Efficiency decomposition in a three-stage network structure: Cooperative DEA, Nash bargaining game models and SOCP formulations

In this paper, for evaluating the efficiency in a three-stage DEA structure we use the additive and the multiplicative cooperative models that comply with the cooperation paradigm in the organizations, where for improving efficiency of system, stages cooperate together. Since the overall efficiency from the cooperative models may not be unique and consequently the stages’ efficiencies, then we combine them with the Nash bargaining game approach that besides maximizing efficiency scores for stages and the whole system, provides a unique and fair efficiency decomposition. Second order programming relaxation of the proposed nonlinear models are given in contrast to the parametric linear models in the literature. Finally, the effectiveness of the proposed models are illustrated with two numerical examples.

Industrial Electrification and Efficiency: Decomposition Evidence from the Korean Industrial Sector

For this study, we conducted a decomposition analysis of industrial electricity consumption based on the logarithmic mean Divisia index approach. An empirical dataset consisting of 11 industrial sectors in Korea from 2000 to 2018 was used. The three-factor decomposition equation was extended to include four factors by decomposing the energy intensity effect into electrification and electricity consumption efficiency effects. The empirical results are summarized as follows: The increase in electricity consumption in the Korean industrial sector from 2000 to 2018 is mostly caused by the production effect. While the structure effect decreases electricity consumption, the intensity effect increases it. The key findings indicate that the hidden electrification effect can be confusing to researchers with regard to the intensity effect. The empirical evidence suggests that the intensity effect has a positive effect on electricity consumption induced by the electrification effect, although the efficiency effect continuously decreased electricity consumption. The decomposition results of some sectors show that electrification, rather than the production effect, contributed the most to the increase in electricity consumption. This implies that while replacing fuel with electricity has been successfully achieved in several sectors, there are still challenges regarding increasing energy efficiency and expanding clean electricity generation.

Bank efficiency analysis of financial innovations: dea model application for the institutional concept

Globalization and digitization of the banking and financial market are well known. They are the trends of this decade-defining the context and efficiency of the banking business. Financial innovations introduced by new technologies have provided banks with the necessary utilities to seize the possibilities to tap into efficiency and competitive advantage gains. In this context, this study seeks to assess the overall efficiency of Azerbaijanian banks in adopting and utilizing financial innovation in providing financial products and services. The data envelopment analysis was applied to compute and compare the ability of financial intermediaries to adopt financial innovations via modern technologies efficiently. Based on the institutional value-added concept, the aggregate efficiency score for each of the 14 banking institutions was calculated. The inefficiency sources were derived from the overall technical efficiency decomposition into pure technical efficiency and scale efficiency. The results showed that only four banks had utilized financial innovations in the banking production process to increase their value-added during 2017-2019. Decomposition results further indicated that slight values of the overall technical inefficiency were caused by scale inefficiency. Thus, these banks' had the capacity for banking business value-added growth by 5-16% just by adjusting scales. Simultaneously, all significant deviations from the absolute overall technical efficiency caused by both pure technical efficiency and scale efficiency. Therefore, there is still much room for banking institutions to increase value-added by adjusting scales and enhancing banking operations and management.

A slacks-based measure approach for efficiency decomposition in multi-period two-stage systems

Two-stage production systems are often encountered in many real applications where the production process is divided into two processes. In contrast to the conventional data envelopment analysis (DEA) models, two-stage DEA models take the operations of the internal processes into account. A number of studies have used two-stage DEA models in order to evaluate the performance of decision making units (DMUs) having a network structure. In this paper, we use a non-radial DEA model called the network slacks-based measure (NSBM) model to measure the efficiency of a system with a multi-period two-stage structure. Then we describe the properties of the proposed model in details. Moreover, we shall decompose the overall efficiency of the system over a number of time periods as a weighted average of the efficiency in each period. The efficiency of the stages, in respect to the entire periods shall be decomposed in terms of the weighted average efficiency of the stages in each period. Finally, the real data of Mellat bank branches in Tehran extracted from extant literature is used to illustrate the proposed approach.

Dynamic Evaluation and Internal Driving Factors of Water Resources Green Efficiency in China

High-quality economic development and the realization of ecological civilization have become the main goals of China’s economic development. This study constructed a global reference Malmquist–Luenberger productivity index model of directional distance function from the perspective of mixed disposability and divided water resources green efficiency into pure technical efficiency change (PEC) index, scale efficiency change (SEC) index, pure technology change (PTC) index and scale technology change (STC) index. The results show the following: (1) The value of China’s water resources green efficiency increased by 1.1% from 2000 to 2016. The central region improved the most (1.4%), followed by the western (1%) and eastern (0.9%) regions. The water resources green efficiency improved in all provinces except Guangxi and Yunnan. (2) The water resources green efficiency is significantly affected by national policies, and there may not be a significant positive correlation with economic development. At present, the water resources green efficiency in most provinces still needs to be improved. (3) From 2000 to 2016, China’s water resources green efficiency decomposition index showed an upward trend except for SEC, and PTC was the main driving force for improving China’s water resources green efficiency. (4) The variation of PEC among provinces showed an inverted “N” trend, while the differences of SEC and STC showed an ascending trend, and PTC showed an inverted “U” trend. The proportions of provinces in which PEC, SEC, and STC indices improved were 40%, 46.67%, and 60%, respectively.