A Direct Utility Model for Asymmetric Complements
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Sanghak | - |
dc.contributor.author | Kim, Jaehwan | - |
dc.contributor.author | Allenby, Greg M. | - |
dc.date.accessioned | 2021-09-06T01:47:10Z | - |
dc.date.available | 2021-09-06T01:47:10Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2013-05 | - |
dc.identifier.issn | 0732-2399 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/103293 | - |
dc.description.abstract | Asymmetric complements refer to goods where one good is more dependent on the other, yet consumers receive enhanced utility from consuming both. Examples include garden hoses and sprinklers, chips and dip, and routine versus personalized services where the former has a broader base for utility generation and the latter is more dependent on the other's presence. Measuring asymmetric effects is difficult when all that is observed are the purchase quantities present in a consumer's market basket. We propose a direct utility model with a latent decision sequence for measuring asymmetric effects that allows us to capture differential responses to cross-category purchases and inventories. Scanner panel data of milk and cereal purchases are used to investigate the presence of asymmetric complementarity, and implications are explored through counterfactual analyses involving cross-price elasticities and spillover effects of merchandising variables. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | INFORMS | - |
dc.subject | PRODUCT CATEGORIES | - |
dc.subject | PURCHASE INCIDENCE | - |
dc.subject | EMPIRICAL-ANALYSIS | - |
dc.subject | CHOICE | - |
dc.subject | BEHAVIOR | - |
dc.subject | SET | - |
dc.title | A Direct Utility Model for Asymmetric Complements | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Jaehwan | - |
dc.identifier.doi | 10.1287/mksc.2013.0782 | - |
dc.identifier.scopusid | 2-s2.0-84878254976 | - |
dc.identifier.wosid | 000319507300005 | - |
dc.identifier.bibliographicCitation | MARKETING SCIENCE, v.32, no.3, pp.454 - 470 | - |
dc.relation.isPartOf | MARKETING SCIENCE | - |
dc.citation.title | MARKETING SCIENCE | - |
dc.citation.volume | 32 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 454 | - |
dc.citation.endPage | 470 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | ssci | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Business & Economics | - |
dc.relation.journalWebOfScienceCategory | Business | - |
dc.subject.keywordPlus | PRODUCT CATEGORIES | - |
dc.subject.keywordPlus | PURCHASE INCIDENCE | - |
dc.subject.keywordPlus | EMPIRICAL-ANALYSIS | - |
dc.subject.keywordPlus | CHOICE | - |
dc.subject.keywordPlus | BEHAVIOR | - |
dc.subject.keywordPlus | SET | - |
dc.subject.keywordAuthor | utility theory | - |
dc.subject.keywordAuthor | choice modeling | - |
dc.subject.keywordAuthor | Bayesian estimation | - |
dc.subject.keywordAuthor | indivisible demand | - |
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