An Empirical Study on Determinants of MG’s Efficiency and Productivity Using Dynamic&Network SBM and Malmquist Index

Purpose The purpose of this paper is to demonstrate that overcapacity and tariff deficit (external constraints) negatively affect the efficiency of distribution firms in the Spanish electricity sector. To do this, the paper is based on the theory of constraints and theory of economic regulation. Design/methodology/approach Data envelopment analysis (DEA) window methodology is carried out on the constant scales (I-C) with a sample consisting of five main distribution firms during the period from 2006 to 2015. In turn, an analysis of the Malmquist index is carried out to assess whether it has had a displacement with respect to the efficiency frontier. Findings The results show that the overcapacity and the tariff deficit negatively affect the efficiency of the distribution firms of the Spanish electricity sector. In addition, there is an existence of external constraints that affect the activities of regulated organisations and the importance of adequate legislation in regulated sectors. Originality/value This study defines a model that shows how the efficiency problems associated with electricity distribution companies such as productive overcapacity or tariff deficit can be measured based on the theory of constraints and theory of economic regulation.

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Longitudinal evaluation of efficiency in a petrochemical company

Benchmarking An International Journal ◽

10.1108/bij-03-2016-0044 ◽

2017 ◽

Vol 24 (7) ◽

pp. 1786-1813 ◽

Cited By ~ 4

Author(s):

Charles Von Gilsa ◽

Daniel Pacheco Lacerda ◽

Luis Felipe Riehs Camargo ◽

Iberê Guarani Souza ◽

Ricardo Augusto Cassel

Keyword(s):

Learning Process ◽

Statistical Significance ◽

Malmquist Index ◽

Internal Reference ◽

Content Type ◽

Internal Resources ◽

Investment Projects ◽

Actual Change ◽

Petrochemical Company ◽

Efficiency And Productivity

Purpose The purpose of this paper is to longitudinally assess the technical efficiency and productivity, considering investment projects and technological change, in a second-generation petrochemical company. Design/methodology/approach The study uses data envelopment analysis (DEA) together with the Malmquist index to measure efficiency during the analysis periods. The working method consists of four main phases, namely development of the conceptual model, construction of the mathematical model, application of model to the case, and analysis of the results. The study utilizes a quantitative approach with descriptive goals seeking to evaluate the impacts of technical changes on the operational efficiency and productivity of the production process. Findings The use of DEA associated with the Malmquist index proved to be viable for analyzing a single company and identifying efficiency improvements, as well as the impacts of the learning process and the implementation of improvement projects. However, the results of the improvement projects and learning process were not representative and had no statistical significance on the actual change in efficiency of the company during the periods analyzed. For the case in question, the learning process and continuous improvement were not observed during all study periods. Practical implications The proposition that the improvement projects and investments implemented increased the efficiency of the company was rejected. Hence, with this work, it was possible to determine that the company unnecessarily invested resources in projects to increase efficiency. Furthermore, the company could have explored more internal resources before making significant investments in increased efficiency. Originality/value As for the value of this research in the theoretical and academic scope, this paper advances knowledge on the application of DEA because it proposes to establish an internal reference benchmarking for comparison. The literature contains few studies that analyze organizations using continuous processes, such as petrochemical processes, in longitudinal studies as a function of time, especially with the use of DEA.

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