A Study of Technical Strategy for Tourism Social Network Services from the Viewpoint of Acceptance Decision Factor

Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 235)


In this paper, we intended to analyze the relationship among tourist’s acceptance decision, perceived value, satisfaction and continuous use for social network service. For this study, the self-administered questionnaire for 199 tourists was employed. As the result, the positive relationships among the above-mentioned factors are found. The technical strategy from this result could be suggested that the positive feedback of customer acceptance decision factors further encourages customers continuous uses of tourism SNS. Therefore tourism SNS providers should consider social aspects in its user retention.


Tourism social network service Acceptance decision factor Self efficacy Social presence Self assertion Social-cultural influence Perceived value Satisfaction Continuous use intention 



This work was supported by National Research Foundation—Grant funded by the Korean Government (National Research Foundation of Korea-2011-32A-B00278).


  1. 1.
    O’Dell J (2011) Is Facebook getting bigger than Google? Accessed Jan 2011
  2. 2.
    Ahmed I, Qazi TF (2011) A look out for academic impacts of Social networking sites (SNSs): a student based perspective. Afr J Bus Manag 5(12):5022–5031Google Scholar
  3. 3.
    Boyd DM, Ellison NB (2007) Social network sites: definition, history, and scholarship. J Comput Mediat Commun 13(1):210–230 (article 11)Google Scholar
  4. 4.
    Donath J, Boyd D (2004) Public displays of connection. BT Technol J 22(4):71–82CrossRefGoogle Scholar
  5. 5.
    Casalo LV, Flavian C, Guinaliu M (2010) Relationship quality, community promotion and brand loyalty in virtual communities: evidence from free software communities. Int J Inf Manag 30(4):357–367CrossRefGoogle Scholar
  6. 6.
  7. 7.
    Wood R, Bandura A (1989) Social cognitive theory of organizational management. Acad Manag Rev 14:361–384Google Scholar
  8. 8.
    Swimmer GI, Ramanaiah NV (1985) Convergent and discriminant validity of selected assertiveness measures. J Pers Soc Psychol 49(1):243–249CrossRefGoogle Scholar
  9. 9.
    Rogers EM (1995) Diffusions of innovations, 4th edn. The Free Press, New York, p 32Google Scholar
  10. 10.
    Sprecher S, Hendrick SS (2004) Self-disclosure in intimate relationships: associations with individual and relationship characteristics over time. J Soc Clin Psychol 23:857–877CrossRefGoogle Scholar
  11. 11.
    Short J, Williams E, Christie B (1976) The social psychology of telecommunications. Wiley, LondonGoogle Scholar
  12. 12.
    Gunawardena CN, Zittle FJ (1997) Social presence as a predictor of satisfaction with a computer-mediated conferencing environment. Am J Distance Educ 11:8–26CrossRefGoogle Scholar
  13. 13.
    Tu CH, McIsaac M (2002) The relationship of social presence and interaction in online classes. Am J Distance Educ 16(3):131–150CrossRefGoogle Scholar
  14. 14.
    Lahaie U (2007) Strategies for creating social presence online. Nurse Educ 32(3):100–101CrossRefGoogle Scholar
  15. 15.
    Venkatesh V, Morris MG, Davis GB, Davis FD (2003) User acceptance of information technology: toward a unified view. MIS Q 27(3):425–478Google Scholar
  16. 16.
    Rogers EM (1995) Diffusion of Innovatoins. Free Press, New YorkGoogle Scholar
  17. 17.
    Bandura A (1977) Social learning theory. Prentice-Hall, Englewood CliffsGoogle Scholar
  18. 18.
    Thompson R, Higgins C, Howell J (1994) Influence of experience on personal computer utilization: testing a conceptual model. J Manag Inf Syst 11(1):167–187Google Scholar
  19. 19.
    Venkatesh V, Davis FD (2000) A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag Sci 46(2):186–204CrossRefGoogle Scholar
  20. 20.
    Farina CR, Miller P, Newhart MJ, Vernon R (2010) Rulemaking in 140 characters or less: social networking and public participation in rulemaking. Accessed Dec 29
  21. 21.
    Wong A, Sohal A (2003) Assessing customer-salesperson interactions in a retail chain: differences between city and country retail district. Mark Intell Plan 21(5):292–304CrossRefGoogle Scholar
  22. 22.
    Chang HH, Wang Y, Yang W (2009) The impact of e-service quality, customer satisfaction and loyalty on e-marketing: moderating effect of perceived value. Total Qual Manag Bus Excellence 20(4):423–443CrossRefGoogle Scholar
  23. 23.
    Chang HH, Wang H (2010) The moderating effect of customer perceived value on online shopping behavior. Online Inf Rev 35(3):333–359CrossRefGoogle Scholar
  24. 24.
    Oliver RL (1980) A cognitive model of the antecedents and consequences of satisfaction decisions. J Mark Res 7(4):460–469CrossRefGoogle Scholar
  25. 25.
    Bhattacherjee A (2001) Understanding information systems continuance: an expectation-confirmation model. MIS Q 25(3):351–370CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Department of Tourism ManagementTongMyong UniversityBusanKorea
  2. 2.Department of Hotel TourismTongMyong UniversityBusanKorea
  3. 3.Department of Media EngineeringTongMyong UniversityBusanKorea

Personalised recommendations