Measuring productivity using Data Envelopment Analysis and Multiple-Objective Programming in flows, logistic and transportation

The logistic and transportation plays an integral part in maintaining a well-functioning organization. One of the most extensively used, original, famous, and popular non-parametric methods for evaluating the efficiency of organizations is the Data Envelopment Analysis, DEA technique. Suppose we can...

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Published in:Acta logistica Vol. 11; no. 2; pp. 245 - 255
Main Authors: Amiri, Maghsoud, Esmaeeli, Jafar, Sharifi, Mani, Zohrehvandi, Shakib, Knapcikova, Lucia
Format: Journal Article
Language:English
Published: Semsa 4S go, s.r.o 01.06.2024
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ISSN:1339-5629, 1339-5629
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Abstract The logistic and transportation plays an integral part in maintaining a well-functioning organization. One of the most extensively used, original, famous, and popular non-parametric methods for evaluating the efficiency of organizations is the Data Envelopment Analysis, DEA technique. Suppose we can formulate the concept of effectiveness in the DEA technique. In that case, we will be able to measure the productivity of organizations since productivity is a blend of efficiency and effectiveness. Several studies have been developed, e.g., the “Malmquist Productivity Index” (MPI) and the “Lunberger Productivity Index” (LPI), which assess the productivity of corporations through the DEA technique, but these models do not display all factors in a system. Also, they need at least two periods to appraise productivity. Furthermore, their two components of efficiency and effectiveness are not considerably evident. Moreover, sensitivity analysis is not possible in these models. Therefore, a model was presented that can measure the relative productivity of decision-making units through the technique of DEA, simultaneously in a period through the two elements of efficiency and effectiveness with the feature of sensitivity analysis and its solution method is more reliable due to the use of multi-objective planning method. In addition, a case study was used to indicate the application of the proposed model, which demonstrated that a branch could be efficient but unproductive.
AbstractList The logistic and transportation plays an integral part in maintaining a well-functioning organization. One of the most extensively used, original, famous, and popular non-parametric methods for evaluating the efficiency of organizations is the Data Envelopment Analysis, DEA technique. Suppose we can formulate the concept of effectiveness in the DEA technique. In that case, we will be able to measure the productivity of organizations since productivity is a blend of efficiency and effectiveness. Several studies have been developed, e.g., the "Malmquist Productivity Index" (MPI) and the "Lunberger Productivity Index" (LPI), which assess the productivity of corporations through the DEA technique, but these models do not display all factors in a system. Also, they need at least two periods to appraise productivity. Furthermore, their two components of efficiency and effectiveness are not considerably evident. Moreover, sensitivity analysis is not possible in these models. Therefore, a model was presented that can measure the relative productivity of decision-making units through the technique of DEA, simultaneously in a period through the two elements of efficiency and effectiveness with the feature of sensitivity analysis and its solution method is more reliable due to the use of multi-objective planning method. In addition, a case study was used to indicate the application of the proposed model, which demonstrated that a branch could be efficient but unproductive.
Author Amiri, Maghsoud
Knapcikova, Lucia
Zohrehvandi, Shakib
Esmaeeli, Jafar
Sharifi, Mani
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StartPage 245
SubjectTerms Data analysis
Data envelopment analysis
Decision making
Effectiveness
Efficiency
Machine tool industry
Management decisions
Multiple objective analysis
Organizations
Productivity
Sensitivity analysis
Title Measuring productivity using Data Envelopment Analysis and Multiple-Objective Programming in flows, logistic and transportation
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