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Drawing upon an extensive body of valuation literature focused on water quality, this paper performs a meta-analysis benefit transfer exercise aimed at quantifying willingness to pay (WTP) for an enhancement in drinking water quality for households that have been directly exposed to Perfluoroalkyl Substances (PFAS) over recent decades in Italy. The analysis compiles metadata of 72 WTP estimates extracted from 40 previous valuation studies conducted in advanced economies. The benefit transfer is realized estimating a meta regression model (MRM) which includes both study design and socio-economic explanatory variables, according to the Weak Structural Utility Theoretic approach. To determine the most suitable MRM specification, a comparative evaluation of various model configurations is developed exploiting the Least Absolute Shrinkage and Selection Operator (LASSO) selection criterion, and assessing their predictive performances in terms of transfer error and explanatory power. The mean transfer error (MTE) and the adjusted R-squared of the preferred MRM are in line with past published meta-analyses (0.665 and 0.607, respectively). The parameters estimated in the model align with both economic theory and intuition. The benefit transfer process results in an estimated annual WTP of € 250.80 per household for improved drinking water quality in the PFAS-affected area and an aggregated value of social benefits from PFAS decontamination of around € 12 million. • First meta-analysis focused on drinking water quality valuation in developed economies. • WTP for PFAS decontamination of drinking water via benefit transfer. • LASSO selection criteria applied for the selection of variables in the meta-regression model. • New dataset for drinking water quality valuation around the world. [ABSTRACT FROM AUTHOR]

This paper proposes a novel four-step methodology to achieve an extended-reality-based choice experiment in historic and touristic centers. The study exploits the case of Manfredonia (a seaside town in southern Italy) to apply the new approach and investigates public attitudes and preferences towards the installation of offshore wind turbines in the area. The novelty of the proposed work is twofold: i) for the first time, a structured methodological approach is defined for the development of a hybrid extended-reality-based choice experiment; ii) the perception of the visual impact of offshore wind turbines is assessed in a touristic and historic city in southern Italy exploiting the proposed approach. Our findings underscore the importance of continuously monitoring public perceptions to maintain and promote support for sustainable energy solutions, particularly in relation to the perception of wind energy's visual impact. In particular, 65% of respondents express their worries about wind power plants impact on the landscape. Moreover, the positive coefficient of the visual impact (0.011) suggests a positive utility of respondents from a higher off-shore turbines' density and a marginal willingness to accept a compensation of about 13€ for the visual impact and of about 33€ for the distance from the shore. In this context the use of extended reality technology in choice experiment scenarios significantly improves the results and enhances the understanding of the landscape impact of offshore wind farms. [Display omitted] [ABSTRACT FROM AUTHOR]