Measure Data Envelopment Analysis Model Research Articles

A hybrid two-stage robustness approach to portfolio construction under uncertainty

This paper proposes a hybrid two-stage robustness approach to portfolio construction under data uncertainty. In the first stage, a stock’s efficiency performance from candidate stocks is assessed and selected using an integrated dynamic slack-based measure data envelopment analysis model. We discuss the stability of efficiency estimates using the leave-one-out method. In the second stage, a “robust” stable and scaled mean-variance-Entropic Value-at-Risk model is used to determine the optimal weights allocated to qualified stocks in the presence of proportional transaction costs. The proposed method reduces computational complexity, increases robustness, and provides a comprehensive evaluation of stocks under different financial decisions, thereby increasing conservatism in the investment process. We demonstrate the applicability of the proposed hybrid two-stage approach to stock data from the Shenzhen and Shanghai Stock Exchanges. Results show that with increasing required returns, the proposed method improves the capital amount for investment and lowers transaction costs at the expense of additional risk. The study concludes by comparing the computational performance of the proposed approach to that of existing methods.

China's transportation sector carbon dioxide emissions efficiency and its influencing factors based on the EBM DEA model with undesirable outputs and spatial Durbin model

The threat of global climate change has caused the international community to pay close attention to atmospheric levels of greenhouse gases such as carbon dioxide. Transportation sector carbon dioxide emissions efficiency (TSCDEE) is a key indicator used to prioritize sustainable development in the transportation sector. In this paper, the epsilon-based measure data envelopment analysis model with undesirable outputs is applied to estimate TSCDEE for 30 provinces in China from 2010 to 2016. We also analyze influencing factors using the spatial Durbin model. Research shows that the overall TSCDEE of the Chinese provinces studied was 0.618, indicating that most regions are still in need of improvements. The provinces with the highest TSCDEE are located in developed coastal regions of China. This study shows that factors such as transportation structure, traffic infrastructure level, and technological progress have prominent positive effects on TSCDEE, while both urbanization level and urban population density exert significantly negative effects on TSCDEE. The findings should have a far-reaching impact on the sustainable development of global transportation.

Evaluating the energy efficiency of wastewater treatment plants in the Yangtze River Delta: Perspectives on regional discrepancies

With priorities to reach a carbon emission peak and integrated development involving ecological demonstration, a systematic evaluation on the energy efficiency and internal discrepancies of wastewater treatment plants in the Yangtze River Delta region is needed. In this study, a slacks-based measure data envelopment analysis model was applied to quantify the relative energy efficiency of 270 regional wastewater treatment plants. Based on the score of relative energy efficiency, the internal discrepancies of the region were identified through a method combining spatial and sensitivity analysis. Although the wastewater treatment plants had met the pollutant limits of discharge standards, the result of data envelopment analysis showed that 253 wastewater treatment plants were inefficient (with efficiency scores less than 1) due to input excess or output shortfall, indicating substantial potential for improving the energy efficiency. Besides, binary logistic regression demonstrated the significant impact from explanatory factors including designed capacity (104 m3/d), loading rate (%), influent ratio of chemical oxygen demand to total nitrogen, and influent concentration (mg/L) of chemical oxygen demand. Moreover, with regards to regional discrepancies, proportion of efficient wastewater treatment plants for Shanghai, Jiangsu, Zhejiang, and Anhui differs significantly. The area surrounding Taihu Lake was recognized as the trough of the Yangtze River Delta region in terms of the relative energy efficiency of wastewater treatment plants. This paper would give a reference for optimization of wastewater treatment plants in the study area and the evaluation framework on internal discrepancies might also be useful for other regions worldwide.

Evaluation and Decomposition of Tourism Inefficiency Considering Heterogeneous Technology: An Empirical Study from China

Considering both sectoral and regional heterogeneities, this article develops a structural meta-frontier slacks-based measure data envelopment analysis model to decompose the inefficiency level, input reduction and output expansion potentials and efficiency change into three components: sectoral heterogeneity, regional heterogeneity, and resource utilization. Subsequently, an empirical study of China’s provincial tourism subsectors between 2000 and 2014 is conducted. The results show that regional heterogeneity and resource utilization failure are the main contributors to the inefficiency of travel agencies, but the inefficiency of star-rated hotels and tourist attractions are dominated by sectoral heterogeneity. The tourism inefficiency of China is mainly characterized by insufficient output rather than input redundancy, and there are significant differences in the sources of output expansion potential for different tourism subsectors. In addition, the driving force for improving the efficiency of travel agencies ascribed to resource utilization capabilities are pure technological progress and technology scale change.

A dynamic multi-stage slacks-based measure data envelopment analysis model with knowledge accumulation and technological evolution

Dynamic data envelopment analysis (DEA) models are built on the idea that single period optimization is not fully appropriate to evaluate the performance of decision making units (DMUs) through time. As a result, these models provide a suitable framework to incorporate the different cumulative processes determining the evolution and strategic behavior of firms in the economics and business literatures. In the current paper, we incorporate two distinct complementary types of sequentially cumulative processes within a dynamic slacks-based measure DEA model. In particular, human capital and knowledge, constituting fundamental intangible inputs, exhibit a cumulative effect that goes beyond the corresponding factor endowment per period. At the same time, carry-over activities between consecutive periods will be used to define the pervasive effect that technology and infrastructures have on the productive capacity and efficiency of DMUs. The resulting dynamic DEA model accounts for the evolution of the knowledge accumulation and technological development processes of DMUs when evaluating both their overall and per period efficiency. Several numerical examples and a case study are included to demonstrate the applicability and efficacy of the proposed method.

旅游地生态效率测度的SBM-DEA模型及实证分析

旅游地生态效率测度的SBM-DEA模型及实证分析

Environmental efficiency of land transportation in China: A parallel slack-based measure for regional and temporal analysis

As the second largest economic entity in the world, China plays an important role in controlling global carbon dioxide (CO2) emissions. The land transportation sector (including railway transportation and road transportation) has been the most important source of emissions in China and the average CO2 emissions of land transportation were 529.31 million tons during the period 2009–2012. In this study, a parallel Slack-Based Measure Data Envelopment Analysis model is proposed, which is used for evaluating the overall efficiency of the land transportation sector and individual efficiencies of the railway transportation and highway transportation subsectors at the same time, considering CO2 emissions. The empirical results lead to three conclusions: (a) only Anhui province is efficient each year during 2009–2012. (b) The environmental efficiency of the Eastern area in China is the best, followed by the Central area, with the Western area being the worst. (c) The performance of railway transportation is better than that of highway transportation. These three conclusions lead to policy suggestions to promote highway transportation technological innovation and narrow the regional imbalances in land transportation. This paper makes two main contributions: the model advances improvements to methods used in the Data Envelopment Analysis technique, and also provides governments with a practical and yet easy-to-adopt perspective to implement land transportation performance measurement that aids in decision making.

A HYBRID INTEGER DATA ENVELOPMENT ANALYSIS BASED ON AN ALTERNATIVE APPROACH OF SUPER SLACK BASED MEASURE FOR MEASURING SUPER EFFICIENCY AND INEFFICIENCY OF DECISION MAKING UNITS

Conventional data envelopment analysis (DEA) models assume that all values of input and output variables are non-integers. However, in many situations of real life DEA application, some of the input and/or output variables are to be integers.The rounding process of the non-integer values to their nearest integers can cause inaccurate efficiency and performance measurement. Thus, it is important to develop a non-radial hybrid integer DEA model. Moreover, the projection of decision making units (DMUs) in the existing super efficiency slack based measure hybrid integer model may not be strongly Pareto-efficient.Thus, our hybrid integer DEA model is developed based on an alternative super efficiency slack based measure DEA model for ranking efficient and inefficient DMUs.The developed model can project efficient DMUs resulted from super efficiency strongly Pareto-efficient by identifying input excesses and output shortfalls of non-integer and integer slack variables. It then discriminates inefficient DMUs whose efficiency scores resulted from super efficiency slack based measure model equal to one.An application to measure the efficiency of 41 academic departments at National Cheng Kung University in Taiwan (NCKU) is used to test the applicability of developed models. The results showed that 51.20% of the departments (DMUs) were super efficiency. Moreover, the result also showed that most of the inefficient departments were caused by their input excesses of expenses and teaching space, and output shortfalls associating with publications and grants.

Analysis of the Environmental Efficiency of the Chinese Transportation Sector Using an Undesirable Output Slacks-Based Measure Data Envelopment Analysis Model

Many countries are attempting to reduce energy consumption and CO2 emissions while increasing the productivity and efficiency of their industries. An undesirable-output-oriented data envelopment analysis (DEA) model with slacks-based measure (SBM) was used to evaluate the changes in the environmental efficiency of the transportation sector in 30 Chinese provinces (municipalities and autonomous regions) between 2003 and 2012. The potential for decreasing CO2 emissions and energy saving was also assessed. Transportation was found to be inefficient in most of the provinces and the average environmental efficiency was low (0.45). The overall average efficiency reached a maximum in 2005 and continually decreased until a minimum was reached in 2009; since then, it has increased. In general, transportation is more efficient in eastern than in central or western China. A sensitivity analysis was also carried out on the input and output indicators. Based on these findings, some policies are proposed to improve the environmental efficiency of the transportation sector in China.

An Application of the Dynamic Network DEA Model: The Case of Banks in Taiwan

ABSTRACTIn this study, we apply the dynamic network slack-based measure data envelopment analysis model (DNSBM) to measure the efficiency of Taiwanese banks during the period 2005–11. Using the network structure, we define intellectual capital creation capability as one of the production stages. In order to capture the dynamics of the transformation process, the nonperforming loans and loan loss reserves are defined as carryover items. This study offers sufficient information for managers to understand not only the overall performance of their banks but also the efficiency of each production stage and the dynamic changes of the overall and divisional efficiencies.

Evaluating economic and environmental efficiency of global airlines: A SBM-DEA approach

This study examined the economic and environmental efficiency of 27 global airlines in 2010. An extended environmental slacks-based measure data envelopment analysis model with the weak disposability assumption was developed to assess the efficiency of the airlines. Asia-based airlines are generally more efficient, followed by European and American airlines. The poor fuel consumption is a major cause of inefficient airlines both in economic and environmental aspects.