Heterogeneous preferences of citizens towards agricultural ecosystem services: the demand relevance in a choice experiment. Issue 1 (1st January 2021)

• Record Type: Journal Article
• Authors: Tienhaara, Annika; Ahtiainen, Heini; Pouta, Eija
• Is Part Of: Ecosystems and people. Volume 17:Issue 1(2021)
• Page Start: 114
• Page End: 127
• Publication Date: 2021-01-01
• Subjects: Bas Amelung; Agriculture -- ecosystem services -- choice experiments -- environmental valuation -- demand relevance; Ecosystem management -- Periodicals; Biotic communities -- Social aspects -- Periodicals; Ecosystem management; Periodicals; Electronic journals; 333.9516
• DOI: 10.1080/26395916.2021.1890641
• Languages: English
• ISSNs: 2639-5908

Abstract

ABSTRACT: Agri-environmental policies affect many ecosystem services from agricultural environments. Valuing ecosystem services with choice experiments requires operationalization of these services for the survey and a careful attribute selection process, as the attributes need to be relevant to respondents. In this paper, we expand the concept of demand relevance of attributes to include not only the importance of ecosystem services to the respondent, but also the success in the supply of these services and the need to improve them. We examined this in the context of citizens' preferences for ecosystem services from agri-environments. The results revealed five citizen groups with differing preferences. Respondents with high demand relevance for ES in the survey were divided into those emphasizing existence values and those emphasizing ES more directly related to the human use of ecosystems. In turn, low demand relevance for the ES was associated with a non-significant cost attribute, preventing the estimation of WTP for these respondents, and led to anomalies in choices. Our findings emphasize the need to take respondents' heterogeneity with respect to preferences, but also to demand relevance, into account in data analysis and support the inclusion of other factors than the importance of attributes when examining demand relevance.