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Extended reality-based choice experiment to assess the impact of offshore wind turbines in historic center: The case of Manfredonia

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 toward...

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Bibliographic Details
Published in:Journal of environmental management 2024-01, Vol.349, p.119454-119454, Article 119454
Main Authors: Caporale, Diana, Sangiorgio, Valentino, De Lucia, Caterina
Format: Article
Language:English
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Summary: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]
ISSN:0301-4797
1095-8630
DOI:10.1016/j.jenvman.2023.119454