Dominance-based measurement of productive and environmental performance for manufacturing

https://doi.org/10.1016/S0377-2217(03)00181-4Get rights and content

Abstract

The concept of efficiency measurement is based on the definition of a frontier that envelopes observed production plans. The effect of pollution prevention and environmental compliance on productive efficiency is typically studied by considering pollution as not freely disposable (i.e., there is a cost incurred to dispose of pollution) or by assigning shadow prices to pollution outputs. However, the frontier along with the required technological assumptions needed for its definition may be replaced with the concept of pairwise dominance. With data from a manufacturing facility, the use of pairwise dominance allows one to consider a wide spectrum of inputs and outputs. Furthermore, the approach of benchmark correspondence is augmented so as to consider environmental performance. Pairwise dominance is applied to segregate production plans into sets according to their relative environmental and productive efficiency performance. These sets in conjunction with appropriately identified reference production plans are used to define distance-based measures of efficiency and environmental performance. Pollution prevention activities of a printed circuit board manufacturing facility motivated the development of the reported analytical framework.

Introduction

The analysis of the effect of pollution prevention and environmental compliance for manufacturing systems has not been studied extensively. The United States Environmental Protection Agency (USEPA) environmental management hierarchy places pollution prevention first, followed by recycling, treatment, and finally disposal in order of preference (USEPA, 1992, p. 5). Pollution prevention is generally considered to include only source reduction prior to recycling, treatment, or disposal. Although not generally considered to be part of pollution prevention activities, recycling is another means of reducing adverse environmental impacts without resorting to expensive end-of-pipe pollution controls and is considered one of the measures of environmental performance defined in this paper.

In the literature, the generation of pollution has been taken into account using a number of different analytical methods briefly presented in Section 2. Two fundamental assumptions underlying these methods are that: (a) Pollution controls are after-the-fact, end-of-pipe and do not explicitly take into account process and other changes that can reduce pollution (i.e., pollution prevention) and can potentially improve efficiency performance. (b) Interactions with other production systems represented by variations in input and output mixes are not taken into account. For example, from an environmental impact perspective it is generally more desirable to send a waste stream to a recycler than to a land disposal facility.

Therefore, the objective of this research is to develop a performance measurement-modeling framework that considers pollution prevention activities and environmentally desirable interactions of a manufacturing facility over time. The term productive and environmental performance is used since criteria other than just the conversion efficiency of inputs to outputs are considered. More specifically, we propose a pairwise dominance approach that considers both efficiency and environmental performance and assesses the environmental desirability of manufacturing system interactions represented by differences in input and output mixes. As part of this approach, we propose specific metrics of performance. This research was motivated by the need to capture the environmental and productive performance of a circuit board manufacturing facility. The implementation of the proposed framework is documented elsewhere (Otis, 1999). Nevertheless, the use of actual manufacturing data provided important insights into the data and analysis requirements for the proposed analytical framework.

In general, the measurement of performance requires the definition of some reference. The measure of performance is then based on a difference between the reference and the system or production plan being evaluated. A production plan is defined by the inputs used and outputs produced by a manufacturing system during a specific time period. The proposed framework in this research addresses three aspects of performance: productive efficiency, pollution prevention, and interaction with other production systems. It augments the benchmark correspondence approach (Tulkens and Vanden Eeckaut, 1995b) so as to include all three aspects of performance.

Productive efficiency is measured by defining an appropriate reference production plan so as to capture variations of efficiency over time. The measure of productive efficiency indicates how well a particular production plan (e.g., mix of inputs used to produce outputs) converts inputs to product outputs. Furthermore, the less input required to produce a given product output the better the manufacturing facility is both from a productive efficiency and environmental performance perspective. In other words, increasing productive efficiency is also desirable from an environmental perspective when considering only the inputs used by a particular manufacturing facility.

The possible relationship between production process changes (e.g., pollution prevention activities) and waste generation are taken into account by considering undesirable outputs (i.e., waste) in production and by making a distinction between material and non-material inputs. Material inputs include raw materials and energy used to make products. Non-material inputs are labor and capital. From an environmental perspective, non-material inputs are preferred to material inputs. Pollution prevention activities should reduce the quantity of undesirable outputs and may also reduce the quantity of material inputs for a given level of product outputs. Improving environmental performance through pollution prevention can improve productive efficiency, as it is usually measured but not necessarily. For example, increased investment and labor may be required to achieve improvements in environmental performance that may result in overall productive efficiency being reduced.

It should be noted that the measurement of performance based on inputs and outputs does not distinguish between pollution prevention activities and other activities that may also improve environmental performance. This is because capital spending, for example, may be used to reduce undesirable outputs through the installation of end-of-pipe pollution controls (e.g., scrubbers on a power plant). This may constitute an improvement in environmental performance, but is not considered pollution prevention.

The extent of interaction with other production systems is another important aspect of environmental performance. This is considered in the proposed framework by evaluating input and output mixes. This requires that inputs and outputs be categorized according to their relative desirability from the perspective of environmental performance. From this perspective, it is desirable to substitute less desirable outputs (e.g., discharge to the air or water) with more desirable outputs (e.g., recycled output) and to substitute less desirable inputs (e.g., mined and refined ores) with more desirable inputs (e.g., scrap metal).

Therefore, the proposed framework first recommends a reference production plan as the basis of the subsequent partitions when evaluating the performance of a manufacturing facility over time. Second, it creates subsets of the production plans based on a distinction between product outputs/undesirable outputs and material/non-material inputs. Third, it applies dominance-based techniques to determine whether or not a substitution moves a production system into a state that is more desirable from an environmental perspective. Fourth, it calculates performance measures by comparing all production plans to the reference production plan. Evaluation of performance is based on these measures.

The proposed framework has general applicability for manufacturing facilities where a large number of inputs and outputs need to be considered so as to more realistically depict manufacturing occurrences. In the case where one needs to consider large number of inputs and outputs one can aggregate variables in order to perform standard efficiency measurement analysis. However, the use of aggregated data makes it substantially more difficult if not impossible to relate results back to occurrences in the production process and provide meaningful performance improvement interventions.

The following sections are included in this paper. In Section 2 the efficiency and productivity literature that deals with environmental issues is briefly summarized. Then, the approach is extensively presented in Section 3. Conclusions and future research issues are discussed in Section 4.

Section snippets

Production theory based approaches that model environmental performance

In measuring productive efficiency, waste products are sometimes explicitly considered and sometimes not. Both econometric and data envelopment analysis (DEA) (Charnes et al., 1978) based techniques are used to evaluate the effect of pollution controls on productive performance. There are three approaches that have been used. One is to apply standard DEA or econometric analysis to decision-making units with and without pollution controls. The results obtained by considering and not considering

The framework

The previous methods for defining the production frontier (also called the reference technology) depend on making different assumptions about the form of the production frontier. The less restrictive the assumptions are the more closely the frontier matches the actual production plans. The advantage of more closely matching the production frontier to actual production plans is that measurements of performance are less subject to variation caused by the assumptions with respect to the shape of

Conclusions and future research issues

Existing methods of measuring productive efficiency have two main drawbacks in terms of their application to operational data from manufacturing facilities. First, the original formulations have focused on evaluating the relative productive efficiency of similar facilities. For example, bank branches, power plants, and so on. These methods were not originally intended for the application to time series data from a single facility. While there are examples of DEA applications to such time series

References (29)

  • D.W. Caves et al.

    The economic theory of index numbers and the measurement of input, output, and productivity

    Econometrics

    (1982)
  • Färe, R., Grosskopf, S., 1995. Environmental decision models with joint outputs. Provided by R. Färe, August...
  • R. Färe et al.

    Multilateral productivity comparisons when some outputs are undesirable: A nonparametric approach

    The Review of Economics and Statistics

    (1989)
  • R. Färe et al.

    On price efficiency

    International Economic Review

    (1990)
  • Cited by (0)

    View full text