R&D Indicators of a Firm as Predictors for Predicting Firm Performance
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Shin, Young Geun | - |
dc.contributor.author | Park, Sang Sung | - |
dc.contributor.author | Jang, Dong Sik | - |
dc.date.accessioned | 2021-09-06T22:46:45Z | - |
dc.date.available | 2021-09-06T22:46:45Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2012-02 | - |
dc.identifier.issn | 1343-4500 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/109021 | - |
dc.description.abstract | To more accurately predict firms' future performance, this study considers a set of influential variables that can affect firms' performance by using three methods based on the Bayesian technique. Then we verify the usefulness of the selected variables by using models based on Neural Networks and the Support Vector Machine technique. The results indicate that for more accurate predictions of firms' future performance, various indicators of R&D performance should be considered in conjunction with financial indicators. Thus, this study contributes to literatures by proposing a model that can better predict firms' future performance and reduce the risk associated with investment. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | INT INFORMATION INST | - |
dc.subject | PATENTS | - |
dc.subject | OUTPUT | - |
dc.title | R&D Indicators of a Firm as Predictors for Predicting Firm Performance | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Park, Sang Sung | - |
dc.contributor.affiliatedAuthor | Jang, Dong Sik | - |
dc.identifier.scopusid | 2-s2.0-84860114255 | - |
dc.identifier.wosid | 000302190200012 | - |
dc.identifier.bibliographicCitation | INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL, v.15, no.2, pp.577 - 596 | - |
dc.relation.isPartOf | INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL | - |
dc.citation.title | INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL | - |
dc.citation.volume | 15 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 577 | - |
dc.citation.endPage | 596 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Engineering, Multidisciplinary | - |
dc.subject.keywordPlus | PATENTS | - |
dc.subject.keywordPlus | OUTPUT | - |
dc.subject.keywordAuthor | R& | - |
dc.subject.keywordAuthor | D | - |
dc.subject.keywordAuthor | Patent | - |
dc.subject.keywordAuthor | Firm Performance | - |
dc.subject.keywordAuthor | Bayesian Technique | - |
dc.subject.keywordAuthor | NNs | - |
dc.subject.keywordAuthor | SVM | - |
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