A formal and empirical comparison of two score measures for best–worst scaling. (December 2016)

• Record Type: Journal Article
• Authors: Marley, A.A.J.; Islam, T.; Hawkins, G.E.
• Is Part Of: Journal of choice modelling. Volume 21(2016)
• Page Start: 15
• Page End: 24
• Publication Date: 2016-12
• Subjects: Best–worst scaling -- Best–worst choice -- Discrete choice -- Experiment -- Scores -- Choice model; Decision making -- Periodicals; Social choice -- Periodicals; Decision making; Social choice; Periodicals; 302.13
• DOI: 10.1016/j.jocm.2016.03.002
• Languages: English
• ISSNs: 1755-5345

Abstract

Abstract: Best–worst scaling (BWS) is a method that asks individuals to choose the most and the least preferred option from a set of available options. There has been extensive discussion and evaluation of the use of scores (data summaries) in the analysis of such data. Here we motivate, summarize, and compare the usefulness of two such score measures: the analytical closed form solution (Lipovetsky and Conklin, 2014, Journal of Choice Modelling ) and normalized best–worst scores (Louviere et al., 2015, Cambridge University Press ). We conclude that both have underlying motivations in the maxdiff model of best–worst choice and that the analytical closed form solution provides better fits to the aggregate choices in several best–worst choice data sets. Abstract : Highlights: Best–worst scaling involves choosing the most and the least preferred option. Score measures are data summaries that are very useful for exploratory analyses. We study the analytical closed form solution and normalized best–worst scores . Each measure has underlying motivations in the maxdiff model of best–worst choice. The analytical closed form solution provides better fits to aggregate data.