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Web Data Mining for Monitoring Business Export Orientation

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Web Data Mining for Monitoring Business Export Orientation

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dc.contributor.author Blazquez, Desamparados es_ES
dc.contributor.author Domenech, Josep es_ES
dc.date.accessioned 2018-07-16T06:58:17Z
dc.date.available 2018-07-16T06:58:17Z
dc.date.issued 2018 es_ES
dc.identifier.issn 2029-4913 es_ES
dc.identifier.uri http://hdl.handle.net/10251/105859
dc.description.abstract [EN] The World Wide Web (WWW) has become the largest repository of information in the world, providing a data stream that grows at the same time as the scope of the Internet does in society. As with most Information and Communication Technologies (ICTs), its digital nature makes it easy for computer programs to analyze it and discover information. This is why it is being increas­ingly explored as a source of new indicators of technology, economics and development. Web-based indicators can be made available on a real-time basis, unlike delayed official data releases. In this paper, we examine the viability of monitoring firm export orientation from automatically retrieved web variables. Our focus on exports is consistent with the role of internationalization in economic development. To evaluate our approach, we first checked to what extent web variables are capable of predicting firm export orientation. Once these new variables are validated, their automated re­trieval is assessed by comparing the predictive performance of two nowcast models: one considering the manually retrieved web variables, the other considering the automatically retrieved ones. Our results evidence that i) web-based variables are good predictors for firm export orientation, and ii) the process of extracting and analyzing such variables can be entirely automated with no significant loss of performance. This way, it is possible to nowcast not only the export orientation of a firm, but also of an economic sector or of a region. es_ES
dc.description.sponsorship This work has been partially supported by the Spanish Ministry of Economy and Competitiveness under grant TIN2013-43913-R, and the Spanish Ministry of Education under grant FPU14/02386. en_EN
dc.language Inglés es_ES
dc.publisher Vilnius Gediminas Technical University es_ES
dc.relation.ispartof Technological and Economic Development of Economy es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Automatic indicators es_ES
dc.subject Big Data es_ES
dc.subject Corporate websites es_ES
dc.subject Export es_ES
dc.subject Monitoring es_ES
dc.subject Nowcasting es_ES
dc.subject Web data mining es_ES
dc.subject.classification ECONOMIA APLICADA es_ES
dc.subject.classification ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES es_ES
dc.title Web Data Mining for Monitoring Business Export Orientation es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3846/20294913.2016.1213193 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MECD//FPU2014-02386/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2013-43913-R/ES/EFICIENCIA ECONOMICA EN LA PLANIFICACION Y USO DE INFRAESTRUCTURAS CLOUD/ es_ES
dc.rights.accessRights Abierto es_ES
dc.date.embargoEndDate 2019-09-20 es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Economía y Ciencias Sociales - Departament d'Economia i Ciències Socials es_ES
dc.description.bibliographicCitation Blazquez, D.; Domenech, J. (2018). Web Data Mining for Monitoring Business Export Orientation. Technological and Economic Development of Economy. 24(2):406-428. https://doi.org/10.3846/20294913.2016.1213193 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3846/20294913.2016.1213193 es_ES
dc.description.upvformatpinicio 406 es_ES
dc.description.upvformatpfin 428 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 24 es_ES
dc.description.issue 2 es_ES
dc.relation.pasarela S\325758 es_ES
dc.contributor.funder Ministerio de Educación, Cultura y Deporte es_ES
dc.contributor.funder Ministerio de Economía, Industria y Competitividad es_ES


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