A Hybrid Clustering Method Using Balanced Scorecard and Data Envelopment Analysis

Heris Golpira
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Heris Golpira: Department of Industrial Engineering, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran

International Journal of Innovation and Economic Development, 2016, vol. 2, issue 1, 15-22

Abstract: This paper introduces a new hybrid clustering method using Data Envelopment Analysis (DEA) and Balanced Scorecard (BSC) methods. DEA cannot identify its’ input and output itself, and it is a major weakness of the DEA. In the proposed method, this gap is resolved by integrating DEA with BSC. Some decision-making units (DMUs) needed in DEA method, in compliance with some inputs and outputs is the major drawback of this integration. To deal with this disadvantage, the proposed method selects the most important strategic factors, attained from the BSC method. These data considered to be the input data for the DEA method to calculate relative closeness (RC) of each DMU to the ideal one. Plotting the screen diagram regarding RC index leads us to the final clustering method. Finally, computational results show the applicability and usefulness of the method.

Keywords: Balanced Scorecard; Data Envelopment Analysis; Ranking method; Clustering (search for similar items in EconPapers)
JEL-codes: M00 (search for similar items in EconPapers)
Date: 2016
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