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Setting B2B digital marketing in artificial intelligence-based CRMs: A review and directions for future research

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Setting B2B digital marketing in artificial intelligence-based CRMs: A review and directions for future research

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dc.contributor.author Saura, Jose Ramon es_ES
dc.contributor.author Ribeiro-Soriano, Domingo es_ES
dc.contributor.author Palacios Marqués, Daniel es_ES
dc.date.accessioned 2022-03-03T19:02:27Z
dc.date.available 2022-03-03T19:02:27Z
dc.date.issued 2021-10 es_ES
dc.identifier.issn 0019-8501 es_ES
dc.identifier.uri http://hdl.handle.net/10251/181222
dc.description.abstract [EN] The new business challenges in the B2B sector are determined by connected ecosystems, where data-driven decision making is crucial for successful strategies. At the same time, the use of digital marketing as a communication and sales channel has led to the need and use of Customer Relationship Management (CRM) systems to correctly manage company information. The understanding of B2B traditional Marketing strategies that use CRMs that work with Artificial Intelligence (AI) has been studied, however, research focused on the understanding and application of these technologies in B2B digital marketing is scarce. To cover this gap in the literature, this study develops a literature review on the main academic contributions in this area. To visualize the outcomes of the literature review, the results are then analyzed using a statistical approach known as Multiple Correspondence Analysis (MCA) under the homogeneity analysis of variance by means of alternating least squares (HOMALS) framework programmed in the R language. The research results classify the types of CRMs and their typologies and explore the main techniques and uses of AI-based CRMs in B2B digital marketing. In addition, a discussion, directions and propositions for future research are presented. es_ES
dc.description.sponsorship In gratitude to the Ministry of Science, Innovation and Universities and the European Regional Development Fund: RTI2018-096295-BC22. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Industrial Marketing Management es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject B2B digital marketing es_ES
dc.subject Artificial intelligence-based CRMs es_ES
dc.subject Multiple correspondence analysis es_ES
dc.subject R (Programming language) es_ES
dc.subject.classification ORGANIZACION DE EMPRESAS es_ES
dc.title Setting B2B digital marketing in artificial intelligence-based CRMs: A review and directions for future research es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.indmarman.2021.08.006 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-096295-B-C22/ES/DIGITALIZACION Y APLICACION DE NUEVOS MODELOS DE NEGOCIO Y GOBERNANZA A LA EMPRESA COLABORATIVA/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Organización de Empresas - Departament d'Organització d'Empreses es_ES
dc.description.bibliographicCitation Saura, JR.; Ribeiro-Soriano, D.; Palacios Marqués, D. (2021). Setting B2B digital marketing in artificial intelligence-based CRMs: A review and directions for future research. Industrial Marketing Management. 98:161-178. https://doi.org/10.1016/j.indmarman.2021.08.006 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.indmarman.2021.08.006 es_ES
dc.description.upvformatpinicio 161 es_ES
dc.description.upvformatpfin 178 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 98 es_ES
dc.relation.pasarela S\456032 es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES


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