Dynamic Models Incorporating Individual Heterogeneity: Utility Evolution in Conjoint Analysis

Marketing Science, Vol. 24, No. 2, pp. 285-293, 2005

Posted: 11 Jun 2016

See all articles by John Liechty

John Liechty

Pennsylvania State University, University Park

Duncan K. H. Fong

Pennsylvania State University

Wayne S. DeSarbo

Pennsylvania State University

Date Written: 2005

Abstract

It has been shown in the behavioral decision making, marketing research, and psychometric literature that the structure underlying preferences can change during the administration of repeated measurements (e.g., conjoint analysis) and data collection because of effects from learning, fatigue, boredom, and so on. In this research note, we propose a new class of hierarchical dynamic Bayesian models for capturing such dynamic effects in conjoint applications, which extend the standard hierarchical Bayesian random effects and existing dynamic Bayesian models by allowing for individual-level heterogeneity around an aggregate dynamic trend. Using simulated conjoint data, we explore the performance of these new dynamic models, incorporating individual-level heterogeneity across a number of possible types of dynamic effects, and demonstrate the derived benefits versus static models. In addition, we introduce the idea of an unbiased dynamic estimate, and demonstrate that using a counterbalanced design is important from an estimation perspective when parameter dynamics are present.

Keywords: heterogeneity, empirical utility functions, dynamic models, Bayesian analysis, conjoint analysis, unbiased dynamic estimates

Suggested Citation

Liechty, John and Fong, Duncan K. H. and DeSarbo, Wayne S., Dynamic Models Incorporating Individual Heterogeneity: Utility Evolution in Conjoint Analysis (2005). Marketing Science, Vol. 24, No. 2, pp. 285-293, 2005, Available at SSRN: https://ssrn.com/abstract=2793318

John Liechty

Pennsylvania State University, University Park ( email )

University Park
State College, PA 16802
United States

Duncan K. H. Fong

Pennsylvania State University ( email )

308 armsby
university park, PA 16802
United States

Wayne S. DeSarbo (Contact Author)

Pennsylvania State University ( email )

University Park
State College, PA 16802
United States

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