Eliciting citizen preferences for multifunctional agriculture in the watershed areas of northern Thailand through choice experiment and latent class models

Abstract

Multifunctional agriculture is increasingly discussed as an alternative to conventional, mono-functional farming and its negative environmental impacts. This study aims at determining Thai society's demand for agri-environmental services offered by a multifunctional agricultural system using two models, i.e. a Choice Experiment Model and a Latent Class Choice Model. The Choice Experiment Model (CEM) is employed to assess citizens’ willingness to pay for various attributes of multifunctional outputs. Extending from the CEM, the heterogeneity of citizens’ preferences across environmental attitudes and knowledge is captured through the Latent Class Choice Model (LCCM). Survey data was obtained from structured interviews with 373 respondents in the country's two largest cities, namely Bangkok and Chiang Mai. The results of the CEM suggest that urban Thai citizens are willing to pay for changes toward multifunctional agriculture, as expressed in an increase of their monthly food expenses. Among the attributes of agri-environmental practices, “organic agriculture in combination with agro-biodiversity conservation” garnered the highest preference, followed by “organic farming as single practice” and “Good Agricultural Practice combined with agro-biodiversity conservation”. Income, gender, agri-environmental knowledge and environment-conscious attitude are important factors determining urban citizens’ support of multifunctionality. Findings of the LCCM revealed a strong heterogeneity in attribute valuation across three different classes of respondents, suggesting that policy-makers need to be aware of diverse preference patterns among Thai citizens with regard to specific attributes of multifunctional agriculture. We further conclude that enhancing environmental literacy and consciousness is a key determinant in gaining citizens’ support for multifunctional agriculture.