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2024 | OriginalPaper | Buchkapitel

Organizational Performance Evaluation Using Artificial Intelligence Algorithm

verfasst von : Elif Yıldırım, Kenan Aydoğdu, Ayten Yilmaz Yalciner, Tijen Over Ozcelik, Mehmet Cetinkaya

Erschienen in: Advances in Intelligent Manufacturing and Service System Informatics

Verlag: Springer Nature Singapore

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Abstract

The Balanced Scorecard (BSC) performance system application has been generally accepted and is frequently applied in evaluating and measuring company performance. This performance evaluation system envisages a system in which the company’s performance is assessed in four dimensions, the indicators determined according to these four dimensions are weighted, and the performance calculation is made consequently. It is a performance system in which the performance of each dimension is independently examined and evaluated.
In this study, the “red area performance evaluation system” applied to Kayalar Pres company, which produces installations and fasteners, is modeled with fuzzy logic. The results are compared with the actual application results.
The application of this study in a performance system with actual data enables the accuracy of the performance indicator weights determined by the management to be compared. The data obtained on the performance system were formed as fuzzy sets based on expert opinions, and a fuzzy set matrix with 81 rules was developed with these sets. The created fuzzy set membership rules were made for all four indicators, and the “company performance score” was calculated. The 81 rules and output results determined in this direction were defined in the MATLAB fuzzy logic function, and the system was modeled on MATLAB accordingly. The results of the fuzzy logic function were obtained and interpreted by comparing the actual measurement results of the company.

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Metadaten
Titel
Organizational Performance Evaluation Using Artificial Intelligence Algorithm
verfasst von
Elif Yıldırım
Kenan Aydoğdu
Ayten Yilmaz Yalciner
Tijen Over Ozcelik
Mehmet Cetinkaya
Copyright-Jahr
2024
Verlag
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-99-6062-0_68

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