A Comparative Model of Cultural Tourism in the North and the Northeast of Thailand

Main Article Content

วงษ์ปัญญา นวนแก้ว ปรัชญา นวนแก้ว

Abstract

The purposes of the research were 1) to identify key factors of cultural tourism in the north and the northeast of Thailand, 2) to analyze and compare the attributes of cultural tourism in the north and the northeast of Thailand, and 3) to design and implement a model of cultural tourism by association rule and decision tree methods. Basic statistics were employed for analyzing the model of cultural tourism through machine learning. The research methodology was divided into three parts: data collection, data analysis and data visualization. The data was collected from 1,317 tourists who visited two cultural tourist attractions in the north and two cultural tourist attractions in the northeast of Thailand: Rongkhun Temple in Chiangrai province, Sri Khomkham temple in Phayao province, Nong Waeng Temple in Khon Kaen province and Prathat Nadun Temple in Maha Sarakham province. Model measurements consisting of accuracy, precision and recall were used for the study.


The result found that satisfaction and opinion of the factor showed factors with the highest level, include resources for tourist attractions and culture and identity of attractions both factors had an average satisfaction of 4.12 or high level. Additionally, fourteen key factors for recall of the cultural tourism consisted of seven factors of tourist attractions, four factors of government policies, and three factors of tourists. The prediction models of cultural tourism in the north and the northeast of Thailand reveal that the application of the models can be developed to promote tourism in the future.

Article Details

How to Cite
นวนแก้วว., & นวนแก้วป. (2018). A Comparative Model of Cultural Tourism in the North and the Northeast of Thailand. Journal of Information Technology Management and Innovation, 4(2), 26-38. Retrieved from https://www.tci-thaijo.org/index.php/itm-journal/article/view/115312
Section
บทความวิจัย

References

[1] Sakulngam, N., Sinthupinyo, S., Thawesaengskulthai, N. and Durongwatana, S. (2013) A study of tourism promotion factors affecting tourists’ demand in Thailand. In:
2013 IEEE International Conference on Industrial Engineering and Engineering Management. [Online]2013 IEEE International Conference on Industrial Engineering
and Engineering Management pp.636–640. Available from: doi:10.1109/IEEM.2013.6962489.
[2] Claster, W.B., Cooper, M. and Sallis, P. (2010) Thailand – Tourism and Conflict: Modeling Sentiment from Twitter Tweets Using Naïve Bayes and Unsupervised Artificial
Neural Nets.In: Modelling and Simulation 2010 Second International Conference on Computational Intelligence. [Online]Modelling and Simulation 2010 Second
International Conference on Computational Intelligence pp.89–94. Available from: doi:10.1109/CIMSiM.2010.98.
[3] Yotsawat, W. and Srivihok, A. (2013) Inbound tourists segmentation with combined algorithms using K-Means and Decision Tree. In: 2013 10th International Joint
Conference on Computer Science and Software Engineering (JCSSE). [Online]2013 10th International Joint Conference on Computer Science and Software
Engineering (JCSSE) pp.189–194. Available from: doi:10.1109/JCSSE.2013.6567343.
[4] Wicha, S., Temdee, P. and Suebsombut, P. (2014) Opened Pins Recommendation System to promote tourism sector in Chiang Rai Thailand. In: Signal and Information
Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific. [Online]Signal and Information Processing Association Annual Summit and
Conference (APSIPA), 2014 Asia-Pacific pp.1–4. Available from: doi:10.1109/APSIPA.2014.7041815.
[5] Wu, H.Y. and Lien, C.Y. (2013) The conceptual model of negative experiences regarding the facilities at family trip destinations; A case study of tourism factories. In:
2013 IEEE International Conference on Industrial Engineering and Engineering Management. [Online]2013 IEEE International Conference on Industrial Engineering
and Engineering Management pp.641–644. Available from: doi:10.1109/IEEM.2013.6962490.
[6] Office of the Permanent Secretary; Ministry of Tourism and Sports. (2011) The National Tourism Development Plan, 2012-2016. Bangkok, Thailand.
[7] Doong, H.S., Wang, H. and Chen, Y.Y. (2011) Study on success factors of tourism websites. In: 2011 Proceedings of the International Conference on e-Business (ICE-
B).2011 Proceedings of the International Conference on e-Business (ICE-B) pp.1–4.
[8] Mobarakeh, M.K. and Rezaei, M. (2014) Identification of effective factors and study of their impact on consumer acceptance of e-tourism in Iran. In: 2014 8th
International Conference on e-Commerce in Developing Countries: With Focus on e-Trust (ECDC). [Online]2014 8th International Conference on e-Commerce in
Developing Countries: With Focus on e-Trust (ECDC) pp.1–8. Available from: doi:10.1109/ECDC.2014.6836760.
[9] Xia, L. and Qing, L. (2012) Empirical analysis on the impact factors of China tourism foreign exchange income. In: 2012 International Conference on Information
Management, Innovation Management and Industrial Engineering. [Online]2012 International Conference on Information Management, Innovation Management and
Industrial Engineering 3, pp.407–410. Available from: doi:10.1109/ICIII.2012.6340004.
[10] Ngamsirijit, W. (2013) Using Capacity Flexibility Model for responsive tourism logistics: The case of Pattaya city. In: 2013 IEEE International Conference on Service
Operations and Logistics, and Informatics (SOLI). [Online]2013 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI) pp.404–
407. Available from: doi:10.1109/SOLI.2013.6611448.
[11] Liu, M. and Choosri, N. (2016) A technical solution to improve the red cab for touring in Chiang Mai: Chinese tourists’ perspective. In: 2016 Chinese Control and
Decision Conference (CCDC). [Online]2016 Chinese Control and Decision Conference (CCDC) pp.6075–6080. Available from: doi:10.1109/CCDC.2016.7532087.
[12] Nuankaew, P. and Temdee, P. (2015) Of online community: Identifying mentor and mentee with compatible different attributes and decision tree. In: 2015 12th
International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON). [Online]2015 12th
International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) pp.1–6. Available from:
doi:10.1109/ECTICon.2015.7207130.
[13] Nuankaew, P., Nuankaew, W. and Thamma T. (2016) The Recommended System for the Relationship between Educational Programs and Students’ Interests. In: 2016
The International Conference on Digital Arts, Media and Technology (ICDAMT-2016), 2-3A.4:34.
[14] Nuankaew, W., Nuankaew, P. and Sararat T. (2016a) To Study: The Significant Factors of Tourism Promotion with Clustering Methods. In: 2016 The 42nd Congress on
Science and Technology of Thailand (STT 42) (In Press), Bangkok, Thailand.
[15] Nuankaew, W., Nuankaew, P. and Sararat T. (2016b) For Discovery: Significant Factors for the Promotion of Tourist Attractions based on Individual Behaviour through
Data-mining Techniques. In: 2016 Chophayom Journal (In Press), Maha Sarakham, Thailand.
[16] Nuankaew, W. and Nuankaew, P. (2016c) To Study the Forecasting Models for Cultural Tourism Style in the Northern of Thailand using Data Mining Techniques. In:
2016 Teaching, Assessment and Learning for Engineering (TALE2016) (In Press), Bangkok, Thailand.