Mapping Preferences Derived from a Choice Experiment: A Comparison of Two Methods

Abstract

In recent decades, discrete choice experiments (DCEs) have proven useful for guiding policy-making decisions, particularly regarding the expression of individual preferences for various policy options. However, when considering spatial planning policies, the usefulness of results such as averaged individual or group preferences may prove limited for decision-makers, since the spatial heterogeneity of preferences is strong in most cases. This paper therefore proposes two methods for mapping, at a small spatial scale, preferences derived from a DCE. Both methods assess the influence of socio-demographic and spatial variables on the preferences to predict willingness to pay at a small spatial scale. Monte Carlo simulations are used to determine the method which best performs in theory. The methods are then compared empirically in the case of light pollution mitigation policies in the Montpellier Metropolitan Area (France). We conclude that, when applicable, the one-step method is the most fit for the purpose, although the two-step method shows practical aspects that can be of interest for applied research.

Keywords: Discrete choice experiment, spatial heterogeneity, spatial planning, social preferences mapping, Monte Carlo simulations, light pollution.