Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/58368
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dc.contributor.authorDuraya Sukthomyaen_US
dc.contributor.authorWimalin Laosiritawornen_US
dc.date.accessioned2018-09-05T04:23:12Z-
dc.date.available2018-09-05T04:23:12Z-
dc.date.issued2018-04-06en_US
dc.identifier.other2-s2.0-85050486814en_US
dc.identifier.other10.1109/ICITM.2018.8333949en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85050486814&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/58368-
dc.description.abstract© 2018 IEEE. Corporate social responsibility (CSR) is an important issue for organization due to the increasing attention of the firm responsibility to their stakeholders. Most of the literature in this area attempt to use statistical method to investigate the relationship of CSR to various firm performance indexes such as stock price, cost of capital, and return on asset. However, most of the works have low adjusted R square value due to the complexity of problem which leads to validity of the conclusion derived from that model. This paper presents the application of artificial neural network (ANN), one of the machine learning tools capable of modeling complex and non-linear relationship between variables. In this work, data from Thai companies listed in Market for Alternative Investment (mai) were used to train ANN. The trained ANN achieved significantly high adjusted R square value comparing with the statistical method.en_US
dc.subjectBusiness, Management and Accountingen_US
dc.subjectEngineeringen_US
dc.titleModeling of the relationship between corporate social responsibility and stock price with artificial neural networken_US
dc.typeConference Proceedingen_US
article.title.sourcetitle2018 7th International Conference on Industrial Technology and Management, ICITM 2018en_US
article.volume2018-Januaryen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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