Measuring Eco-Inefficiency: A New Frontier Approach

Abstract

Increasing social concerns over the environmental externalities associated with business activities are pushing firms to identify activities that create economic value with less environmental impact and to become more eco-efficient. Over the past two decades, researchers have increasingly used frontier efficiency models to evaluate productive efficiency in the presence of undesirable outputs, such as greenhouse gas emissions. In this paper, we identify critical flaws of existing frontier models and show that under these models eco-inefficient firms can be identified as eco-efficient. We develop a new ecoinefficiency frontier model that rectifies these problems. Our model allows us to calculate, for each firm, an eco-inefficiency score and improvements in outputs necessary to attain eco-efficiency. We demonstrate, through a Monte-Carlo experiment that our eco-inefficiency model provides a more reliable measurement of corporate eco-inefficiency than the existing frontier models. In the simulation experiment we develop a production function of multiple desirable and undesirable outputs that extends the classical Cob-Douglas function of a single output. The multi-output production function allows for greater flexibility in the simulation analysis of frontier models.

Production frontier methodologies and efficiency as a performance measure in strategic management research

“…For example, the field of frontier methodologies has seen emerging extension to topics such as the measurement of eco‐efficiency and corporate social performance, where some of the outputs may be undesirable (such as pollution, labor issues, etc. ; see Chen and Delmas, , ; Reinhard, Lovell, and Thijssen, ). We encourage strategic management researchers to exploit frontier methodologies to explore agendas in these and other topic areas.…”

A comprehensive analysis of China's regional energy saving and emission reduction efficiency: From production and treatment perspectives

“…The third category is considering the disposability of production technology into non-parametric DEA model. Another way categorizing DEA models with undesirable outputs is in Chen and Delmas's (2012) study. Examples include the "undesirable output as input" model (Hailu and Veeman, 2001), Seiford and Zhu's (2002) model (SZ model), the hyperbolic model (Färe et al, 1989) and the directional distance function model (Chung et al, 1997).…”

“…A more detailed description of these models can be seen in Chen and Delmas (2012). They illustrated these four frontiers as in Fig.…”

Measuring energy and environmental performance for regions in China by using DEA-based Malmquist indices

“…In the DEA literature, there have been a variety of approaches to dealing with undesirable outputs, which can be mainly divided into two categories (Song et al 2012;Chen and Delmas 2012). The first one is based on the weak disposability assumption of undesirable outputs (Färe et al 1989(Färe et al , 2005Zhou et al 2012) and the second category on the strong disposability assumption on undesirable output.…”