In this paper we demonstrate a method that enables you to identify random respondents during a MaxDiff survey. This means that you may be able to tag and disqualify poor quality respondents before ... Read More
Chapter 6 exerpt from the book Applied MaxDiff.
Over the last 15 years, new flavors of MaxDiff have been devised to extend its capabilities to measure more items or to address drawbacks. This short white paper describes seven different flavors of ... Read More
Best-worst scaling (BWS) gives you better information with fewer respondents—it works better than traditional rating scales or constant sum questions, achieving better discrimination among the items ... Read More
Bandit MaxDiff (best-worst scaling) achieves greater measurement precision than standard MaxDiff for items that have the highest utility scores. When that is your focus, you can vastly improve the ... Read More
Clients don’t seem to be able to get enough of a good thing and this seems to apply more to MaxDiff than to some of the other methods we use: clients frequently ask for MaxDiff experiments that ... Read More
The author (Orme) describes a hybrid discrete choice method that results in conjoint utilities on a common utility scale (where comparisons across levels of different attributes are supported). For ... Read More
This paper describes the technical procedures used in the MaxDiff System. MaxDiff (best-worst) scaling is a trade-off method for measuring the importance or preference for multiple items, such as ... Read More
Maximum Difference Scaling is widely used to measure the relative values of items/attributes. Despite the strengths of MaxDiff, some analysts would prefer data that represented more than just ... Read More
Traditional MaxDiff analysis leads to relative importance/preference scores. But, there is no possible way for respondents to express that (for example) all the items are important or none of the ... Read More
This paper compares different methods of obtaining individual-level scores for MaxDiff surveys at the individual level: Simple counting, individual-level logit, and HB. Key to the success for all ... Read More
In this paper, we create an artificial situation that demonstrates the relative scaling issue for MaxDiff at its worst. We collect a first wave of MaxDiff data on 30 items, and based on the items’ ... Read More
This article provides a case study regarding how MaxDiff and Cluster Ensemble analysis can be used to segment a population. Sawtooth Software conducted an online study among US respondents just prior ... Read More
The author (Orme) presents results from two studies testing a new procedure called Adaptive MaxDiff Scaling. Rather than focus equal attention on estimating respondents' preferences (or importances) ... Read More
The authors investigate how the number of items per MaxDiff set affects dropout rates, survey length, positional bias, parameter equivalence, and predictive validity. Three commercial studies are ... Read More
This paper communicates results of a Monte Carlo simulation study on how the precision of estimates for MaxDiff (best/worst) experiments is affected by: Number of items presented per set, Number of ... Read More
This article offers a case study demonstrating how best/worst scaling may be used for estimating the price sensitivity of automobile buyers to different car options, such as warranty, anti-lock ... Read More
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 ... Read More
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