Quotation Scholz, Michael, Dorner, Verena, Franz, Markus, Hinz, Oliver. 2015. Measuring consumers' willingness to pay with utility-based recommendation systems. Decision Support Systems (DSS). 72 60-71.


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Abstract

Our paper addresses two gaps in research on recommendation systems: first, leveraging them to predict consumers' willingness to pay; second, estimating non-linear utility functions – which are generally held to provide better approximations of consumers' preference structures than linear functions – at a reasonable level of cognitive consumer effort. We develop an approach to simultaneously estimate exponential utility functions and willingness to pay at a low level of cognitive consumer effort. The empirical evaluation of our new recommendation system's utility and willingness to pay estimates with the estimates of a system based on linear utility functions indicates that exponential utility functions are better suited for predicting optimal recommendation ranks for products. Linear utility functions perform better in estimating consumers' willingness to pay. Based on our experimental data set, we show how retailers can use these willingness to pay estimates for profit-maximizing pricing decisions.

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Publication's profile

Status of publication Published
Affiliation External
Type of publication Journal article
Journal Decision Support Systems (DSS)
Citation Index SCI
WU Journalrating 2009 A
WU-Journal-Rating new FIN-A, INF-A, MAR-A, STRAT-B, WH-B
Language English
Title Measuring consumers' willingness to pay with utility-based recommendation systems
Volume 72
Year 2015
Page from 60
Page to 71
Reviewed? Y
DOI https://doi.org/10.1016/j.dss.2015.02.006
Open Access N

Associations

People
Dorner, Verena (Details)
External
Franz, Markus (TU Darmstadt, Germany)
Hinz, Oliver (TU Darmstadt, Germany)
Scholz, Michael (University of Passau, Germany)
Organization
Institute for Digital Ecosystems IN (Details)
Research areas (ÖSTAT Classification 'Statistik Austria')
5367 Management information systems (Details)
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