Monitoring the Performance of Petrochemical Organizations in Saudi Arabia Using Data Envelopment Analysis

Hisham Alidrisi, Mehmet Emin Aydin, Abdullah Omer Bafail, Reda Abdulal and Shoukath Ali Karuvatt
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Hisham Alidrisi: Department of Industrial Engineering, King Abdulaziz University, Jeddah, 21589, Saudi Arabia
Mehmet Emin Aydin: Department of Computer Science, University of West of England, Bristol, BS16 1QY, UK
Abdullah Omer Bafail: Department of Industrial Engineering, King Abdulaziz University, Jeddah, 21589, Saudi Arabia
Reda Abdulal: Department of Industrial Engineering, King Abdulaziz University, Jeddah, 21589, Saudi Arabia
Shoukath Ali Karuvatt: Department of Industrial Engineering, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

Mathematics, 2019, vol. 7, issue 6, 1-16

Abstract: The petrochemical industry plays a crucial role in the economy of the Kingdom of Saudi Arabia. Therefore, the effectiveness and efficiency of this industry is of high importance. Data envelopment analysis (DEA) is found to be more acceptable in measuring the effectiveness of various industries when used in conjunction with non-parametric methods such as multiple regression, analytical hierarchy process (AHP), multidimensional scaling (MDS), and other multiple criteria decision making (MCDM) approaches. In this study, ten petrochemical companies in the Kingdom of Saudi Arabia are evaluated using Banker, Charnes and Cooper (BCC)/Charnes, Cooper, and Rhodes (CCR) models of DEA to compute the technical and super-efficiencies for ranking according to their relative performances. Data were collected from the Saudi Stock Exchange on key financial performance measures, five of which were chosen as inputs and five as outputs. Five DEA models were developed using different input–output combinations. The efficiency plots obtained from DEA were compared with the Euclidean distance scatter plot obtained from MDS. The dimensionality of MDS plots was derived from the DEA output. It was found that the two-dimensional positioning of the companies was congruent in both plots, thus validating the DEA results.

Keywords: data envelopment analysis; benchmarking; petrochemical industries; technical and super-efficiencies; multidimensional scaling; efficiency and scatter plots (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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