Research that discusses the impact of implementing Green Human Resource Management and environmentally friendly behavior, especially in sustainable tourism, is limited. It becomes crucial to understand how implementing good green human resource management practices in tourism sector organizations. To achieve the objectives of this research, a qualitative approach was used where the data and information collected were obtained through direct observation and interviews with tourism informants. The findings show the importance of environmentally friendly behavior as the implementation of green human resource management is able to improve tourism management. The uniqueness of this research is developing a model of human resource readiness in implementing environmentally friendly behavior towards sustainable tourism. This resource readiness will be reflected in the GHRM model in supporting sustainable tourism. The results of this research offer a model of sustainable Green Tourism which includes antecedents, implementation and results achieved. These antecedents come from internal and external (environmental ethics and management commitment) managers which will result in good GHRM implementation. This model will be the basis for implementing sustainable tourism in human resource management practices based on literature reviews and also tourism management practices.

This study examined the role of cryptocurrencies in tourism and their acceptance across EU regions, with particular attention to the digital transformation precipitated by the COVID-19 pandemic. The analysis focuses on the relationship between cryptocurrency acceptance points and the intensity of tourism, highlighting that the acceptance of cryptocurrencies is significantly correlated with tourism services. The literature review highlighted that Web 3.0, especially blockchain technology and decentralized applications, opens new possibilities in tourism, including secure and transparent transactions, and more personalized travel experiences. The research investigated cryptocurrency acceptance points and the intensity of tourism within the EU. The study illuminates that the acceptance of cryptocurrencies significantly correlates with tourism services. The data and methodology demonstrated the analysis methods for examining the relationship between cryptocurrency acceptance points and tourism intensity, including the use of clustering neural networks and Eurostat data utilization. The results showed a positive correlation between the number of cryptocurrency acceptance points and tourism intensity in the EU, affirming the research hypothesis. According to the regression analysis results, each additional cryptocurrency acceptance point is associated with an increase in tourism intensity. The significance of the research lies in highlighting the growing role of digital payment solutions, especially cryptocurrencies, in tourism, and their potential impacts on the EU economy. The analysis supports that the intertwining of tourism and digital financial technologies opens new opportunities in the sector for both providers and tourists.

The COVID-19 pandemic in 2019 heralded a downturn in the Thai economy, particularly in the tourism and hospitality sectors which rely heavily on international tourists. To decrease the dependence of international tourists, this research outlined three objectives as 1) explore and classify the high-end domestic tourism market among 77 provinces in Thailand, 2) study the potential and readiness of tourism resources and tourism products to cater to the demand of high-end domestic tourists, and 3) suggest tourism management approaches for domestic high-end tourists after the crisis. Both quantitative and qualitative research methodologies were applied to achieve the research objectives. Income was used to identify and segment high-end domestic tourists living in 77 provinces in Thailand, while a verified questionnaire collected data from 1200 respondents nationwide. Forty-one experts from different tourism-related agencies at local and regional levels were targeted using purposive sampling techniques, and semi-structured interviews were conducted to acquire qualitative data. High-end domestic tourists, classified by monthly income, were segmented into Silver (50,000–70,000 THB), Gold (70,001–90,000 THB), Diamond (91,001–110,000 THB), and Platinum groups (Over 110,001 THB). These high-end domestic tourists shared both similarities and differences in tourism needs, preferences, and behaviors. Sixteen provinces in six domestic regions demonstrated the potential and readiness of tourism resources and products to satisfy the needs, preferences, and behaviors of high-end domestic tourists.