Choice-Based Conjoint (CBC) Workshop
by Peter Kurz and Winfried Steiner
Haus der bayerischen Landwirtschaft Herrsching
Rieder Str. 70, 82211 Herrsching am Ammersee
|Start:||Tuesday,||18 Sep 2018||09:00|
|End:||Friday,||21 Sep 2018||16:00|
This four-day workshop introduces participants to the state-of-the-art as well as to advanced topics in choice-based conjoint (CBC) analysis. Days 1 and 2 provide a profound overview of all basic data collection and data analysis steps in order to conduct a CBC study, like questionnaire design, constructing efficient CBC designs, and estimating utilities using logit, latent class and Hierarchical Bayes models. Day 3 provides guidelines for market simulations based on estimated conjoint utilities, and discusses pros and cons of related choice rules. Day 4 extends the simulation and introduces heuristics for optimal new product (line) design, and further focuses on pricing issues in CBC studies. All contents are illustrated with examples and exercises, and participants will learn how to apply the CBC approach by means of the Sawtooth software. Participants will further have the opportunity to deepen their understanding with an additional practice study at the end of each day.
The workshop will address all pressing questions concerning the design of a CBC study as well as recent methodical developments for analyzing CBC data, including:
Participants will receive a 30-days fully functional version of the Sawtooth software modules used in the workshop (Lighthouse Studio, Latent class, CBC/HB, ASM).
- how to set critical parameters like the number of attributes per choice set, the number of alternatives per choice set, the number of choice sets per respondent, and the number of respondents,
- how to assess criteria that affect the efficiency of a CBC design (orthogonality, level overlap, level balance, utility balance), whether to choose fixed versus randomized tasks, when to focus on main effects versus interaction effects,
- how to estimate segment-specific utilities using the latent class approach versus individual utilities using an Hierarchical Bayes approach, and how to evaluate model performances from a statistical and managerial point of view,
- how and when to use which choice rules for market simulation (first choice, logit choice, randomized first choice, random draws),
- how to optimize product portfolios in market simulations using heuristics or other optimization techniques,
- how to handle specific interaction- and cross-effects with alternative-specific designs (ASD − the real discrete choice models),
- how to build optimal conjoint choice models when "price" is the main focus (e.g. price-only choice models vs. adding non-price attributes),
- how to deal with the problem of price reversals (e.g. coding options, price constraints, tie draws),
- how to derive (cross) price response functions from conjoint choice models.