Multimedia Tools and Applications

, Volume 68, Issue 2, pp 321–336 | Cite as

A comparative study of the motivational orientation type on users’ behavior: focusing on ubiquitous computing services



One of the main problems of today’s ubiquitous computing systems is that they do not meet their quality requirements. Ubiquitous computing services such as mobile data services (MDS) are fundamentally different from traditional information systems (IS) in terms of important quality factors such as information or system quality because it has been used in various life contexts. We identify important quality factors on various contexts in Korea MDS market. Using the results of qualitative study, we propose research model. To identify the effect of motivational orientation type on users’ behavior, we classified users according to their propensities into intrinsic and extrinsic motivational orientation groups. The results show that the impact of quality factors on user satisfaction is differentiated depending on motivational orientation types. The paper concludes with a discussion of the study’s limitations and implications.


Information quality System quality Motivational orientation Mobile data service Contribution to quality of life 



The authors appreciate comments from editors and reviewers of Multimedia Tools and Applications. This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (#2011-0012490).


  1. 1.
    Federal Trade Commission (2002) The mobile wireless web, data services and beyond: Emerging technologies and consumer issues. Available at:
  2. 2.
    Amabile TM (1988) A model of creativity and innovation in organizations. In: Staw BM, Cummings LL (eds) Research in organizaitonal behavior, vol 10. JAI Press, Greenwich, CT, pp 123–167Google Scholar
  3. 3.
    Amabile TM, Hill KG, Hennessey BA, Tighe EM (1994) The work preference inventory: assessing intrinsic and extrinsic motivational orientations. J Pers Soc Psychol 66(5):950–967CrossRefGoogle Scholar
  4. 4.
    Ambrose PJ, Rai A, Ramaprasad A (2006) Internet usage for information provisioning: theoretical construct development and empirical validiation in the clinical decision-making context. IEEE Trans Eng Manag 53(1):112–129CrossRefGoogle Scholar
  5. 5.
    Andrews FM, Withey SB (1976) Social indicators of well-being: America’s perception life. Plenum Press, New YorkCrossRefGoogle Scholar
  6. 6.
    Bhattacherjee A, Premkumar G (2004) Understanding changes in belief and attitude toward information technology usage: a theoretical model and longitudinal test. MIS Q 28(2):229–254Google Scholar
  7. 7.
    Bollen KA, Lennox R (1991) Conventional wisdom on measurement: a structural equation perspective. Psychol Bull 110:305–314CrossRefGoogle Scholar
  8. 8.
    Bruseberg A, McDonagh-Philp D (2001) New product development by eliciting user experience and aspirations. Int J Hum Comput Stud 55(4):435–452CrossRefMATHGoogle Scholar
  9. 9.
    Buchanan G, Farrant S, Marsden G, Pazzani M (2001) Improving mobile internet usability. In: Proceedings International WWW Conference, Hong-KongGoogle Scholar
  10. 10.
    Campbell A, Converse PE, Rodgers WL (1976) The quality of American life. Russel Sage Foundation, New YorkGoogle Scholar
  11. 11.
    Chae MH, Kim JW, Kim HY, Ryu HS (2002) Information quality for mobile data services: a theoretical model with empirical validation. Electron Mark 12(1):38–46CrossRefGoogle Scholar
  12. 12.
    Chin W (1998) The partial least squares approach to structural equation modeling. In: Marcoulides GA (ed) Modern methods for business research. Laurence Erlbaum Associates, Mahwah, New Jersey, pp 295–336Google Scholar
  13. 13.
    Choi M, Lee I, Choi H, Kim J (2003) A cross-cultural study on the post-adoption behavior of mobile internet users. In: Proceedings of DIGIT, SeattleGoogle Scholar
  14. 14.
    Davis FD, Bagozzi RP, Warshaw PR (1992) Extrinsic and intrinsic motivation to use computers in the workplace. J Appl Soc Psychol 22(14):1111–1132CrossRefGoogle Scholar
  15. 15.
    Delone WH, McLean ER (1992) Information systems success: the quest for the dependent variable. Inf Syst Res 3(1):60–96CrossRefGoogle Scholar
  16. 16.
    Diamantopoulos A, Winklhofer HM (2001) Index construction with formative indicators: an alternative to scale development. J Mark Res 37:269–277CrossRefGoogle Scholar
  17. 17.
    Diener E (1984) Subjective well-being. Psychol Bull 95:542–575CrossRefGoogle Scholar
  18. 18.
    Folmer E, Gurp J, Bosch J (2003) Scenario-based Assessment of Software Architecture Usability. In Proceedings of the Workshop on Bridging the Gaps Between Software Engineering and Human-Computer Interaction (SE-HCI). IFIP, 61–68Google Scholar
  19. 19.
    Forenll C, Larcker D (1981) Evaluating structural equation models with unobservable variables and measurement error. J Mark Res 18:39–50CrossRefGoogle Scholar
  20. 20.
    Gefen D, Karahanna E, Straub D (2003) Trust and TAM in online shopping: an integrated model. MIS Q 27(1):51–90Google Scholar
  21. 21.
    Hulland J (1999) Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strateg Manag J 20:195–204CrossRefGoogle Scholar
  22. 22.
    Ives B, Olson MH, Baroudi JL (1983) The measurement of user information satisfaction. Commun ACM 26(10):785–793CrossRefGoogle Scholar
  23. 23.
    Keil M, Tan BC, Wei K-K, Saarinen T (2000) A cross-cultural study on escalation of commitment behavior in software projects. MIS Q 24(2):299–325CrossRefGoogle Scholar
  24. 24.
    Kim H, Kim J (2003) Post-adoption behavior of mobile internet users: a model-based comparison between continuers and discontinuers. In: Proceedings of the HCI/MIS'03 Workshop, SeattleGoogle Scholar
  25. 25.
    Konkka K, Oyj N, Koskinen S (2005) Mobile user experience: challenges in international end-user needs research and design. In: Proceedings of HCI international, Las VegasGoogle Scholar
  26. 26.
    Lee MKO, Cheung CMK, Chen Z (2005) Acceptance of internet-based learning medium: the role of extrinsic and intrinsic motivation. Inf Manage 42:1095–1104CrossRefGoogle Scholar
  27. 27.
    Lee DJ, Sirgy MJ (1995) Determinants of Involvement in the Consumer/Marketing Life Domain in Relation to Quality of Life: A Theoretical Model and Research Agenda. Developments in quality-of-life studies in marketing, vol. 5, edited by H. Lee Meadow, M. Joseph Sirgy, and Don Rahtz, DeKalb, IL: Academy Science, pp 13–18Google Scholar
  28. 28.
    Maguire M, Bevan N (2005) User requirements analysis: a review of supporting methods. In: Proceedings of IFIP 17th World Computer Congress, Montreal Canada, pp 25–30Google Scholar
  29. 29.
    Mankoff J, Carter S (2005) Crossing qualitative and quantitative evaluation in the domain of ubiquitous computing. In: CHI2005 Workshop Portland, Oregon, USAGoogle Scholar
  30. 30.
    McKinney V, Yoon K, Zahedi F (2002) The measurement of Web-customer satisfaction: an expectation and disconfirmation approach. Inf Syst Res 13:296–315CrossRefGoogle Scholar
  31. 31.
    Pavot W, Diener E (1993) Review of the satisfaction with life scale. Psychol Assess 5:164–171CrossRefGoogle Scholar
  32. 32.
    Ryan RM, Deci EL (2000) Intrinsic and extrinsic motivations: classic definitions and new directions. Contemp Educ Psychol 25:54–67CrossRefGoogle Scholar
  33. 33.
    Ryan C, Gonsalves A (2005) The effect of context and application type on mobile usability: an empirical study. In: Twenty-Eighth Australasian Computer Science Conference (ACSC2005), Newcastle, Australia, pp 115–124Google Scholar
  34. 34.
    Seddon PB (1997) A respecification and extention of the DeLone and McLean model of IS success. Inf Syst Res 8(3):240–253CrossRefGoogle Scholar
  35. 35.
    Shang R-A, Chen Y-C, Shen L (2005) Extrinsic versus intrinsic motivations for consumers to shop on-line. Inf Manage 42:401–413CrossRefGoogle Scholar
  36. 36.
    Sirgy MJ (2002) Psychology of quality of life. Kluwer Academic Publishers, NetherlandsCrossRefGoogle Scholar
  37. 37.
    Sirgy MJ, Cornwell T (2001) Further validation of the Sirgy et al’.s measure of community quality of life. Soc Indic Res 56:125–143CrossRefGoogle Scholar
  38. 38.
    Sirgy MJ, Hansen DE, Littlefield JE (1994) Does hospital satisfaction affect life satisfaction? J Macromark 14:36–46CrossRefGoogle Scholar
  39. 39.
    Spreng R, MacKenzie SB, Olshavsky RW (1996) A reexamination of the determinants of consumer satisfaction. J Mark 60(3):15–32CrossRefGoogle Scholar
  40. 40.
    Straub DW, Watson RT (2001) Research commentary: transformational issues in researching IS and Net-enabled organizations. Inf Syst Res 12(4):337–345CrossRefGoogle Scholar
  41. 41.
    Sun X, Collins R (2002) Attitudes and consumption values of consumers of imported fruit in Guangzhou, China. Int J Consum Stud 26(1):34–43CrossRefGoogle Scholar
  42. 42.
    Venkatesh V, Brown SA (2001) A longitudinal investigation of personal computers in homes: adoption determinants and emerging challenges. MIS Q 25:71–102CrossRefGoogle Scholar
  43. 43.
    Weiser M (1993) The computer for the twenty-first century. Sci Am 265(3):94–104CrossRefGoogle Scholar
  44. 44.
    White JC, Varadarajan PR, Dacin PA (2003) Market situation interpretation and response: the role of cognitive style, organizational culture, and information use. J Mark 67(3):63–79CrossRefGoogle Scholar
  45. 45.
    Wixom BH, Todd PA (2005) A theoretical integration of user satisfaction and technology. Acceptance. Inf Syst Res 16(1):85–102CrossRefGoogle Scholar
  46. 46.
    Wixom BH, Watson HJ (2001) An empirical investigation of the factors affecting data warehousing success. MIS Q 25(1):17–41CrossRefGoogle Scholar
  47. 47.
    Yi MY, Hwang Y (2003) Predicting the use of web-based information systems: self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model. Int J Hum Comput Stud 59(4):431–449CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Department of Management Information SystemsCatholic University of PusanPusanKorea
  2. 2.School of BusinessYonsei UniversitySeoulKorea

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