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Article: The Value of “Bespoke”: Demand Learning, Preference Learning, and Customer Behavior

TitleThe Value of “Bespoke”: Demand Learning, Preference Learning, and Customer Behavior
Authors
Issue Date2018
PublisherINFORMS. The Journal's web site is located at http://mansci.pubs.informs.org
Citation
Management Science, 2018, v. 64 n. 7, p. 3129-3145 How to Cite?
Abstract“Bespoke,” or mass customization strategy, combines demand learning and preference learning. We develop an analytical framework to study the economic value of bespoke systems and investigate the interaction between demand learning and preference learning. We find that it is possible for demand learning and preference learning to be either complements or substitutes, depending on the customization cost and the demand uncertainty profile. They are generally complements when the personalization cost is low and the probability of having high demand is large. Contrary to usual belief, we show that higher demand uncertainty does not necessarily yield more complementarity benefits. Our numerical study shows that the complementarity benefit becomes weaker when customers are more strategic. Interestingly, the substitute loss can occur when the personalization cost is small and the probability of having high demand is large, when customers are strategic.
Persistent Identifierhttp://hdl.handle.net/10722/243221
ISSN
2017 Impact Factor: 3.544
2015 SCImago Journal Rankings: 4.384

 

DC FieldValueLanguage
dc.contributor.authorHuang, T-
dc.contributor.authorLiang, C-
dc.contributor.authorWang, J-
dc.date.accessioned2017-08-25T02:51:49Z-
dc.date.available2017-08-25T02:51:49Z-
dc.date.issued2018-
dc.identifier.citationManagement Science, 2018, v. 64 n. 7, p. 3129-3145-
dc.identifier.issn0025-1909-
dc.identifier.urihttp://hdl.handle.net/10722/243221-
dc.description.abstract“Bespoke,” or mass customization strategy, combines demand learning and preference learning. We develop an analytical framework to study the economic value of bespoke systems and investigate the interaction between demand learning and preference learning. We find that it is possible for demand learning and preference learning to be either complements or substitutes, depending on the customization cost and the demand uncertainty profile. They are generally complements when the personalization cost is low and the probability of having high demand is large. Contrary to usual belief, we show that higher demand uncertainty does not necessarily yield more complementarity benefits. Our numerical study shows that the complementarity benefit becomes weaker when customers are more strategic. Interestingly, the substitute loss can occur when the personalization cost is small and the probability of having high demand is large, when customers are strategic.-
dc.languageeng-
dc.publisherINFORMS. The Journal's web site is located at http://mansci.pubs.informs.org-
dc.relation.ispartofManagement Science-
dc.titleThe Value of “Bespoke”: Demand Learning, Preference Learning, and Customer Behavior-
dc.typeArticle-
dc.identifier.emailWang, J: jingqi@hku.hk-
dc.identifier.authorityWang, J=rp01778-
dc.description.naturepostprint-
dc.identifier.doi10.1287/mnsc.2017.2771-
dc.identifier.hkuros274209-
dc.identifier.hkuros289190-
dc.publisher.placeUnited States-

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