Measuring and Improving Eco‐efficiency Using Data Envelopment Analysis

The concept of eco‐efficiency can be defined with the “product value/environmental influence” ratio. Different models have been proposed to measure eco‐efficiency. The main difference among them is the weighting system used to aggregate the environmental results. Data envelopment analysis (DEA) permits this aggregation without requiring a subjective judgment about the weights. In this study, we applied a DEA model to Spanish Mahón‐Menorca cheese production to determine the most eco‐efficient production techniques. To this end, 16 scenarios of Mahón‐Menorca cheese production were built regarding technical (degree of automation) and cleaner production criteria. The environmental impacts were assessed by means of life cycle assessment. We carried out an economic assessment by determining the economic value added and the net income for each scenario. The results are referred to as 1 kilogram (kg) cheese ripened over 105 days. Through DEA, an eco‐efficiency ratio between 0 and 1 was obtained. Three scenarios were found to be eco‐efficient, with a high degree of automation (enclosed vat and molding and demolding machines) and accelerated cheese ripening. We used Monte Carlo simulation to carry out a sensitivity analysis to compare the influence of price changes on the eco‐efficiency ratio. The results emphasize the consistency and stability of the eco‐efficient scenarios.