DOI QR코드

DOI QR Code

A study on factors affecting consumers' information retrieval activities: Focusing on outbound tourism consumers in Japan and South Korea

소비자의 정보 검색 활동에 영향을 미치는 요인에 관한 연구 한국과 일본의 아웃바운드 관광 상품 소비자를 중심으로

  • Bae, Jongmin (Gradaute School, College of Commerce, Nihon University)
  • 배종민 (일본대학교 상학연구과)
  • Received : 2018.02.28
  • Accepted : 2018.04.20
  • Published : 2018.04.28

Abstract

Information is very important for modern consumers, and the factors that have a great influence on product purchasing. Accordingly, elucidating factors affecting the retrieval process of information is an important. This study identifies factors that affect tourism information retrieval activities. First, it was carried out the meta analysis of tourism information, repurchase intention, attitude toward technology, and information utilization. Through the meta analysis, hypothesis model about each factor of information retrieval and repurchase of tourism products was suggested. The hypothesis model was verified by a survey of Korean and Japanese tourists. As a result, it is confirmed the relationship between the above factors. The results of this study are expected to contribute to the development of a tourists' information usage model in the future.

Keywords

Tourism marketing;Korea;Japan;The use of information;The factors of search activity

References

  1. Jacobsen, K. S. & Munar, A. M. (2012). Tourist information search and destination choice in a digital age. Tourism Management Perspectives, 1, 39-47. https://doi.org/10.1016/j.tmp.2011.12.005
  2. Li, X., Li, X.. & Hudson, S.(2013). The application of generational theory to tourism consumer behavior: An American perspective. Tourism Management, 37, 159-164.
  3. Cho, H. Y. (2006). Studies in Online Travel Information Credibility and Relation Continuance Trust. Doctoral dissertation. The Graduate School of Kyonggi University, Kyonggi-do.
  4. Ham, Y. G. & Chae, S. B. (2012). Big-data, Change the Management. Seoul : The Samsung Economic Research Institute of Korea.
  5. Bengio, Y., Courville, A. & Vincent, P. (2013). Representation learning: A review and new perspectives. IEEE Trans Pattern Anal Mach Intell, 35(8), 1798-1828. doi: 10.1109/TPAMI.2013.50. https://doi.org/10.1109/TPAMI.2013.50
  6. Pan, B. (2003). Travel Information Search on the Internet: An Exploratory Study. Doctoral dissertation. Urbana, Illinois.
  7. Lee, J. H. (2017). A Study on How Reference Groups, Convenience and Pursuit of Information Affect Subscription-Based Webtoon Service Usage through Reliability and Curiosity. Journal of Convergence for Information Technology, 7(2), 101-109.
  8. Lee, S. H. & Lee, D. W. (2014). A Case Study in Japanese and Prospect of Cloud Computing Service in Convergence Age. Journal of the Korea Convergence Society, 6(1), 17-22. https://doi.org/10.15207/JKCS.2015.6.1.017
  9. Samdahl, D. M. & Jekubovich, N. J. (1997). A critique of leisure constraints: Comparative analyses and understandings. Journal of Leisure Research, 29(4), 430-452. https://doi.org/10.1080/00222216.1997.11949807
  10. Hinch, T. D. & Jackson, E. L. (2000). Leisure constraints research: Its value as a framework for understanding tourism seasonality. Current Issues in Tourism, 3(2), 87-106. https://doi.org/10.1080/13683500008667868
  11. Pennington-Gray, L. A. & Kerstetter, D. L. (2002). Testing a constraints model within the context of nature-based tourism. Journal of Travel Research, 40(4), 416-423. https://doi.org/10.1177/0047287502040004008
  12. Nyaupane, G. P., Morais, D. B. & Graefe, A. R. (2004). Nature tourism constraints: A cross-activity comparison. Annals of Tourism Research, 31(3), 540-555. https://doi.org/10.1016/j.annals.2004.01.006
  13. Andronikidis, A., Vassiliadis, C. A., Priporas, C. V. & Kamenidou, I. C. (2007). Examining leisure constraints for ski centre visitors: implications for services marketing. Journal of Hospitality & Leisure Marketing, 15(4), 69-86. https://doi.org/10.1300/J150v15n04_05
  14. Joung, J. W. & Lee, S. H. (2017). The effect of information asymmetry between accounting information provider and users on information user decision. Journal of Convergence for Information Technology, 7(2), 125-130. https://doi.org/10.22156/CS4SMB.2017.7.2.125
  15. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
  16. Fishbein, M. & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley.
  17. Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122-147. https://doi.org/10.1037/0003-066X.37.2.122
  18. Lederer, A. L., Maupin, D. J., Sena, M. P. & Zhuang, Y. (2000). The technology acceptance model and the World Wide Web. Decision Support Systems, 29, 269-282. https://doi.org/10.1016/S0167-9236(00)00076-2
  19. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 321-323.
  20. Kang, M. S. (2017). A study on the Development of Topic Map for Analysis of Customer Satisfaction in Tourism Industry. Journal of the Korea Convergence Society, 8(10), 249-255. https://doi.org/10.15207/JKCS.2017.8.10.249