Measuring green technology progress in large-scale thermoelectric enterprises based on Malmquist–Luenberger life cycle assessment

Abstract

The Malmquist–Luenberger (ML) method is generally used for the overall evaluation of the green technology progress of decision-making units (DMUs) rather than that of subsystems. Life cycle assessment (LCA) can be applied to assess environmental effects but not measure technology progress. By combining the two methods and improving the ML productivity index, this study proposes an ML-LCA model. We find that the weighted computation of the rate of green technology progress for each subsystem based on weights acquired using LCA can effectively reveal the deep-seated production and management experiences of enterprises. To test the method in practical terms, this study analyzes the production processes of 1372 thermoelectric enterprises in China from 2004 to 2013, and measures their green technological progress using the ML-LCA method. Our findings indicate that the proposed ML-LCA method can effectively derive the conditions underlying the changes in each DMU during the evaluation period.