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Article: The Value of “Bespoke”: Demand Learning, Preference Learning, and Customer Behavior
Title | The Value of “Bespoke”: Demand Learning, Preference Learning, and Customer Behavior |
---|---|
Authors | |
Keywords | Customer behavior Customization Demand forecast Operations-marketing interface |
Issue Date | 2018 |
Publisher | INFORMS. 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 Identifier | http://hdl.handle.net/10722/243221 |
ISSN | 2023 Impact Factor: 4.6 2023 SCImago Journal Rankings: 5.438 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Huang, T | - |
dc.contributor.author | Liang, C | - |
dc.contributor.author | Wang, J | - |
dc.date.accessioned | 2017-08-25T02:51:49Z | - |
dc.date.available | 2017-08-25T02:51:49Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | Management Science, 2018, v. 64 n. 7, p. 3129-3145 | - |
dc.identifier.issn | 0025-1909 | - |
dc.identifier.uri | http://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.language | eng | - |
dc.publisher | INFORMS. The Journal's web site is located at http://mansci.pubs.informs.org | - |
dc.relation.ispartof | Management Science | - |
dc.subject | Customer behavior | - |
dc.subject | Customization | - |
dc.subject | Demand forecast | - |
dc.subject | Operations-marketing interface | - |
dc.title | The Value of “Bespoke”: Demand Learning, Preference Learning, and Customer Behavior | - |
dc.type | Article | - |
dc.identifier.email | Wang, J: jingqi@hku.hk | - |
dc.identifier.authority | Wang, J=rp01778 | - |
dc.description.nature | postprint | - |
dc.identifier.doi | 10.1287/mnsc.2017.2771 | - |
dc.identifier.scopus | eid_2-s2.0-85029318735 | - |
dc.identifier.hkuros | 274209 | - |
dc.identifier.hkuros | 289190 | - |
dc.identifier.isi | WOS:000440920900009 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 0025-1909 | - |