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Data envelopment analysis (DEA) has recently gained great popularity in modeling environmental performance because it provides condensed information to decision makers when the production process includes undesirable outputs. In this paper, we develop a new slacks-based efficiency measurement for modeling environmental performance using the environmental DEA technology. The proposed index has more theoretical justification, and distinguishes among different decision making units (DMUs) better in practice. Then we further extend it to the nonoriented index with double aim of increasing desirable outputs and reducing undesirable outputs. Finally, we calculate the index for each of 25 OECD European countries in a model of CO₂ emission performance from 2007 to 2009 and the results obtained are presented.

Gas refineries are an important part of the energy supply in the world but they may produce byproducts like emissions too. Thus, both technical performance and environmental execution are important and need to be analyzed. Iran is the third-highest producer of natural gas in the world. It produces 6.5% of the natural gas in the world. This paper rummages the environmental and technical performance of Iranian gas refineries through data envelopment analysis (DEA), which is a strong frontier analysis approach is used in this study. Although the primary result shows a rather good performance of Iranian gas refineries overall, more potentials are found for improvement. We find 6% technical potential and 8% environmental potential for improvement which is still a considerable amount. Thus, national and international policymakers should consider this potential for better production and supply of natural gas. We also provided an empirical robustness check to enrich our findings.

Data envelopment analysis (DEA) is a technique to evaluate the relative efficiency of a set of decision making units (DMUs) which is applicable in different systems such as engineering, ecology, and so forth. In real-world situations, there are instances in which production processes of systems must be analyzed in multiple periods while desirable and undesirable outputs are present; therefore, in the current paper, a DEA-based procedure is suggested to estimate the performance of systems with desirable and undesirable outputs over several periods of time. Actually, the overall and period efficiencies of DMUs in the presence of undesirable outputs are calculated by using the DEA technique. Different aspects of disposability, i.e., strong and weak, are considered for undesirable outputs. Moreover, the overall efficiency is indicated as a weighted average of the efficiencies of periods. Efficiency changes between two periods are also estimated. The proposed approach has been tested by a numerical example and applied to evaluate the efficiency of commercial transport industry in 17 countries. The findings show that efficiency scores and their changes between periods might alter by incorporating undesirable outputs into the multi-period system under evaluation; consequently, the proposed approach obtains more rational and accurate results when undesirable outputs are present.