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dc.creatorMoreno Moreno, Antonio Manueles
dc.creatorSanchís Pedregosa, Carloses
dc.creatorBerenguer, Emmaes
dc.date.accessioned2020-04-03T09:03:15Z
dc.date.available2020-04-03T09:03:15Z
dc.date.issued2019
dc.identifier.citationMoreno Moreno, A.M., Sanchís Pedregosa, C. y Berenguer, E. (2019). Success Factors in Peer-to-Business (P2B) Crowdlending: A Predictive Approach. IEEE Access, 7, 148586-148593.
dc.identifier.issn2169-3536es
dc.identifier.urihttps://hdl.handle.net/11441/94870
dc.description.abstractPeer-to-Business (P2B) crowdlending is gaining importance among companies seeking funding. However, not all projects get the same take-up by the crowd. Thus, this study aims to determine the key factors that drive non-professional investors to choose a given loan in an online environment. To this purpose, we have analyzed 243 crowdlending campaigns on October.eu platform. We have obtained a series of variables from the analyzed loans using logistic regression. Results indicate that loan amount, loan term and overall credit rating are the key predictors of non-professional lender P2B crowdlending success. These findings may be useful for predicting whether the crowd will subscribe to a loan request or not. This information would help businesses to modify specific loan characteristics (if possible) to make their loans more attractive or could even lead companies to consider a different financial option. It could also help platforms select and adapt project parameters to secure their success.es
dc.formatapplication/pdfes
dc.format.extent8es
dc.language.isoenges
dc.publisherIEEEes
dc.relation.ispartofIEEE Access, 7, 148586-148593.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectCrowdfundinges
dc.subjectCrowdlendinges
dc.subjectInstitutional lenderses
dc.subjectLogistic regressiones
dc.subjectNon-professional lenderses
dc.subjectPeer-to-business (P2B)es
dc.titleSuccess Factors in Peer-to-Business (P2B) Crowdlending: A Predictive Approaches
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Economía Financiera y Dirección de Operacioneses
dc.relation.publisherversionhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8864063es
dc.identifier.doi10.1109/ACCESS.2019.2946858es
dc.journaltitleIEEE Accesses
dc.publication.volumen7es
dc.publication.initialPage148586es
dc.publication.endPage148593es

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