Kantimarn Chindaprasert

Dr. Kantimarn Chindaprasert

Faculty of Tourism and Hotel Management, Mahasarakham University, Thailand

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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22 February 2021 in Computation
Verified
Journal Article
Open access
PDF file
NKNarisara Khamsing
Narisara Khamsing
Kantimarn ChindaprasertKantimarn Chindaprasert
Kantimarn Chindaprasert
Rapeepan PitakasoRapeepan Pitakaso
Rapeepan Pitakaso
WSWorapot Sirirak
Worapot Sirirak
CTChalermchat Theeraviriya
Chalermchat Theeraviriya
This research presents a solution to the family tourism route problem by considering daily time windows. To find the best solution for travel routing, the modified adaptive large neighborhood search (MALNS) method, using the four destructions and the four reconstructions approach, is applied here. The solution finding performance of the MALNS method is compared with an exact method running on the Lingo program. As shown by various solutions, the MALNS method can balance travel routing designs, including when many tourist attractions are present in each path. Furthermore, the results of the MALNS method are not significantly different from the results of the exact method for small problem sizes. For medium and large problem sizes, the MALNS method shows a higher performance and a smaller processing time for finding solutions. The values for the average total travel cost and average travel satisfaction rating derived by the MALNS method are approximately 0.18% for a medium problem and 0.05% for a large problem, 0.24% for a medium problem, and 0.21% for a large problem, respectively. The values derived from the exact method are slightly different. Moreover, the MALNS method calculation requires less processing time than the exact method, amounting to approximately 99.95% of the time required for the exact method. In this case study, the MALNS algorithm result shows a suitable balance of satisfaction and number of tourism places in relation to the differences between family members of different ages and genders in terms of satisfaction in tour route planning. The proposed solution methodology presents an effective high-quality solution, suggesting that the MALNS method has the potential to be a great competitive algorithm. According to the empirical results shown here, the MALNS method would be useful for creating route plans for tourism organizations that support travel route selection for family tours in Thailand.

1 March 2015 in Asia-Pacific Journal of Innovation in Hospitality and Tourism (APJIHT)
Verified
Journal Article
Open access
PDF file
Kantimarn ChindaprasertKantimarn Chindaprasert
Kantimarn Chindaprasert
PYParadee Yasothornsrikul
Paradee Yasothornsrikul
RERanee Esichaikul
Ranee Esichaikul
Over the past few decades, the influence of the Greater Mekong Sub-region (GMS) program and Asian Economic Community (AEC) framework of ASEAN has led to an increasing number of tourists visiting Thailand and Laos (PDR) border sites. Accordingly, the Thailand-Laos (PDR) border destination appears to have a high tourism market potential as it is seen as an important tourist attraction, nationally and internationally. The investigation of cross-border tourism in this area will benefit the development of the tourism industry along Thailand and Laos (PDR). Consequently, the current study aims to investigate a structural model explaining destination loyalty and its inter-relationship with push and pull motivation, and satisfaction, in the context of Thai revisits to the Thailand-Laos (PDR) border destination. A total of 400 questionnaires were collected and analysed by a Structural Equation Modeling software called Mplus version 6.12. Findings of this study reveal that push motivation and satisfaction are both determinants of Thai visitors’ destination loyalty for the Thailand-Laos border. Implications for Thailand and Laos (PDR) border destination managers are also discussed.