Latent Class Model

A choice experiment approach to evaluate maize farmers’ decision-making processes in Lao PDR

We used discrete choice experiments to explore the potential adoption of alternative agricultural systems. We analyse the heterogeneity of farmers’ preferences and heuristics of choices using a latent class model, where class can include different heuristics such as attribute non attendance, and elimination by aspect.

Identify Lao farmers' goals and their ranking using best–worst scaling experiment and scale‐adjusted latent class models

We developed a best–worst scaling (BWS) experiment, in which farmers have to declare the “most” and the least “important” goals they use when making decisions. We first derive a ranking of the goals according to the population average, which showed the importance of rice self-sufficiency and transmission of farm capital. We then use a scale-adjusted latent class analysis. We identified four groups of homogenous preferences among farmers.