Comparison of supply chain performance evaluation with BSC-FDEA and BSC-RDEA methods in Tabriz automotive industries

Subject Areas : Industrial Management

SINA CHARTAB JABBARI ¹ , kamaleddin rahmani youshanloui ² , mohammad paseban ³ , yagoub Alavi matin ⁴ , Mojtaba Ramazani ⁵

1 - Ph.D Student, Department of Management, Management, Economic and Accounting Faculty , Tabriz Branch , Islamic Azad University , Tabriz, Iran.
2 - Assistant prof., Department of Management, Management, Economic and Accounting Faculty, Tabriz Branch, Islamic Azad University, Tabriz, Iran.
3 - Assistant Professor, Department of Management, Tabriz Branch, Islamic Azad University, Tabriz, Iran
4 - Assistant Prof., Management Faculty, Islamic Azad University Tabriz Branch, Tabriz, Iran
5 - Department of Management, Bonab Branch, Islamic Azad University, Bonab, Iran

Received: 2022-09-21 Accepted : 2023-01-23 Published : 2023-02-20

Keywords: Data envelopment analysis, fuzzy number set, rough number set, Supply Chain Efficiency, Automobile manufacturing,

Abstract :

Considering the importance of the issue of efficiency in the advancement of societies and the place it occupies in today's organizations, the use of performance evaluation has become an unavoidable necessity. In the present study, the performance evaluation of five active supply chains with the same structure with the aim of comparing the results of the combined RDEA-BSC and FDEA-BSC models in Tabriz automotive industry and the input and output data in the form of symmetrical triangular fuzzy numbers and the set of uneven numbers to the input and output model The models show the performance of the supply chain. From the Balanced Scorecard (BSC) method as a tool for designing performance evaluation indicators in four aspects; financial, processes, customer and learning and human force growth have been used and also the type of applied-descriptive research and measurement tool is questionnaire, financial documents and information analysis method, FDEA, RDEA, BSC mathematical model and sensitivity analysis. The results of the research show that the efficiency of Amico in each model is higher than other studied companies

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