 19:539–564CrossRefGoogle Scholar
  19. 19.
    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
  20. 20.
    Kurkovsky S, Zanev V, Kurkovsky A (2005) SMMART: using context-awareness in m-commerce. MobileHCT2005, pp 383–384Google Scholar
  21. 21.
    Lee YE, Benbasat I (2003) Interface design for mobile commerce. Commun ACM 46(12):49–52CrossRefGoogle Scholar
  22. 22.
    Lee YE, Benbasat I (2004) A framework for the study of customer interface design for mobile commerce. Int J Electron Commun 8(3):79–102Google Scholar
  23. 23.
    Liang TP, Huang ZW, Yeh YH, Lin B (2007) Adoption of mobile technology in business: a fit-viability model. Ind Manag Data Syst 107(8):1154–1169CrossRefGoogle Scholar
  24. 24.
    Lin YL, Liang TP, Ho SC, Yeh YH (2007) The impact of situation influences on the intention to use mobile value-added services. Paper presented at the 6th workshop on e-business (WeB2007), Montreal, Quebec, 9 December 2007Google Scholar
  25. 25.
    Lin YM, Shih DH (2008) Deconstructing mobile commerce service with continuance intention. Int J Mobile Commun 6(1):67–87CrossRefGoogle Scholar
  26. 26.
    Lopez-Nicolas C, Molina-Castillo FJ, Bouwman H (2008) An assessment of advanced mobile services acceptance: contributions from TAM and diffusion theory models. Inf Manag-Amst 45:359–364CrossRefGoogle Scholar
  27. 27.
    Luley PM, Paletta L, Almer A (2005) Visual object detection from mobile phone imagery for context awareness. MobileHCT2005, pp 385–386Google Scholar
  28. 28.
    Maamar Z (2003) Virtual extension: commerce, e-commerce, and m-commerce: what comes next? Commun ACM 46(12):251–257CrossRefGoogle Scholar
  29. 29.
    Mallat N (2007) Exploring consumer adoption of mobile payments—a qualitative study. J Strateg Inf Syst 16:413–432Google Scholar
  30. 30.
    Mallat N, Rossi M, Tuunainen VK, Oorni A (2008) An empirical investigation of mobile ticketing service adoption in public transportation. Pers Ubiquitous Comput 12:57–65CrossRefGoogle Scholar
  31. 31.
    Mallat N, Rossi M, Tuunainen VK, Oorni A (2009) The impact of use context on mobile service acceptance: the case of mobile ticketing. Inf Manag 46:190–195CrossRefGoogle Scholar
  32. 32.
    Matskin M, Tveit A (2001) Mobile commerce agents in WAP-based services. J Database Manag 12(3):27–35Google Scholar
  33. 33.
    Moon JW, Kim YG (2001) Extending the TAM for a world-wide-web context. Inf Manag-Amst 38:217–230CrossRefGoogle Scholar
  34. 34.
    Morales-Aranda AH, Mayora-Ibarra O, Negrete-Yankelevich S (2004) M-modeler: a framework implementation for modeling m-commerce applications. Paper presented at the 6th international conference on electronic commerce, pp 596–602Google Scholar
  35. 35.
    Ngai EWT, Cheng TCE, Au S, Lai KH (2007) Mobile commerce integrated with RFID technology in a container depot. Decis Support Syst 43:62–76CrossRefGoogle Scholar
  36. 36.
    Nordqvist S, Hovmark S, Zika-Viktorsson A (2004) Perceived time pressure and social processes in project teams. Int J Proj Manag 22:463–468CrossRefGoogle Scholar
  37. 37.
    Okazaki S (2005) Mobile advertising adoption by multinationals senior executives’ initial responses. Internet Res 15(2):160–180CrossRefMathSciNetGoogle Scholar
  38. 38.
    Park CW, Iyer ES, Smith DC (1989) The effects of situational factors on in-store grocery shopping behavior: the role of store environment and time available for shopping. J Consum Res 15(4):422–433CrossRefGoogle Scholar
  39. 39.
    Peffers K, Tuunanen T (2005) Planning for IS applications: a practical, information theoretical method and case study in mobile financial services. Inf Manag-Amst 42:483–501CrossRefGoogle Scholar
  40. 40.
    Schmitt BH, Shultz CJ (1995) Situational effects on brand preferences for image products. Psychol Mark 12(5):433–446CrossRefGoogle Scholar
  41. 41.
    Schwabe G, Göth C (2005) Mobile learning with a mobile game: design and motivational effects. J Comput Assist Learn 21:204–216CrossRefGoogle Scholar
  42. 42.
    Shin DH (2009) Towards an understanding of the consumer acceptance of mobile wallet. Comput Hum Behav 25:1343–1354CrossRefGoogle Scholar
  43. 43.
    Slack F, Rowley J (2002) Online kiosks: the alternative to mobile technologies for mobile users. Internet Res 12(3):248–257CrossRefGoogle Scholar
  44. 44.
    Tamminen S, Oulasvirta A, Toiskallio K, Kankainen S (2004) Understanding mobile contexts. Pers Ubiquitous Comput 8:135–143CrossRefGoogle Scholar
  45. 45.
    Tewari G, Youll J, Maes P (2002) Personalized location-based brokering using an agent-based intermediary architecture. Decis Support Syst 34:127–137CrossRefGoogle Scholar
  46. 46.
    Topi H, Valacich JS, Hoffer JA (2005) The effects of task complexity and time availability limitations on human performance in database query tasks. Int J Hum-Comput Stud 62:349–379CrossRefGoogle Scholar
  47. 47.
    Tsang M, Ho SH, Liang TP (2004) Consumer attitudes toward mobile advertising: an empirical study. Int J Electron Commun 8(3):65–78Google Scholar
  48. 48.
    Van der Heijden H (2004) User acceptance of hedonic information systems. MIS Q 28(4):695–704Google Scholar
  49. 49.
    Varchney U, Vetter R (2002) Mobile commerce: framework, applications and networking support. Mobile Netw Appl 7:185–198CrossRefGoogle Scholar
  50. 50.
    Verkasalo H (2009) Contextual patterns in mobile service usage. Pers Ubiquitous Comput 13:331–342CrossRefGoogle Scholar
  51. 51.
    Wang YS, Liao YW (2007) The conceptualization and measurement of m-commerce user satisfaction. Comput Hum Behav 23:381–398CrossRefMathSciNetGoogle Scholar
  52. 52.
    Wong YK, Hsu CJ (2008) The confidence-based framework for business to consumer (B2C) mobile commerce adoption. Pers Ubiquitous Comput 12:77–84CrossRefGoogle Scholar
  53. 53.
    Yi MY, Jackson JD, Park JS, Probst JC (2006) Understanding information technology acceptance by individual professionals-toward an integrative view. Inf Manag-Amst 43:350–363CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2010

Authors and Affiliations

  1. 1.Department of Information ManagementNational Sun Yat-sen UniversityKaohsiungTaiwan

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