Eliciting Consumer Preferences Using Robust Adaptive Choice Questionnaires
| Autor: | Theodoros Evgeniou, Olivier Toubia, Jacob Abernethy, Jean-Philippe Vert |
|---|---|
| Rok vydání: | 2008 |
| Předmět: |
Computer science
business.industry Machine learning computer.software_genre Knowledge acquisition Computer Science Applications Personalization Support vector machine Market research Computational Theory and Mathematics Robustness (computer science) Statistical learning theory Artificial intelligence Data mining business computer Information Systems |
| Zdroj: | IEEE Transactions on Knowledge and Data Engineering. 20:145-155 |
| ISSN: | 1041-4347 |
| DOI: | 10.1109/tkde.2007.190632 |
| Popis: | We propose a framework for designing adaptive choice-based conjoint questionnaires that are robust to response error. It is developed based on a combination of experimental design and statistical learning theory principles. We implement and test a specific case of this framework using Regularization Networks. We also formalize within this framework the polyhedral methods recently proposed in marketing. We use simulations as well as an online market research experiment with 500 participants to compare the proposed method to benchmark methods. Both experiments show that the proposed adaptive questionnaires outperform existing ones in most cases. This work also indicates the potential of using machine learning methods in marketing. |
| Databáze: | OpenAIRE |
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