dc.contributor.author | Dabrowski, Maciej | en |
dc.contributor.author | Acton, Thomas | en |
dc.date.accessioned | 2010-12-10T13:24:08Z | en |
dc.date.available | 2010-12-10T13:24:08Z | en |
dc.date.issued | 2010-09-01 | en |
dc.identifier.citation | Dabrowski, M. and T. Acton (2010). Comparing techniques for preference relaxation: a decision theory perspective 11th International Conference on Electronic Commerce and Web Technologies (EC-Web 2010). Bilbao, Spain. | en |
dc.identifier.isbn | 3642152074 | en |
dc.identifier.isbn | 9783642152078 | en |
dc.identifier.uri | http://hdl.handle.net/10379/1512 | en |
dc.description.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 ltering
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. | en |
dc.format | application/pdf | en |
dc.language.iso | en | en |
dc.publisher | Springer | en |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Ireland | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/3.0/ie/ | |
dc.subject | Decision theory | en |
dc.subject | Recommender systems | en |
dc.subject | Preference relaxation | en |
dc.subject | eCommerce | en |
dc.subject | Enterprise Agility | en |
dc.title | Comparing techniques for preference relaxation: a decision theory perspective | en |
dc.type | Conference Paper | en |
dc.description.peer-reviewed | peer-reviewed | en |
dc.contributor.funder | Science Foundation Ireland - Grant No. SFI/08/CE/I1380 (Lion-2) | en |
nui.item.downloads | 435 | |