A choice experiment approach to evaluate maize farmers' decision-making processes in Lao PDR. (September 2022)

• Record Type: Journal Article
• Authors: Jourdain, Damien; Lairez, Juliette; Striffler, Bruno; Lundhede, Thomas
• Is Part Of: Journal of choice modelling. Volume 44(2022)
• Publication Date: 2022-09
• Subjects: Behavioural mixing -- Taste heterogeneity -- Elimination by aspects -- Random utility -- Latent class; Decision making -- Periodicals; Social choice -- Periodicals; Decision making; Social choice; Periodicals; 302.13
• DOI: 10.1016/j.jocm.2022.100366
• Languages: English
• ISSNs: 1755-5345

Abstract

Abstract: Sustainable intensification seeks to increase outputs from existing farmland in ways that have a lower environmental impact. An extensive literature has examined the determinants of farmers' adoption of the different agro-ecological cropping systems needed to achieve these goals. However, the farmers' preferences for the attributes of these systems and the decision processes for choosing between available systems is still poorly understood. To fill this gap, this paper proposes a methodology that relies on a discrete choice experiment to analyse farmers' preferences for cropping systems and estimate the heterogeneity of decision processes among farmers. We modelled three major types of decision processes potentially used by farmers to evaluate the systems that are not consistent with the standard utility maximization framework. These findings offer insights into the behavioural patterns of respondents and should help crop system promoters and developers to better understand how their proposed systems are likely to be evaluated by different types of farmers. Highlights: Farmers' preferences and decision processes for choosing between agricultural systems is still poorly understood. A Discrete Choice Experiment was used to understand farmers' preference in Lao PDR. We used a pre-screening model (Vrij and Krueger, 2017) to reduce the set of Attribute Non Attendance (ANA) rules modelled. We used a latent class approach to estimate the probability that respondents use ANA or Elimination by Aspects decision rules. We find that these non-compensatory decision rules are important.