Monitoring the Performance of Petrochemical Organizations in Saudi Arabia Using Data Envelopment Analysis
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Department of Industrial Engineering, King Abdulaziz University, Jeddah, 21589, Saudi Arabia
2
Department of Computer Science, University of West of England, Bristol, BS16 1QY, UK
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Author to whom correspondence should be addressed.
Mathematics 2019, 7(6), 519; https://doi.org/10.3390/math7060519
Received: 3 May 2019 / Revised: 29 May 2019 / Accepted: 4 June 2019 / Published: 6 June 2019
(This article belongs to the Special Issue Application of Optimization in Production, Logistics, Inventory, Supply Chain Management and Block Chain)
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.
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Keywords:
data envelopment analysis; benchmarking; petrochemical industries; technical and super-efficiencies; multidimensional scaling; efficiency and scatter plots
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MDPI and ACS Style
Alidrisi, H.; Aydin, M.E.; Bafail, A.O.; Abdulal, R.; Karuvatt, S.A. Monitoring the Performance of Petrochemical Organizations in Saudi Arabia Using Data Envelopment Analysis. Mathematics 2019, 7, 519. https://doi.org/10.3390/math7060519
AMA Style
Alidrisi H, Aydin ME, Bafail AO, Abdulal R, Karuvatt SA. Monitoring the Performance of Petrochemical Organizations in Saudi Arabia Using Data Envelopment Analysis. Mathematics. 2019; 7(6):519. https://doi.org/10.3390/math7060519
Chicago/Turabian StyleAlidrisi, Hisham; Aydin, Mehmet E.; Bafail, Abdullah O.; Abdulal, Reda; Karuvatt, Shoukath A. 2019. "Monitoring the Performance of Petrochemical Organizations in Saudi Arabia Using Data Envelopment Analysis" Mathematics 7, no. 6: 519. https://doi.org/10.3390/math7060519
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