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Abstract: There are two difficulties in doing an objective evaluation of the performance of decision-making units (DMUs). The first one is how to treat undesirable outputs jointly produced with the desirable outputs, and the second one is how to treat uncontrollable variables, which often capture the impact of the operating environment. Given difficulties in both model construction and data availability, very few published papers simultaneously consider the above two problems. This article attempts to do so by proposing six DEA-based performance evaluation models based on a research sample of the Chinese coal-fired power plants. The finding of this paper not only contributes for the performance measurement methodology, but also has policy implications for the Chinese coal-fired power sector.

Conclusion:

221 coal-fired power plants are pooled in a research sample in this paper, along with data on their annual generation, capital, labour, and fuel consumption, and also with data on their vintage, calorific value of coal and unit scale. The results obtained indicate that the impact of uncontrollable variables is relatively significant. This confirms the hypothesis that at least some power plants with relatively low efficiency scores in the traditional model achieved these in part due to their relatively unfavorable operating environments. However, it should be noted that after correcting this we find inefficiency to be around 10%. Eliminating this inefficiency via the appropriate market and regulatory mechanisms would yield substantial economic and environmental benefits. Future research will examine power plant efficiency in more detail and incorporate additional undesirable
outputs, such as CO2.

by Hongliang Yang, Michael Pollitt both of Judge Business School, University of Cambridge, Cambridge, CB2 1AG, UK

University of Cambridge Electric Policy Research Group www.electricitypolicy.org.uk
http://www.electricitypolicy.org.uk/pubs/wp/eprg0712.pdf