A Low-Effort Recommendation System with High Accuracy
In recent studies on recommendation systems, the choice-based conjoint analysis has been suggested as a method for measuring consumer preferences. This approach achieves high recommendation accuracy and does not suffer from the start-up problem because it is also applicable for recommendations for new consumers or of new products. However, this method requires massive consumer input, which causes consumer reluctance. In a simulation study, we demonstrate the high accuracy, but also the high user’s effort for using a utility-based recommendation system using a choice-based conjoint analysis with hierarchical Bayes estimation. In order to reduce the conflict between consumer effort and recommendation accuracy, we develop a novel approach that only shows Pareto-efficient alternatives and ranks them according to the number of dominated attributes. We demonstrate that, in terms of the decision accuracy of the recommended products, the ranked Pareto-front approach performs better than a recommendation system that employs choice-based conjoint analysis. Furthermore, the consumer’s effort is kept low and comparable to that of simple systems that require little consumer input. Copyright Springer Fachmedien Wiesbaden 2013
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 5 (2013)
Issue (Month): 6 (December)
|Contact details of provider:|| Web page: http://www.springer.com/economics/journal/12599|
|Order Information:||Web: http://link.springer.de/orders.htm|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Hey, John D., 1982. "Search for rules for search," Journal of Economic Behavior & Organization, Elsevier, vol. 3(1), pages 65-81, March.
- Marcel Fritz & Christian Schlereth & Stefan Figge, 2011. "Empirical Evaluation of Fair Use Flat Rate Strategies for Mobile Internet," Business & Information Systems Engineering, Springer, vol. 3(5), pages 269-277, October.
- Loomes, Graham & Sugden, Robert, 1982. "Regret Theory: An Alternative Theory of Rational Choice under Uncertainty," Economic Journal, Royal Economic Society, vol. 92(368), pages 805-24, December.
- Jyrki Wallenius & James S. Dyer & Peter C. Fishburn & Ralph E. Steuer & Stanley Zionts & Kalyanmoy Deb, 2008. "Multiple Criteria Decision Making, Multiattribute Utility Theory: Recent Accomplishments and What Lies Ahead," Management Science, INFORMS, vol. 54(7), pages 1336-1349, July.
- Christian Schlereth & Christine Eckert & Bernd Skiera, 2012. "Using discrete choice experiments to estimate willingness-to-pay intervals," Marketing Letters, Springer, vol. 23(3), pages 761-776, September.
- Stanley F. Biggs & Jean C. Bedard & Brian G. Gaber & Thomas J. Linsmeier, 1985. "The Effects of Task Size and Similarity on the Decision Behavior of Bank Loan Officers," Management Science, INFORMS, vol. 31(8), pages 970-987, August.
- Gerald Häubl & Valerie Trifts, 2000. "Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids," Marketing Science, INFORMS, vol. 19(1), pages 4-21, May.
- Oliver Hinz & Jochen Eckert, 2010. "The Impact of Search and Recommendation Systems on Sales in Electronic Commerce," Business & Information Systems Engineering, Springer, vol. 2(2), pages 67-77, April.
- Gensler, Sonja & Hinz, Oliver & Skiera, Bernd & Theysohn, Sven, 2012. "Willingness-to-pay estimation with choice-based conjoint analysis: Addressing extreme response behavior with individually adapted designs," European Journal of Operational Research, Elsevier, vol. 219(2), pages 368-378.
- Eric J. Johnson & John W. Payne, 1985. "Effort and Accuracy in Choice," Management Science, INFORMS, vol. 31(4), pages 395-414, April.
- Michael Yee & Ely Dahan & John R. Hauser & James Orlin, 2007. "Greedoid-Based Noncompensatory Inference," Marketing Science, INFORMS, vol. 26(4), pages 532-549, 07-08.
- Butler, John C. & Dyer, James S. & Jia, Jianmin & Tomak, Kerem, 2008. "Enabling e-transactions with multi-attribute preference models," European Journal of Operational Research, Elsevier, vol. 186(2), pages 748-765, April.
- John Butler & Douglas J. Morrice & Peter W. Mullarkey, 2001. "A Multiple Attribute Utility Theory Approach to Ranking and Selection," Management Science, INFORMS, vol. 47(6), pages 800-816, June.
- Arnaud De Bruyn & John C. Liechty & Eelko K. R. E. Huizingh & Gary L. Lilien, 2008. "Offering Online Recommendations with Minimum Customer Input Through Conjoint-Based Decision Aids," Marketing Science, INFORMS, vol. 27(3), pages 443-460, 05-06.
- Lohse, Gerald L. & Johnson, Eric J., 1996. "A Comparison of Two Process Tracing Methods for Choice Tasks," Organizational Behavior and Human Decision Processes, Elsevier, vol. 68(1), pages 28-43, October.
- Denzil G. Fiebig & Michael P. Keane & Jordan Louviere & Nada Wasi, 2010. "The Generalized Multinomial Logit Model: Accounting for Scale and Coefficient Heterogeneity," Marketing Science, INFORMS, vol. 29(3), pages 393-421, 05-06.
- Hoyer, Wayne D, 1984. " An Examination of Consumer Decision Making for a Common Repeat Purchase Product," Journal of Consumer Research, University of Chicago Press, vol. 11(3), pages 822-29, December.
When requesting a correction, please mention this item's handle: RePEc:spr:binfse:v:5:y:2013:i:6:p:397-408. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Guenther Eichhorn)or (Christopher F Baum)
If references are entirely missing, you can add them using this form.