This research aimed to explore the influences of water tourism demand on tourists' revisit intention. The data were collected by a questionnaire from a sample group of Thai and foreign tourists who used a water transportation service on the Mekong River in Luang Prabang, Lao PDR. The random sampling method was used as a convenience sampling technique by quota sampling and classified by ports that served tourists in the Luang Prabang area. Then, the data were analyzed by confirmatory factor analysis (CFA) using the ADANCO software program to verify the structural validity of the latent variables and analyze the model’s consistency. The study found that factors affecting the demand for water tourism consisted of two components: (1) Tourism factors and (2) water transportation factors on the Mekong River. Considering the factors that affected the demand for water tourism, it was found that the most influential factor was the water transportation of the Mekong River, especially the creation of a service product for tourists with the purpose of leisure and the type of water transportation service. Simultaneously, demand for water tourism was found to be one of the main factors reflecting the influence of tourists' revisit intention, especially water tourism on the Mekong River. According to the study, factors affecting the demand for water tourism in the Luang Prabang area greatly affected the demand for water tourism; in addition, the demand for water tourism affected the tourists' revisit intention as well. Therefore, entrepreneurs in water tourism should pay attention to water transportation, and whether it would be the type or design of the water transportation, standards of the water transportation, security measures, and setting a clear service schedule. etc., so that tourists could make their own travel plans to be more appropriate. Furthermore, the Lao government and the private sector should adopt common and unified policies for developing water tourism and promoting publicity and tourism marketing for the effectiveness of Luang Prabang’s water tourism activities.

The rate of foreign tourist arrivals coming to Vietnam as an emerging tourism market has been increased significantly bringing enormous benefits for improving the socio-economic indicators. The purpose of this paper is to examine the impact of exchange rate policy on the number of foreign tourist arrivals in Vietnam over the period 2006-2018. Our regression results show the exchange rate maintained a positive impact on the demand of foreign tourists and indicate that the domestic currency devaluation also had a positive effect on the number of foreign tourists to Vietnam. Besides, the quantitative result also indicates the number of foreign tourist arrival in the early periods had a positive impact on itself in the current period. Furthermore, the Granger causality test con-firms the existence of a one-way causal relationship between the exchange rate and the number of foreign tourist arrivals. Finally, the paper provides some implications for policymakers in order to efficiently use the exchange rate policy to increase the number of foreign tourist arrivals in the coming time.

Tourism has emerged as a major industry worldwide and a sector in many countries. This sector has experienced a rapid growth and has become a key driver for sustainable socioeconomic developments globally. However, tourism is also a vector of environmental degradation through the emission of greenhouse gases (GHG). Therefore, the aim of this study was to analyze the main factors that are affecting the tourism demand in ASEAN-5 countries. Using a panel of five ASEAN countries over a 44-year period and applying the Pooled Mean Group (PMG) approach, the empirical results have shown that the major determinants of tourism demand in these countries are income, trade, tourism price, and carbon dioxide emission. The results have also shown that the PMG performed better than the Mean Group (MG) estimator. This paper refers to the PMG estimator because it constrains the long run coefficients to be identical, but allows the short run coefficients and error variances to differ across groups. Income and trade appeared to exert significant positive impacts on tourism demand, whereas tourism price and carbon dioxide emissions have negative impacts on tourism demand in these ASEAN-5 countries. The results would be a good reference for policy makers in these specific countries.

This study analyzes the tourism network and destinations after the COVID-19 pandemic using social network analysis (SNA). Analysis of 789 destinations in Thailand has found that the destinations are connected by 1,1175 tourism routes. The network is a sparse network with a low network density. It seems to have a scale-free property that reflects that most destinations have low connectivity and a small number of destinations have high connectivity. The network has a large average path length and low clustering coefficient. Different roles of destinations are identified based on degree, betweenness and closeness centrality. The findings draw implications for vitalizing the sector.