TY - JOUR
T1 - An estimate of the value of the beachfront with respect to the hotel room rates in Thailand
AU - Somphong, Chatuphorn
AU - Udo, Keiko
AU - Ritphring, Sompratana
AU - Shirakawa, Hiroaki
N1 - Funding Information:
The authors would like to thank the Department of Coastal and Marine Resources of Thailand (DMCR) for providing the location of sandy beach zones data, location of coastal protection structures data, and coastal provinces' land cover data. This research was supported by the Advancing Co-design of Integrated Strategies with Adaptation to Climate Change on Thailand (ADAP-T) supported by the Science and Technology Research Partnership for Sustainable Development (SATREPS), JST-JICA and the Research and Development Grant of Japan Institute of Country-ology and Engineering.
Funding Information:
The authors would like to thank the Department of Coastal and Marine Resources of Thailand (DMCR) for providing the location of sandy beach zones data, location of coastal protection structures data, and coastal provinces' land cover data. This research was supported by the Advancing Co-design of Integrated Strategies with Adaptation to Climate Change on Thailand (ADAP-T) supported by the Science and Technology Research Partnership for Sustainable Development (SATREPS) , JST-JICA and the Research and Development Grant of Japan Institute of Country-ology and Engineering .
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/7/1
Y1 - 2022/7/1
N2 - An economic assessment for a non-market resource like sandy beaches is always a challenge for Thailand's coastal policy planners due to the lack of data availability, especially on the national scale. While beach tourism in Thailand has been an essential part of the Thai economy, the sandy beaches are probably exposed to the future sea-level rise. Therefore, the need for tourism benefits of the beaches should be conducted. The research attempted to measure the effect of sandy beach characteristics and hotel location on hotel room rates. A sample of 3319 hotel rooms across Thailand's coastal sub-districts, covering the entire sandy beaches in Thailand, was collected through a hotel-booking online database during the country's peak season. The considered variables include hotel room attributes, sandy beach characteristics, hotel locations, and coastal infrastructures. Through a hedonic price model based on geographically weighted regression analysis, the relationship between the dependent variables (hotel room rate) and the independent variables (selected beach variable) was estimated to evaluate the marginal effect and its spatial variations. The tourism benefit was calculated assuming the marginal effect of the hotel's beachfront locations on hotel price. The study suggested that the location in front of the beach raised the average hotel room rates by 13–41%. The results emphasized the significant spatial variability of the effect of beachfront location on the hotel price. In addition, the effect of beach protection structures (i.e., seawall, breakwaters, groins) on the hotel price was also investigated and implied a slight drop by 8–15% of the average price. The other sandy beach variables (such as beach length, width, and slope) effects on hotel price were also investigated. The finding of this study aims to help policymakers select and design proper adaptations to coastal erosion on tourist beaches in Thailand.
AB - An economic assessment for a non-market resource like sandy beaches is always a challenge for Thailand's coastal policy planners due to the lack of data availability, especially on the national scale. While beach tourism in Thailand has been an essential part of the Thai economy, the sandy beaches are probably exposed to the future sea-level rise. Therefore, the need for tourism benefits of the beaches should be conducted. The research attempted to measure the effect of sandy beach characteristics and hotel location on hotel room rates. A sample of 3319 hotel rooms across Thailand's coastal sub-districts, covering the entire sandy beaches in Thailand, was collected through a hotel-booking online database during the country's peak season. The considered variables include hotel room attributes, sandy beach characteristics, hotel locations, and coastal infrastructures. Through a hedonic price model based on geographically weighted regression analysis, the relationship between the dependent variables (hotel room rate) and the independent variables (selected beach variable) was estimated to evaluate the marginal effect and its spatial variations. The tourism benefit was calculated assuming the marginal effect of the hotel's beachfront locations on hotel price. The study suggested that the location in front of the beach raised the average hotel room rates by 13–41%. The results emphasized the significant spatial variability of the effect of beachfront location on the hotel price. In addition, the effect of beach protection structures (i.e., seawall, breakwaters, groins) on the hotel price was also investigated and implied a slight drop by 8–15% of the average price. The other sandy beach variables (such as beach length, width, and slope) effects on hotel price were also investigated. The finding of this study aims to help policymakers select and design proper adaptations to coastal erosion on tourist beaches in Thailand.
KW - Accommodation price
KW - Coastal tourism
KW - Geographically weighted regression
KW - Hedonic pricing method
KW - Sandy beaches
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U2 - 10.1016/j.ocecoaman.2022.106272
DO - 10.1016/j.ocecoaman.2022.106272
M3 - Article
AN - SCOPUS:85133687601
SN - 0964-5691
VL - 226
JO - Ocean and Coastal Management
JF - Ocean and Coastal Management
M1 - 106272
ER -