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The perception of costs and benefits allows residents to carry out an assessment that determines their attitude towards tourism. This study seeks to determine the effect of the perceived benefits and costs (economic, sociocultural and environmental) on the support to the arrival of more tourists, both directly and mediated by overall attitude towards tourism, in the case of Punta del Este. Punta del Este forms part of the Department of Maldonado and is the main sun and beach tourism destination in the Oriental Republic of Uruguay. The questionnaire contained items with five-point Likert scales and sociodemographic questions. The data used (obtained between March and August 2016) are made up of a sample of 420 residents from Maldonado and Punta del Este. The analysis of the data has been carried out through partial least squares (PLS) regression, specifically SmartPLS. Among the results, it should be noted that benefits and costs perceived have no direct effect on the support to the arrival of more tourists; only economic benefits (positive) and sociocultural costs (negative) have a significant effect on the overall attitude towards tourism; the support to the arrival of more tourists depends exclusively on the overall attitude.

Increased competition amongst the hotel industry players has challenged managers not to focus their attention exclusively on ways to attract and satisfy their customers, but to invest in customer retention strategies with the potential to ensure superior performance of their hotels. This study aims to determine strategies to retain customers in hotels in Ghana, an emerging market. A cross-sectional survey was employed to collect data from 677 hotel employees in 56 Ghanaian licensed hotels. Based on SmartPLS, study findings indicate that customer satisfaction, loyalty and retention embedded in the tangibility and reliability dimensions of the lodging quality index are important for customer retention among hotels in Ghana.

This study focuses on examining the impact of energy consumption, economic structure, population, and manufacturing output on the CO₂ emissions of selected emerging countries by utilizing the Structural Time Series Model (STSM). Based on the annual data ranging from 1970 to 2019, the model is built up using total primary energy consumption, GDP per capita, population and manufacturing value-added, and, finally, a stochastic Underlying Emission Trend as explanatory variables. STSM is extended by the introduction of the notion of Underlying Energy Demand Trend (UEDT) as a factor for exogenous effects, including development in technical progress, energy efficiency improvements, changes in human behaviors, economy, and environmental regulations. In this context, STSM and the notion of UEDT are implemented to form a forecasting model for CO₂ emissions of the selected emerging countries. The model discovers the significant influences of all selected variables of CO₂ emissions. The results suggest that the most forceful factor in CO₂ emissions is the total primary energy supply. Furthermore, while the long-term impact of economic growth on CO₂ emissions is negative for some emerging economies, it is positive for several others. The model also measures the long-term manufacturing value-added elasticity of CO₂ emissions in these emerging economies.

Tourism and community development are two complementary variables. There are many studies in the literature examining the effects of tourism on society. However, the number of studies focussing on the subject from the perspective of overtourism is still very limited. Although a shrinking in tourism demand is estimated for the next few years due to Covid-19, it is expected that the sector will face an even more intense tourist boom around the world after this health crisis. Therefore, the phenomenon of overtourism remains important. In this context, a conceptual examination was made in the current chapter regarding the observed and possible effects of tourism density on communities. The existing literature clearly shows that being successful in the long term is impossible with a tourism plan that uses natural resources, infrastructure facilities and traditional values of the region to create tourist demand but ignores the wishes and well-being of the community residents.

Environmental degradation is a global concern that results from massive economic activities. Carbon dioxide (CO₂) emissions are one of the environmental degradation indicators. This study investigates the impact of population, oil consumption, international tourist arrival, and corruption on CO₂ emissions in ASEAN’s five developing countries of Malaysia, Indonesia, Thailand, Philippines, and Vietnam from 1998 to 2017. This study employed panel Fixed-effect (FE) regression to estimate the panel data generated by British Petroleum and World Bank. The result revealed that the population has a significant positive effect on CO₂ emissions. Furthermore, oil consumption has a significant positive effect on CO₂ emissions. Meanwhile, the effect of tourism and the corruption perception index (CPI) as a proxy of corruption on CO₂ emissions was positive but not significant. Authorities should construct such policies to reduce CO₂ emissions by applying low-carbon technologies, green mass transport, and creating less corrupt behavior.