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Data envelopment analysis (DEA) model has been proved as a useful technique to solve the infeasibility problem encountered in the Malmquist–Luenberger index (MLI). This study provides an alternative to avoid infeasibility under dynamic environments. The availability of new models is verified with a numerical example. In detail, we apply modified MLI models to assess the change of productivity for 28 banks in China from 2007 to 2016. The analysis shows the following: (1) Productivities of most banks were progressive before 2014 and declined since the bad influence of the economic decline in 2015. (2) Time is the main factor that causes productivity differences among the four types of banks. (3) The technical change mainly affects the productivity change for all four types of banks. The results also provide useful guidance for financial regulators and bank managers. For example, the variable change during this period implies that the income structure of the banking system in China is slowly changing to some extent, where corresponding strategies are needed. It also conforms to the law that science and technology is the primarily productive force. [ABSTRACT FROM AUTHOR]

The process of a regional industrial system in China can be separated into two internal stages: production stage and pollutant abatement stage. This paper aims to examine the efficiency of Chinese regional industrial systems by taking the operational performance of its two internal stages into consideration. Unlike traditional data envelopment analysis models that treat decision making units as “black box” when measuring their efficiencies with undesirable factors, this paper proposes a two-stage model based on slacks-based measure to evaluate the efficiency of Chinese regional industrial systems. By decomposing the efficiency into production efficiency and abatement efficiency, the proposed model can estimate the efficiencies of the whole regional industrial system, its production stage and abatement stage simultaneously. The model provides a way of improving performance of a regional industrial system through identifying its inefficient internal stages. This can help to find out the main sources of the inefficiency that arise from the internal stages within the system, which cannot be done by using conventional environmental data envelopment analysis models. Findings resulting from the model application show that there are great disparities in regional industrial systems' efficiencies, and the inefficiency of Chinese industrial system is largely driven by the abatement stage. [ABSTRACT FROM AUTHOR]

Data envelopment analysis has recently gained popularity and attention in operational and environmental assessment. A common feature of previous studies is decreasing an input vector to decrease the vector of undesirable outputs which is referred to as natural disposability. However, little research has considered how to increase the amount of capital input for clean production technology to decrease the amount of undesirable outputs in a data envelopment analysis framework, which is referred to as managerial disposability. Thus, this paper proposes an improved approach that considers measuring unified (operational and environmental) efficiency for managerial disposability, and compares this approach with the one for natural disposability. The proposed approach provides a positive strategy to reduce undesirable outputs and improve unified efficiency through increasing capital investment in clean production technology. A case study of regional industries in China in 2006–2010 utilizing this approach is also presented. The empirical study shows that the unified efficiencies of regional industries in China have relatively high scores for managerial disposability, and increasing capital investment is vital to achieve sustainable development in clean production technology. [ABSTRACT FROM AUTHOR]