Comparing Techniques for Preference Relaxation: A Decision Theory Perspective

Abstract

This research proposes a decision aid based on a novel type of preference relaxation, which enables consumers to easily make quality choices in online multiattribute choice scenarios. In contrast to filtering and recommendation mechanisms that are a potential solution to this problem, our method combines decision theory with preference relaxation and enables consumers to consider high-quality alternatives they initially eliminated. We compare our approach with existing methods using a set of 2650 car advertisements gathered from a popular advertiser website. We discuss the potential impact of our method on decision quality and give an overview of implications for practitioners and researchers.

The performance of recommender systems in online shopping: A user-centric study

“…In the example above, a consumer using such a product search tool, and who provided preferences on price ($7000 to $8000) and mileage (25000mi to 75000mi) would be presented with a result set with only those offers that fully satisfy all the stated criteria, that is, are both within the price and mileage range. This approach is often referred to as product filtration using hard-constraints or logical filtering (Mirzadeh & Ricci, 2007) and has many limitations acknowledged in the literature (Dabrowski & Acton, 2010b;Felfernig, Mairitsch, Mandl, Schubert, & Teppan, 2009;Mirzadeh, Ricci, & Bansal, 2004), addressed with recommendation method, for example through preference relaxation.…”

“…non-dominated) from the decision-making perspective. Overall, we expected that the SBR methods should not impact decision effort, as previous studies suggest (Dabrowski et al, 2012;Dabrowski & Acton, 2010b) that the number of products included in the result set is similar to the levels in the logical filtering approach. We expect, however, that the amount of necessary effort for SBR will be significantly lower than in case of Standard Relaxation, hence:…”