Journal
JOURNAL OF ENVIRONMENTAL MANAGEMENT
Volume 292, Issue -, Pages -Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jenvman.2021.112743
Keywords
Renaturation measures; Water ecosystems; Flood mitigation; Choice experiments; Hybrid latent class choice model
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Funding
- Regional Government of Sardinia - Water Authority (Agenzia Regionale del Distretto Idrografico della Sardegna - Servizio Tutela e Gestione della Risorsa Idrica) [12/12405]
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This study contributes to the research on social acceptance of interventions aimed at water ecosystem improvement and flood risk mitigation through renaturation measures. By applying a Hybrid Latent Class (HLC) model to the data, the study reveals the existence of two distinct groups with different valuations of project attributes, depending on latent attitudes toward environmental protection and risk perception. The study confirms the effectiveness of the HLC modeling approach in stated preference studies regarding ecosystems valuation as it enhances understanding of public preferences and provides more targeted policy indications.
The present paper offers a contribution to the research on social acceptance of interventions aimed at water ecosystem improvement and flood risk mitigation through renaturation measures. A CE study has been implemented to assess trade-offs between attributes of alternative projects, including social costs deriving from proposed actions of renaturation of river flows. The aim of our approach is to investigate the role of attitudinal factors in the valuation of costs and benefits generated by renaturation measures. A Hybrid Latent Class (HLC) model is applied to the data, revealing the existence of two distinct groups, characterised by different valuations of the attributes of the project. It is found that class membership depends on latent attitudes toward environmental protection and risk perception. Our study confirms the fruitfulness of the HLC modelling approach in stated preference studies regarding ecosystems valuation, as it provides a richer understanding of public preferences and allows more finely targeted policy indications.
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