Latent Class MNL is a utility estimation approach that finds groups (segments) of respondents who have similar preferences as captured via CBC or MaxDiff experiments. Latent Class MNL simultaneously ... Read More
Increasingly, stated preference choice projects involve Menu-Based Choice scenarios (MBC) where respondents can select one to multiple options from a menu. This is not surprising, given the fact that ... Read More
The Advanced Simulation Module (ASM) extends the capabilities of the standard Windows-based market simulator to enable product optimization searches, based on the criteria of utility, share, purchase ... Read More
Choice-Based Conjoint Analysis (CBC) is an integrated component within the Lighthouse Studio platform for conducting choice-based conjoint studies. The main characteristic distinguishing choice-based ... Read More
Adaptive Choice-Based Conjoint (ACBC) is a new approach for adaptive choice-based conjoint studies. The interview has three main phases: 1) BYO (configuration) phase, 2) Consideration phase, 3) ... Read More
Hierarchical Bayes is an advanced technique for computing individual- level estimates of regression coefficients or part worths. HB has been described favorably in numerous journal articles. Its ... 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
Hierarchical Bayes is an advanced technique for computing individual- level part worths from CBC data. HB has been described favorably in numerous journal articles. Its strongest point of ... Read More
Some CBC projects do not fit the traditional mold (full-profile, common attributes, limited attributes and levels). The Advanced Design Module (ADM) for CBC gives the researcher additional ... Read More
Convergent Cluster & Ensemble Analysis (CCEA) is software for doing cluster and cluster ensemble analysis. CCEA uses k-means as its standard cluster algorithm. However, the newer Ensemble Analysis ... Read More
Adaptive Conjoint Analysis (ACA) is software for conjoint (trade-off) analysis. The term "adaptive" refers to the fact that the computer-administered interview is customized for each respondent. Data ... Read More
Hierarchical Bayes is an advanced technique that can be used in estimating part worths for conjoint analysis experiments. HB has been described favorably in many journal articles. Its strongest point ... Read More
Conjoint Value Analysis (CVA) is an integrated component within our SSI Web platform for full-profile conjoint analysis. The CVA technique (ratings-based or card-sort conjoint) is a classic technique ... Read More
Hierarchical Bayes is a relatively new technique for computing individual- level part worths from conjoint data. HB has been described favorably in several recent journal articles. Its strongest ... Read More
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