Developing a Strategy of Environmental Management for Electric Generating Companies Using DEA-Methodology
DOI:
https://doi.org/10.25728/assa.2017.17.4.521Keywords:
data envelopment analysis, non-parametric optimization, ecologic effects, environmental management, ecology management, electric companiesAbstract
This paper investigates the possibility of utilization of the Data Envelopment Analysis (DEA), which is a non-parametric method of optimization, to solving problems of environmental management in electric generating companies. An advantage of DEA is the possibility to work with DMUs without any knowledge of the actual functional relation between inputs and outputs. We analyze methods of incorporating the negative ecologic effects into a model and propose an algorithm for applying the basic DEA CCR input-oriented model twice in succession for the purpose of developing an optimal (ecologically and economically) strategy for environmental management in electricity energy generating companies. The developed method consists of sequentially solving several DEA models: the first-stage model determines the effectiveness of DMUs from an ecologic perspective and calculates target values for decreasing negative ecologic effects of non-effective DMUs. The second stage requires solving one input-oriented CCR model for each non-effective object, using economic and social characteristics of projects meant to reduce negative environmental influence, and using the target values calculated in the first stage as outputs. Besides the problem of evaluation the comparative efficiency of DMUs, ecologically oriented studies also often needs to evaluate the changes in a DMU’s efficiency dynamically. For this, the Malmquist productivity index (MPI) is used. MPI is a non-parametric method for analyzing time series that allows to track changes in DMU efficiency over time by means of DEA models. We test this algorithm on the statistical data provided by Russian electric companies for the period 2009-2011, and discuss methods for its practical application. The statistical data used in our calculations is averaged, and the results do not reflect the entire picture and should not be used to judge the quality of ecologic management in these companies. Nevertheless, the calculations can be used to evaluate the progress of completion and the practicality of investment projects of companies, from an environmental viewpoint. They also may be used to help develop state programs for support of modernization in electric energy industry, ecologic standards or energy-saving programs.