Inefficiency countervailed DEA (IC-DEA) method for assessing corporate environmental performance

Abstract

Data envelopment analysis (DEA) is a method frequently used to evaluate relative firm performance. However, high values in a few indicators can lead to a company being regarded as ‘efficient’, despite valuing poorly in other essential indicators. The Inefficiency Countervailed DEA (IC-DEA) method is thus developed. The method first defines an inefficient frontier using the proposed Reverse DEA (RDEA) model. An IC-DEA value is then determined by summing both the DEA and RDEA values. The IC-DEA method was applied to assess the environmental performance of major opto-electronic companies in Taiwan, demonstrating its applicability.

Keywords:

• environmental studies
• corporate planning
• data envelopment analysis
• linear programming
• optimization
• decision analysis

Corporate environmental performance (CEP) assessment has become an important task worldwide. The DEA method is thus frequently applied to evaluate relative firm performance based on multiple inputs and outputs. However, high values in a few indicators can lead to a company being regarded as ‘efficient,’ despite valuing poorly in other essential indicators. To resolve such problems, the Reverse-DEA (RDEA) model is proposed to determine the inefficient frontier and identify companies that are not truly efficient. Then, an IC-DEA value is computed by summing both the DEA and RDEA values for comparing CEP among companies. The proposed IC-DEA method improves the original DEA method by simultaneously considering both the efficiency and inefficiency frontiers to provide an unbiased method for assessing relative CEP.

Corporate environmental performance (CEP) assessment has become an important task worldwide. The DEA method is thus frequently applied to evaluate relative firm performance based on multiple inputs and outputs. However, high values in a few indicators can lead to a company being regarded as ‘efficient,’ despite valuing poorly in other essential indicators. To resolve such problems, the Reverse-DEA (RDEA) model is proposed to determine the inefficient frontier and identify companies that are not truly efficient. Then, an IC-DEA value is computed by summing both the DEA and RDEA values for comparing CEP among companies. The proposed IC-DEA method improves the original DEA method by simultaneously considering both the efficiency and inefficiency frontiers to provide an unbiased method for assessing relative CEP.

Acknowledgements

The authors thank the National Science Council, Taiwan, R.O.C. for partially supporting this research under Grant No. NSC96-2221-E-009-056-MY3.