Development of Local Cultural Tourism Communication Model to Promote Tourism in Nakhon Si Thammarat Province Using Conjoint Analysis Technique

Main Article Content

Pelapon Suwanacheep
Lunjakon Nillakan
Panya Lertgrai

Abstract

This study aimed to analyze the characteristics of local cultural tourism communication through virtual tours that satisfy tourists. The researcher collected all relevant characteristics of virtual tours through a literature review process and selected the five most important virtual tour characteristics using the Analytic Hierarchy Process (AHP). These characteristics were then used to design a questionnaire using conjoint analysis techniques. The sample group consisted of 200 tourists aged 18-70 years who visited Mueang District, Nakhon Si Thammarat Province. Data were collected through questionnaires and analyzed using conjoint analysis techniques, while satisfaction values were calculated using linear regression analysis. The findings revealed that the most important characteristic for general tourists was the local cultural tourism communication through virtual tours that incorporated both real and graphic panoramic images, presented through either tourism routes or game-based learning, with a 5-minute viewing duration, featuring 3D models, and accompanying videos.

Article Details

Section
บทความวิจัย (Research Articles)

References

การท่องเที่ยวแห่งประเทศไทย. (2564). 9 แนวโน้มใหม่ ในอนาคตการท่องเที่ยว. สืบค้นเมื่อ 20 ธันวาคม 2567, จาก https://thai.tourismthailand.org/Articles/9tat

Alamanda, D. T., Ramdhani, A. & Ramadhan, M. B. (2021). Virtual tourism of mount Garut tourism using conjoint analysis. Age, 16(20), pp. 1-6.

Bajaj, A. (1999). Conjoint analysis: A potential methodology for IS research analysis. Retrieved June 3, 2024, from https://shorturl.asia/fzCI4

Geng, W. (2022). Whether and how free virtual tours can bring back visitors. Retrieved June 15, 2024, from https://doi.org/10.1080/13683500.2022.2043253

Green, P. E., Krieger, A. M. & Wind, Y. (2001). Thirty years of conjoint analysis: reflections and prospects. Interface, 31(3), pp. 56-73.

Hair, J., Black, W., Babin, B., Anderson, R. & Tatham, R. (2006). Multivariate data analysis (6th ed.). Upper Saddle River, NJ: Pearson Prentice Hall.

Hauser, J. R., & Rao, V. R. (2002). Conjoint analysis, Related modeling, and application. advances in marketing research: Progress and prospects. Retrieved July 26, 2024, from https://shorturl.asia/tEDJC

Oppewal, H. & Vriens, M. (2000). Measuring perceived service quality using integrated conjoint experiment. International Journal of Bank Marketing, 18(4), pp. 154-169.

Suwanacheep, P. & Chompu-Inwai, R. (2020). Evaluation of customer preferences for ready-to-cook dried pork product attributes using conjoint analysis. Retrieved February 24, 2025, from https://www.wcse.org/WCSE_2019_ SUMMER/W061.pdf

Wittink, D. R. & P. Cattin. (1982). Commercial use of conjoint analysis: A survey. Journal of Marketing, 46(3), pp. 44-53.

Zhang, J., Wei, X., Fukuda, H., Zhang, L. & Ji, X. (2021). A choice-based conjoint analysis of social media picture posting and souvenir purchasing preference: A case study of social analytics on tourism. Information Processing & Management, 58(6), pp. 17-30.