Total factor energy productivity considering undesirable pollutant outputs: A new double frontier based malmquist productivity index

Abstract

Determining energy productivity change during a time interval is an important issue in many production lines. Data Envelopment Analysis (DEA) approach is a well-known technique utilized to measure productivity change and widely used by researchers to analyze the performance of decision making units. In this regard, the modified Enhanced Russell Measure (ERM), a non-radial DEA-based efficiency model, is applied to develop new models for measuring the Malmquist productivity index (MPI). To present productivity changes of decision making units (DMUs) over time more truly and more comprehensively than the conventional MPI method, this paper proposed three new approaches by using optimistic, pessimistic, and general viewpoints of data envelopment analysis. However, in many production processes, undesirable outputs such as smoke or waste pollution may be generated. Thus, this paper has further developed the proposed approaches in the presence of an undesirable output. The proposed methodology is applied to evaluate the productivity changes and efficiencies of chickpea production farms in 16 provinces in Iran.