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A configuration-based recommender system for supporting e-commerce decisions

Scholz, Michael , Dorner, Verena, Schryen, Guido and Benlian, Alexander (2017) A configuration-based recommender system for supporting e-commerce decisions. European Journal of Operational Research 259 (1), pp. 205-215.

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Other URL: http://doi.org/10.1016/j.ejor.2016.09.057


Abstract

Multi-attribute value theory (MAVT)-based recommender systems have been proposed for dealing with issues of existing recommender systems, such as the cold-start problem and changing preferences. However, as we argue in this paper, existing MAVT-based methods for measuring attribute importance weights do not fit the shopping tasks for which recommender systems are typically used. These methods ...

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Item type:Article
Date:2017
Institutions:Business, Economics and Information Systems > Institut für Wirtschaftsinformatik
Business, Economics and Information Systems > Institut für Wirtschaftsinformatik > Professur für Wirtschaftsinformatik (Prof. Dr. Guido Schryen)
Identification Number:
ValueType
10.1016/j.ejor.2016.09.057DOI
Keywords:MULTIATTRIBUTE UTILITY MEASUREMENT; PROSPECT-THEORY; CONJOINT-ANALYSIS; MODELS; CHOICE; RANGE; CUSTOMIZATION; UNCERTAINTY; SENSITIVITY; HEURISTICS; E-commerce; Recommender system; Attribute weights; Configuration system; Decision support
Dewey Decimal Classification:300 Social sciences > 330 Economics
Status:Published
Refereed:Yes, this version has been refereed
Created at the University of Regensburg:Yes
Item ID:38996
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