Application of Support Vector Machines in Evaluating the Internationalization Success of Companies

The internationalization started to be seen as an opportunity for many companies. This is one of the most crucial growth strategies for companies. Internationalization can be defined as a corporative strategy for growing through foreign markets. It can enhance the product lifetime and improve produc...

Descripción completa

Detalles Bibliográficos
Autores: Rustam, Z, Yaurita, F, Segovia Vargas, María Jesús
Tipo de recurso: artículo
Fecha de publicación:2018
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/19037
Acceso en línea:https://hdl.handle.net/20.500.14352/19037
Access Level:acceso abierto
Palabra clave:Contabilidad (Economía)
Empresas
Mercados bursátiles y financieros
5303 Contabilidad Económica
5311 Organización y Dirección de Empresas
id ES_f11c4bef01da825bcc0ff1ca4e1f04c0
oai_identifier_str oai:docta.ucm.es:20.500.14352/19037
network_acronym_str ES
network_name_str España
repository_id_str
spelling Application of Support Vector Machines in Evaluating the Internationalization Success of CompaniesRustam, ZYaurita, FSegovia Vargas, María JesúsContabilidad (Economía)EmpresasMercados bursátiles y financieros5303 Contabilidad Económica5311 Organización y Dirección de EmpresasThe internationalization started to be seen as an opportunity for many companies. This is one of the most crucial growth strategies for companies. Internationalization can be defined as a corporative strategy for growing through foreign markets. It can enhance the product lifetime and improve productivity and business efficiency. However, there is no general model for a successful international company. Therefore, the success of an internationalization procedure must be estimated based on different variables such as the status, strategy, and market characteristics of the company. In this paper, we try to build a model in evaluating the internationalization success of a company based on existing past data by using Support Vector Machines. The results are very encouraging and show that Support Vector Machines can be a useful tool in this sector. We found that Support Vector Machines achieved 81.36% accuracy rate with RBF Kernel, 80% training set, andInstitute of Physics PublishingUniversidad Complutense de Madrid20182018-01-0120182018-01-01journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/20.500.14352/19037reponame:Docta Complutenseinstname:Universidad Complutense de Madrid (UCM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Atribución 3.0 Españahttps://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccessoai:docta.ucm.es:20.500.14352/190372026-06-02T12:44:21Z
dc.title.none.fl_str_mv Application of Support Vector Machines in Evaluating the Internationalization Success of Companies
title Application of Support Vector Machines in Evaluating the Internationalization Success of Companies
spellingShingle Application of Support Vector Machines in Evaluating the Internationalization Success of Companies
Rustam, Z
Contabilidad (Economía)
Empresas
Mercados bursátiles y financieros
5303 Contabilidad Económica
5311 Organización y Dirección de Empresas
title_short Application of Support Vector Machines in Evaluating the Internationalization Success of Companies
title_full Application of Support Vector Machines in Evaluating the Internationalization Success of Companies
title_fullStr Application of Support Vector Machines in Evaluating the Internationalization Success of Companies
title_full_unstemmed Application of Support Vector Machines in Evaluating the Internationalization Success of Companies
title_sort Application of Support Vector Machines in Evaluating the Internationalization Success of Companies
dc.creator.none.fl_str_mv Rustam, Z
Yaurita, F
Segovia Vargas, María Jesús
author Rustam, Z
author_facet Rustam, Z
Yaurita, F
Segovia Vargas, María Jesús
author_role author
author2 Yaurita, F
Segovia Vargas, María Jesús
author2_role author
author
dc.contributor.none.fl_str_mv Universidad Complutense de Madrid
dc.subject.none.fl_str_mv Contabilidad (Economía)
Empresas
Mercados bursátiles y financieros
5303 Contabilidad Económica
5311 Organización y Dirección de Empresas
topic Contabilidad (Economía)
Empresas
Mercados bursátiles y financieros
5303 Contabilidad Económica
5311 Organización y Dirección de Empresas
description The internationalization started to be seen as an opportunity for many companies. This is one of the most crucial growth strategies for companies. Internationalization can be defined as a corporative strategy for growing through foreign markets. It can enhance the product lifetime and improve productivity and business efficiency. However, there is no general model for a successful international company. Therefore, the success of an internationalization procedure must be estimated based on different variables such as the status, strategy, and market characteristics of the company. In this paper, we try to build a model in evaluating the internationalization success of a company based on existing past data by using Support Vector Machines. The results are very encouraging and show that Support Vector Machines can be a useful tool in this sector. We found that Support Vector Machines achieved 81.36% accuracy rate with RBF Kernel, 80% training set, and
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-01-01
2018
2018-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14352/19037
url https://hdl.handle.net/20.500.14352/19037
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Atribución 3.0 España
https://creativecommons.org/licenses/by/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Atribución 3.0 España
https://creativecommons.org/licenses/by/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Institute of Physics Publishing
publisher.none.fl_str_mv Institute of Physics Publishing
dc.source.none.fl_str_mv reponame:Docta Complutense
instname:Universidad Complutense de Madrid (UCM)
instname_str Universidad Complutense de Madrid (UCM)
reponame_str Docta Complutense
collection Docta Complutense
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869424097583169536
score 15,300724

Similares en LA Referencia