Efficiency and benchmarking in the presence of undesirable (bad) outputs: A DEA approach

Abstract

Environmental assessment recently becomes a major policy issue in the world. This

study introduces a data envelopment analysis (DEA) model to explore a new use of DEA

for the environmental assessment in which outputs are classified into desirable (good) and

undesirable (bad). Such an output separation is important in the DEA-based environmental

assessment. We used a Range-Adjusted Measure (RAM) DEA model for combining the

two performance measures operational and environmental performance as a unified measure.

Reducing the amount of undesirable outputs is the main purpose of environmental

assessment. Therefor, we try to project the inefficient organization on the efficient frontier

such that the obtained projection produces fewer undesirable outputs than the evaluated

organization. To reach this goal, it is not important to increase or decrease the amount of

inputs.