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This study aims to present and empirically examines an expanded service model that incorporates green hotel practices together with a multidimensional/higher-order measurement model of service quality, as well as perceived value and satisfaction, to examine the relationships among these variables and hotel consumers’ loyalty/behavioral intentions (BI).

The model was examined using partial least squares structural equation modeling (PLS-SEM) using data gathered in August 2018 from 200 surveys completed by UK subjects who stayed at upscale European hotels.

The results of PLS-SEM found that hotel service quality has a direct and positive effect on perceived value, satisfaction and BI. There is also an indirect effect of service quality on BI through perceived value and satisfaction, while green practices only had a direct effect on perceived value, not satisfaction or BI.

This study offers new insights into the network of causal relationships among determinants of hotel consumers’ BI. The results offer hotel operators a better understanding of specific green practices and service quality attributes they can use to more favorably influence consumers’ intentions to revisit the property and recommend them through positive word-of-mouth.

This research is particularly relevant in today’s reality characterized by travelers’ growing concern for green issues and business’ responsibilities toward the environment. Moreover, unlike previous studies, this study assumes a multidimensional scheme for service quality, further enhancing the understanding of hotel consumers’ BI relationships.

This study examines the effect of sustainable development goal (SDG) concerns regarding the sustainability issues raised in the United Nations SDG agenda on pro-sustainable travel behavior (PSTB) by building on the norm activation model as well as value theory (altruism), with the latter assumed to moderate the effect of SDG concerns on PSTB.

The model was tested using structural equation modeling (SEM) based on data from 200 USA respondents who have traveled internationally in the past 12 months.

The results confirmed the effect of SDG concerns on positively influencing PSTB both directly and indirectly (through the NAM variables of “responsibility” and “obligation”). Additionally, results revealed that altruism positively moderates the effect of SDG concerns on PSTB.

Results provide tourism businesses and destinations with a better understanding of which aspects of the 17 issues identified in the UN SDG agenda are more likely to influence travelers’ future PSTB and whether such behavioral changes additionally depend on people’s individual altruism levels.

Unlike previous studies focusing mainly on environmental concerns and tourists’ pro-environmental behavior, this study offers a more comprehensive understanding of PSTB in light of today’s UN SDGs.

This study aims to examine a comprehensive model for the concurrent effects of tourists’ sustainability concerns, social norms, frugality and awareness of the UN’s sustainable development goals (SDGs) on sustainable travel behavior (STB), with sustainability in this case extending beyond the environmental to include economic and socio-cultural aspects as well.

The model is tested using a structural equation modeling technique based on data collected from 200 US respondents who traveled internationally in the past year.

Results reveal that all aforementioned variables, namely, sustainability concerns, social norms, frugality and SDG awareness, when considered together each positively influenced STB. However, SDG awareness did not accentuate tourists’ sustainability concerns associated with travel and tourism, as initially hypothesized.

Unlike previous studies that have mainly focused on the pro-environmental aspects of sustainability and failed to consider the aforementioned variables concurrently, the results from this study advance our understanding of the determinants of STB (more generally) while accounting specifically for the expected role of the UN SDG agenda.

This chapter reviews the methods available to hospitality and tourism researchers to perform moderation analysis with continuous variables in partial least squares structural equation modeling (PLS-SEM), with the objective of enhancing understanding and encouraging the use of these techniques in future papers. The product term method is presented first, followed by an empirical example/application in the context of hospitality and tourism. Two extensions, namely the two-stage approach that can help cope with formative and higher-order constructs, and the orthogonalizing approach that can help generate more accurate results and overcome multicollinearity among tourism variables in the presence of a continuous moderator variable, are then presented and discussed. The chapter concludes by presenting guidelines and recommendations for improving the use of interaction effects in analyses of tourism variables, as well as highlighting ongoing developments in both the product term method and PLS-SEM software.

The purpose of this paper is to capture the causal relationships between the primary constituents of the tourism destination paradigm – namely, the economy, society, and the natural and infrastructural environments – and demand for tourism at that destination.

Inspired by prior tourism literature, the study uses structural equation modeling (SEM) methodologies with a cross‐sectional data sample from 162 countries, to evaluate a priori proposed measurement and structural models for relationships among the economy, society, environment constructs, and tourism.

The results indicate that although the economy construct was found to have no direct influence on tourism, it does have a mediating, positive impact on tourism through the society and environment constructs, with the society construct paralleling the condition of the infrastructure. Moreover, society and environment were found to have a direct, positive impact on generating tourism activities, and revenues.

This study contributes to the literature on tourism demand modeling by verifying causal relationships between tourism constructs and supply variables at the “country” level. In other words, it examines whether relationships among tourism constructs and variables exist and, as such, asks if they are responsible for a destination's success.

This study's results provide destination managers with information to help them understand how individual variables affect the economy, society, and tourism industry aggregately, and as such what actions or investments can help to develop a country's tourism industry effectively.

By integrating several supply‐side factors related to the destination, this paper provides more comprehensive results compared to previous applications of SEM that used a limited number of destination variables and subsequently provided only limited results.