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dc.contributor.authorZhang, Jonathan Z.en_US
dc.contributor.authorWatson IV, George F.en_US
dc.contributor.authorPalmatier, Robert W.en_US
dc.contributor.authorDant, Rajiv P.en_US
dc.date.accessioned2017-05-29T12:34:48Z
dc.date.available2017-05-29T12:34:48Z
dc.date.issued2016en_US
dc.identifier.issn0022-2429en_US
dc.identifier.doi10.1509/jm.15.0066en_US
dc.identifier.urihttp://hdl.handle.net/10072/337606
dc.description.abstractFirms routinely engage in relationship marketing (RM) efforts to improve their relationships with business partners, and extant research has documented the effectiveness of various RM strategies. According to the perspective proposed in this article, as customers migrate through different relationship states over time, not all RM strategies are equally effective, so it is possible to identify the most effective RM strategies given customers’ states. The authors apply a multivariate hidden Markov model to a six-year longitudinal data set of 552 business-to-business relationships maintained by a Fortune 500 firm. The analysis identifies four latent buyer–seller relationship states, according to each customer’s level of commitment, trust, dependence, and relational norms, and it parsimoniously captures customers’ migration across relationship states through three positive (exploration, endowment, recovery) and two negative (neglect, betrayal) migration mechanisms. The most effective RM strategies across migration paths can help firms promote customer migration to higher performance states and prevent deterioration to poorer ones. A counterfactual elasticity analysis compares the relative importance of different migration strategies at various relationship stages. This research thus moves beyond extant RM literature by focusing on the differential effectiveness of RM strategies across relationship states, and it provides managerial guidance regarding efficient, dynamic resource allocations.en_US
dc.description.peerreviewedYesen_US
dc.languageEnglishen_US
dc.publisherAmerican Marketing Associationen_US
dc.relation.ispartofpagefrom53en_US
dc.relation.ispartofpageto75en_US
dc.relation.ispartofissue5en_US
dc.relation.ispartofjournalJournal of Marketingen_US
dc.relation.ispartofvolume80en_US
dc.subject.fieldofresearchMarketing not elsewhere classifieden_US
dc.subject.fieldofresearchcode150599en_US
dc.titleDynamic Relationship Marketingen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Peer Reviewed (HERDC)en_US
dc.type.codeC - Journal Articlesen_US
dc.description.versionPublisheden_US
gro.rights.copyright© 2016 American Marketing Association. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.en_US
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