Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
권호 표지
DOI QR코드

DOI QR Code

Application of Theory of Reasoned Action in u-Tour System

유투어 시스템에서의 합리적 행동이론 적용

  • Kim, Mincheol (Dept. of Management Information Systems, Jeju National University)
  • Received : 2014.10.25
  • Accepted : 2014.12.20
  • Published : 2014.12.28
Download PDF
⟨ Previous Next ⟩

Abstract

The objective of this study is to propose the implications using theory of reasoned action(TRA) on u-Tour system. This research model through TRA is consisted as three constructs: user-friendliness(cognitive), perceived usefulness(cognitive) and purchase intention(affective). This study analyzes with a total of 153 respondents and used PLS-SEM method considering the small number of samples. Also, with the analysis, WarpPLS software is used in order to ferret out non-linear relationship between the constructs of research model. As a result of analysis, this research model shows statistical level significantly on proposed hypotheses and the applicability of TRA model in u-Tour system. Furthermore, additional analysis presents the possibility of non-linear relationship on each path between the constructs of research model showing J-shape. Also, the result showes the fact that the relationship had partly negative (-) effect on dependent factor. Additional analysis proposes that income variable as base of purchase intention has a moderating effect on all paths of research model.

본 연구의 목적은 유-투어 시스템의 합리적 행동이론(TRA)을 사용하여 관련 시사점을 제시하는 것이다. 여기서 크게 사용자 친숙성(인지적 요인), 인지된 유용성(정서적 요인)과 구매 의도(능동적 요인) 등 세 가지 구조로 연구 모형이 구성되었다. 본 연구는 총 153명의 응답자 표본을 갖고 분석하였는데, 적은 표본 수를 고려하여 PLS-SEM 방법을 적용하였다. 또한, 연구 모형 내 각 경로에서 비선형 관계를 탐색하기 위하여 WarpPLS 소프트웨어를 활용하였다. 분석 결과, 제안된 연구 모델은 통계적으로 유의하였고, 유투어 시스템이 제안된 TRA 이론의 적용 가능성을 보여 주었다. 또한, 추가 분석으로서, 연구 모형 내 각 경로에서 비선형 관계로서 J 형태의 가능성을 보여주면서, 종속요인에 부분적으로 부(-)의 영향이 있다는 사실을 보여 주었다. 그리고 구매의도의 기반이 되는 소득변수는 제안된 모형 내 각 경로에 조절적 효과를 줄 수 있음을 실증적으로 제시하였다.

Keywords

References

  1. D. Fodness.B. Murray, A Typology of Tourist information Search Strategies. Journal of Travel Research, Vol. 37, No. 2, pp. 108-119, 1998. https://doi.org/10.1177/004728759803700202
  2. T. E. Boyce.P. N. Hineline, Interteacing: A strategy for enhancing the user-friendliness of behavioural arrangement in the college classroom. The Behavioral Analyst, Vol. 25, No. 2, pp. 215-226, 2002. https://doi.org/10.1007/BF03392059
  3. D. Wang.S. Park.D. R. Fesenmaier, The role of Smartphones in mediating the touristic experience. Journal of Travel Research, Vol. 51, No. 4, pp. 371-387, 2011.
  4. R. Kramer.M. Modsching.K. Hagen.U. Gretzel, Behavioural impacts of mobile tour guides. Information and Communication Technologies in Tourism, pp. 109-118, 2007.
  5. M. Weiser, The Computer for the 21st Century. Scientific American, pp. 94-104, 1991.
  6. R. Watson.S. Akselsen.E. Monod.L. Pitt, The open tourism consortium: Laying the foundations for the future of tourism. European Management Journal, Vol. 22, No. 3, pp. 315-326, 2004. https://doi.org/10.1016/j.emj.2004.04.014
  7. Jeju u-Tour. Available from: http://www.u-tour.or.kr/Sub/?pid=0701
  8. M. Fishbein.I. Ajzen, Belief, attitude, intention, and behavior. Reading, MA: Addison-Wesley, 1975.
  9. L. G. Schiffman.L. L. Kanuk, Consumer behavior (3rd Eds.). Englewood Cliffs, NJ: Prentice-Hall, 1987.
  10. S. Rivard.S. L. Huff, Factors of success for end-user computing. Communication of the ACM, Vol. 31, No. 5, pp. 552-561, 1988. https://doi.org/10.1145/42411.42418
  11. H. G. Van der Roest.F. J. M. Meiland.C. Jonker.Rose-Marie Droes, User evaluation of the DEMentia-specific Digital Interactive Social Chart (DEM-DISC) - A pilot study among informal carers on its impact, user friendliness and, usefulness. Aging & Mental Health, Vol. 14, No. 4, pp. 461-470, 2010. https://doi.org/10.1080/13607860903311741
  12. V. Venkatesh.F. D. Davis, A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, Vol. 46, No. 2, pp. 186-204, 2000. https://doi.org/10.1287/mnsc.46.2.186.11926
  13. V. Venkatesh.M. G. Morris.G. B. Davis.F. D. Davis, User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, Vol. 27, pp. 425-478, 2003. https://doi.org/10.2307/30036540
  14. D. A. Baker.J. L. Crompton, Quality, satisfaction and behavioral intentions. Annals of Tourism Research, Vol. 27, No. 3, pp. 785-804, 2000. https://doi.org/10.1016/S0160-7383(99)00108-5
  15. R. F. Falk.N. B. Miller, A Primer for Soft Modeling. University of Akron Press, Akron, OH, 1992.
  16. N. Kock, WarpPLS${(R)}$ 4.0 user manual. ScriptWarp Systems$^{TM}$. Laredo, TX, USA, 2013.
  17. C. M. Ringle.M. Sarstedt.D. W. Straub, A Critical Look at the Use of PLS-SEM in MIS Quarterly. MIS Quarterly, Vol. 36, No. 1, pp. iii-xiv, 2012.
  18. J. J. Sosik.S. S. Kahai.M. J. Piovoso, Silver Bullet or Voodoo Statistics? A Primer for Using the Partial Least Squares Data Analytic Technique in Group and Organization Research. Group Organization Management, Vol. 34, No. 1, pp. 15-36, 2009.
  19. D. W. Barclay.C. A. Higgins.R. Thompson, The Partial Least Squares Approach to Causal Modeling: Personal Computer Adoption and Use as Illustration. Technology Studies, Vol. 2, No. 2, pp. 285-309, 1995.
  20. C. Fornell.D. F. Larcker, Evaluating Structural Equation Models with Unobservable Variables and measurement Error. Journal of Marketing Research, Vol. 18, No. 1, pp. 39-50, 1981, https://doi.org/10.2307/3151312
  21. J. F. Hair.R. E. Anderson.R. L. Taltam.W. C. Black, Multivariatedataanalysis. Upper Saddle River. NY: Prentice-Hall, 1998.
  22. R. P. Bagozzi.Y. Yi, Specification, Evaluation, and Interpretation of Structural Equation Models. Journal of the Academy of Marketing Science, Vol. 40, pp. 8-34, 2012. https://doi.org/10.1007/s11747-011-0278-x
  23. R. Bagozzi.P. Y. Yi.L. W. Phillips, Assessing Construct Validity in Organizational Research. Administrative Science Quarterly. Vol. 36, No. 3, pp. 421-458, 1991. https://doi.org/10.2307/2393203
  24. C. Cassel.P. Hackl.P.A. H. Westlund, Robustness of Partial Least-Squares Method for Estimating Latent Variable Quality Structures. Journal of Applied Statistics, Vol. 26, No. 4, pp. 435-446, 1999. https://doi.org/10.1080/02664769922322
  25. N. Malhotra.S. Kim.A. Patil, Common Method Variance in IS Research: A Comparison of Alternative Approaches and a Reanalysis of Past Research. Management Science, Vol. 52, No. 2, pp. 1865-1883, 2006. https://doi.org/10.1287/mnsc.1060.0597
  26. P. Pavlou.H. Liang.Y. Xue, Understanding and Mitigating Uncertainty in Online Exchange Relationships: A Principal-Agent Perspective. MIS Quarterly, Vol. 31, No. 1, pp. 105-136, 2007. https://doi.org/10.2307/25148783
  27. Y. Reisinger.L. Turner, Structural Equation Modeling with LISREL: Application in Tourism. Tourism Management, Vol. 20, pp. 71-88, 1999. https://doi.org/10.1016/S0261-5177(98)00104-6
  28. W. W. Chin, Issues and Opinion on Structural Equation Modeling. MIS Quarterly, Vol. 22, No. 1, pp. vii-xvi, 1998.
  29. D. Gefen.D. Straub, A Practical Guide to Factorial Validity Using PLS-Graph: Tutorial and Annotated Example. Communications of the Association for Information Systems, Vol. 16, pp. 91-109, 2005.
  30. J. Hair.F. M. Sarstedt.C. M. Ringle.J. A. Mena, An Assessment of the Use of Partial Least Squares Structural Equation Modeling in Marketing Research. Journal of Academy of Marketing Science, Vol. 40, pp. 414-433, 2012. https://doi.org/10.1007/s11747-011-0261-6
  31. M. Wetzels.G. Odekerken-Schroder.C. van Oppen, Using PLS Path Modeling for Assessing Hierarchical Construct Models: Guidelines and Empirical Illustration. MIS Quarterly, Vol. 33, pp. 177-195, 2009. https://doi.org/10.2307/20650284