Preferences and Willingness to Pay for Green Hotel Attributes in Tourist Choice Behavior: The Case of Taiwan

Abstract

ABSTRACTAlthough many companies in the hotel industry aim to pursue more sustainable and socially responsible practices, the present literature shows mixed results with regard to tourist reactions to such moves, especially for the service quality perception impacted by implemented green practices and the willingness to pay more for such actions. Unlike previous research examining tourists’ preferences for separate green hotel attributes, this study identifies the determinants of tourists’ choice of green hotel attributes. Additionally, the study measures the willingness to pay (WTP) for such services, in the context of the Taiwanese market, using the stated preference of combined green hotel attribute scenarios. A multinomial logit (MNL) model is employed to estimate the relative influence of behavioral and facility attributes on choice behavior. Furthermore, the study examines determinants influencing respondents’ choice of green hotel attributes. A latent variable class model (LVCM) approach is applied in the estimation of the unobserved heterogeneity, and a total of 390 valid respondents were used in the analysis. The empirical MNL results indicate that while tourists prefer luxury rooms and the provision of personal toiletries, they are also willing to accept reduced service quality. Additionally, sex, income, and age have significant influences on tourist choice behavior. The results of the LVCM model demonstrate that respondents with high levels of the green consumption trait are more likely to choose hotels that have a greater number of environmentally friendly attributes. The implicit amount that tourists are willing to pay for room quality is around US$13, for the provision of personal toiletries is about US$22, and for service quality is US$12, but they also require a discount of approximately US$11 in order to accept the common practices of green hotels. This study is useful in providing the hotel industry and government with quantitative information that can be used to develop and implement better green hotel policies.