Best--worst scaling: What it can do for health care research and how to do it.

By Terry N. Flynn, Jordan J. Louviere, T. Peters, J. Coast. Journal of Health Economics, 2007

830 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/cda64116057b197c9732a1c9959d11ef23085ba4

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In Economics and Econometrics

Citations in the corpus

Constructing experimental designs for discrete-choice experiments: report of the ISPOR Conjoint Analysis Experimental Design Good Research Practices Task Force. (2013, background): “[26] Flynn TN, Louviere JJ, Peters TJ, et al.”
Discrete Choice Experiments in Health Economics: Past, Present and Future (2018, background): “Case 3 BWS, however, involves an attribute-based comparison between two or more alternatives and is considered an extension of DCEs in the literature [367, 42].”
What you see may not be what you get: Asking consumers what matters may not reflect what they choose (2010, methodology): “One method is a direct measurement of feature importance, which we accomplish with best–worst scaling along with graphical representations of some packaging elements (Marley and Louviere 2005; Finn and Louviere 1992; Flynn et al. 2007 ), and a second, indirect method is based on a DCE (Louviere and”
Comparison of best–worst and hedonic scaling for the measurement of consumer wine preferences (2009, background): “The difference between best and worst scores in a BWS experiment can either be calculated on a sample or a respondent level depending on the design (Flynn et al. 2007).”
Best-worst scaling: theory and methods (2014, background): “Analysis of best-worst data can be conducted in a variety of ways (Louviere et al., 2008; Flynn et al., 2007; Flynn 2010).”
Conducting Discrete Choice Experiments to Inform Healthcare Decision Making (2012, background): “and worst attribute level in several single profiles, DCEs can isolate and measure patient preferwhich potentially allows one to estimate the imporences, but decisions about healthcare treatment can tance of each attribute and measure them on a cominvolve joint decisions between patients and their m”
Consumer preferences of wine in Italy applying best‐worst scaling (2009, methodology): “Flynn et al. (2007) stated that with BW it is possible to estimate the impact of all but one attribute, where the impact of an attribute is the average across all its levels.”