A Fuzzy Logic Approach for Corporate Performance Evaluation

dc.authorscopusid57219902775
dc.authorscopusid56118641300
dc.authorscopusid6603658187
dc.contributor.authorTaşkan, Buşra
dc.contributor.authorKaratop, Buket
dc.contributor.authorKubat, Cemalettin
dc.date.accessioned2024-09-11T19:58:24Z
dc.date.available2024-09-11T19:58:24Z
dc.date.issued2024
dc.departmentİstanbul Gelişim Üniversitesien_US
dc.description12th International Symposium on Intelligent Manufacturing and Service Systems, IMSS 2023 -- 26 May 2023 through 28 May 2023 -- Istanbul -- 302369en_US
dc.description.abstractToday’s brutal competition environment has made it a necessity for businesses to evaluate their performance in order to maintain their existence and gain sustainable competitive advantage. The current environment does not allow businesses that do not perform performance evaluations a chance to survive. Therefore, corporate performance evaluation is a multi-criteria, complex and uncertain real-life problem that is vital for businesses. Corporate performance should be measured multi-dimensionally, but performance indicators of these dimensions may not always be expressed with a numerical value or may have uncertainty. In this case, the closest results are obtained by using fuzzy logic. Based on the current importance of the subject, a fuzzy model has been developed for the evaluation of corporate performance in this study. The outputs of the model are total enterprise performance, corporate reputation and financial output. Although the number of inputs used for each output varies, the inputs used in the model are the environment, customers, society, government, competitors, suppliers, business processes and sustainability. The application of the model is demonstrated with a case study using the fuzzy logic toolbox of the MATLAB program. Performance values for “Total Enterprise Performance”, “Corporate Reputation” and “Financial Output” were obtained as 16.9, 16.9 and 20.8, respectively. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.en_US
dc.identifier.doi10.1007/978-981-99-6062-0_69
dc.identifier.endpage743en_US
dc.identifier.isbn978-981996061-3en_US
dc.identifier.issn2195-4356en_US
dc.identifier.scopus2-s2.0-85174587511en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.startpage733en_US
dc.identifier.urihttps://doi.org/10.1007/978-981-99-6062-0_69
dc.identifier.urihttps://hdl.handle.net/11363/8464
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.relation.ispartofLecture Notes in Mechanical Engineeringen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240903_Gen_US
dc.subjectArtificial Intelligence; Corporate Performance; Corporate Performance Evaluation; Corporate Performance Measurement; Fuzzy Logic; Performance; Performance Evaluation; Performance Measurementen_US
dc.titleA Fuzzy Logic Approach for Corporate Performance Evaluationen_US
dc.typeConference Objecten_US

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