The book covers all recent developments in Conjoint Analysis. Leading scientists present theory and applications of this technique. In short, the following models, techniques, and applications are discussed: normative models that maximize return, extension of choice-based conjoint simulations, latent class, hierarchical Bayes modelling, new choice simulators, normative models for representing competitive actions and reactions (based on game theory), applications in diverse areas, computation of monetary equivalents of part worth, share/return optimisation (including Pareto frontier analysis), coupling of conjoint analysis with the perceptual and preference mapping of choice simulator results.

Latest developments in conjoint analysis which is the most important multivariate technique in marketing Covers all hot topics in the field Includes supplementary material: sn.pub/extras

Autorentext
Prof. Dr. Frank Huber ist Inhaber des Lehrstuhls für Betriebswirtschaftslehre, insbesondere Marketing der Universität Mainz. Professor Dr. Andreas Herrmann ist Inhaber des Lehrstuhls für Allgemeine Betriebswirtschaftslehre und Marketing an der Johannes-Gutenberg Universität Mainz.

Inhalt
Conjoint Analysis as an Instrument of Market Research Practice.- Measurement of Price Effects with Conjoint Analysis: Separating Informational and Allocative Effects of Price.- Market Simulation Using a Probabilistic Ideal Vector Model for Conjoint Data.- A Comparison of Conjoint Measurement with Self-Explicated Approaches.- Non-geometric Plackett-Burman Designs in Conjoint Analysis.- On the Influence of the Evaluation Methods in Conjoint Design - Some Empirical Results.- Evolutionary Conjoint.- The Value of Extent-of-Preference Information in Choice-Based Conjoint Analysis.- A Multi-trait Multi-method Validity Test of Partworth Estimates.- Conjoint Preference Elicitation Methods in the Broader Context of Random Utility Theory Preference Elicitation Methods.- Conjoint Choice Experiments: General Characteristics and Alternative Model Specifications.- Optimization-Based and Machine-Learning Methods for Conjoint Analysis: Estimation and Question Design.- The Combinatorial Structure of Polyhedral Choice Based Conjoint Analysis.- Using Conjoint Choice Experiments to Model Consumer Choices of Product Component Packages.- Latent Class Models for Conjoint Analysis.- A Generalized Normative Segmentation Methodology Employing Conjoint Analysis.- Dealing with Product Similarity in Conjoint Simulations.- Sales Forecasting with Conjoint Analysis by Addressing Its Key Assumptions with Sequential Game Theory and Macro-Flow Modeling.