2298. Computing Nash equilibria for product design based on hierarchical Bayesian mixed logit models
Invited abstract in session TD-47: Consumer Demand and Marketing I, stream Retail Operations.
Tuesday, 14:30-16:00Room: Parkinson B08
Authors (first author is the speaker)
| 1. | Jan Dressler
|
| Marketing, Clausthal University of Technology, Institute of Management and Economics | |
| 2. | Peter Kurz
|
| bms – marketing research + strategy GmbH | |
| 3. | Winfried Steiner
|
| Marketing, Clausthal University of Technology, Institute of Management and Economics |
Abstract
Over the past few decades, choice-based conjoint analysis has become an
indispensable technique for the elicitation of consumer preferences, serving as the foundation for product design and assortment optimization in marketing and retailing. Despite a substantial body of theoretical and empirical research, there has actually been little effort in this field devoted to exploring subsequent reactions of competitors based on non-cooperative game theory, although manufacturers and retailers are increasingly interested in market equilibria to support managerial decisions. Only a fraction of the existing frameworks considered competition on both price and design, none of which accounted for Bayesian hyperparameter uncertainty, let alone under different choice rules.
In order to close this research gap, we developed a comprehensive system for conjoint-based game-theoretic simulation, ranging from utility generation, through choice design and Bayesian model estimation, to Nash equilibrium computation. After analyzing numerous equilibria build upon actual retail prices and costs of notebooks, we found that a deterministic choice rule generally led to equilibria with lower prices and profits but at the same time demonstrated a much greater stability in prices across various levels of preference heterogeneity and disturbance. This is crucial, as price was the main driver of profits, and held true even when Bayesian posterior means were employed instead of draws.
Keywords
- Marketing
- Game Theory
- Simulation
Status: accepted
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