THE EFFICIENCY OF TOURISM ORGANIZATION MANAGEMENT USING DIGITAL TECHNOLOGY

Authors

  • sarochinee Siriwattana

Keywords:

Organization management efficiency, tourism, foreign travelers, digital technology

Abstract

This study aimed to investigate the interaction between biosocial characteristics, the provision of services via websites and social networks, as well as the response of individual demands, affecting the effectiveness of tourism organization management of foreign tourists. The study was designed as a mixed-methods study that focused particularly on quantitative research. A sample survey of 500 international visitors to Thailand who completed the questionnaire served as the basis for the study. The statistics were also incorporated into the relationship path analysis to ascertain the influence of the relationship. Using interviews with the sample group, a qualitative research method was also used to fill in gaps in the study and support the quantitative research.

The relationship influence study suggests that social media has the greatest influence on the efficiency of tourism organization management among travelers. In addition, the social media component, in association with meeting individual needs, affects the relationship in terms of the efficiency of tourism organization management of travelers. Consistent with qualitative study, the aforementioned findings indicate that social media has a significant impact on tourist tourism as a function of the website's potential to satisfy different needs. Therefore, these characteristics are relevant and essential to the efficiency of tourism organization management using digital technology. In addition, in this research, it is found that research on tourism organization management of foreign tourists is necessary to study the path of causal factors in order to know the direct effect, indirect effect, and total effects of every variable since every variable has a causal interrelated influence.

References

Byrne, B.M. (2009), Structural Equation Modeling with AMOS: Basic Concepts, Applications, and Programming;. London: Routledge.

Carol, X. O. & Choon, L. S. (2003). Customer loyalty strategy in the internet era. Pacific Asia Conference on Information Systems (1734-1744), 10-13 July 2003, Adelaide, South Australia.

Chavalier, A. & Ivory, M. Y. (2003). Web designs: Influences of designer’s expertise and constraints. International Journal of Human-Computer Studies, 58, 57-87.

Cheng, M. K. & Lee, M. K. O. (2006). Understanding consumer trust in internet shopping: A multidisciplinary approach. Journal of the American Society for Information -Science and Technology, 57(4), 479-492.

Cronbach, L.J. (1990). Coefficient Alpha and The Internal Structure of Tests. Psychometrika.

Ersoy, N., & Calik, N. (2010). Brand loyalty: Emotional devotion or rational behavior-A study on mobile telephones from Eskisehir, Turkey. The Business Review, Cambridge, 15(1), 212.

Jetsalid Angsukanjanakul. (2017). Modeling Sustainable Management for Community based Tourism: A Case Study of Floating Markets in the Lower Central Thailand. International Journal of Management and Applied Science, 3(1), 43-46.

Kish, L. (1965). Survey Sampling. New York: John Wiley and Sons Inc.

Kuo, H. M., Hwang, S. L., & Wang, M. Y. (2004). Evaluation research of information and supporting interface in electronic commerce web sites. Information and Management, 41(3), 377-397.

National Statistic Office Ministry of Information and Communication Technology. Available online: http://web.nso.go.th/index.htm (accessed on 5 December 2021).

Office of the National Economic and Social Development Council (NESDC). Available online: http://www.nesdb.go.th/nesdb_en/more_news.php?cid=154&filename=index (accessed on 5 December 2021).

Srinivasan S., Rolph, A. & Kishore, P. (2002). Customer loyalty in e-commerce: An exploration of its antecedents and consequences. Journal of Retailing, 78, 41-50.

Sugiyama, K. & Andree, T. (2010). The Dentsu way: Secrets of cross switch marketing from the world’s most innovative advertising agency. New York: McGraw-Hill.

Sutthichaimethee, P., Ariyasajjakorn, D. A (2020), Forecasting Model on Carrying Capacity for Government’s Controlling Measure under Environmental Law in Thailand: Adapting Non-recursive Autoregression Based on the Var-X Model. International Journal of Energy Economics and Policy, 10, 645-655.

Sutthichaimethee, P., Chatchorfa, A., Suyaprom, S. (2019), A Forecasting Model for Economic Growth and CO2 Emission Based on Industry 4.0 Political Policy under the Government Power: Adapting a Second-Order Autoregressive-SEM. J. Open Innov. Technol. Mark. Complex., 5, 69.

Sutthichaimethee, P., Dockthaisong, B. (2018), A Relationship of Causal Factors in the Economic, Social, and Environmental Aspects Affecting the Implementation of Sustainability Policy in Thailand: Enriching the Path Analysis Based on a GMM Model. Resources, 7, 87.

World Tourism Organization. (2011). Travel and Tourism 2011, World travel and tourism council, London, UK.

Xu, S., Mingzhu, L., Bu, N., & Pan, S. (2017). Regulatory frameworks for ecotourism: An application of Total Relationship Flow Management Theorems. Tourism Management., 61, 321-330.

Downloads

Published

2023-01-11

How to Cite

Siriwattana, S. (2023). THE EFFICIENCY OF TOURISM ORGANIZATION MANAGEMENT USING DIGITAL TECHNOLOGY. Journal of MCU Social Development, 7(3), 404–424. retrieved from https://so06.tci-thaijo.org/index.php/JMSD/article/view/258107