Maximum Difference Scaling: Improved Measures of Importance and Preference for Segmentation (2003)

Maximum Difference (MaxDiff, or best/worst) scaling is a relatively new technique for measuring the importance or preference of multiple items. In MaxDiff tasks, respondents see sets of items (typically 4 to 6). In each set, respondents indicate which item is most important (preferred) and least important (preferred). Steve Cohen describes the methodology and presents results for a methodological study comparing MaxDiff measurement with monadic ratings and paired comparisons, and also a case study focusing on using MaxDiff for segmentation work. MaxDiff is shown to provide results that have greater between-item and between-respondent discrimination, and greater predictive accuracy than either monadic ratings or paired comparisons. Steve won the "best presentation" award with this paper at the 2003 Sawtooth Software Conference.

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