Super-efficiency Data Envelopment Analysis Model Research Articles

Robust, extended goal programming with uncertainty sets: an application to a multi-objective portfolio selection problem leveraging DEA

AbstractThis study presents a two-phase approach of Data Envelopment Analysis (DEA) and Goal Programming (GP) for portfolio selection, representing a pioneering attempt at combining these techniques within the context of portfolio selection. The approach expands on the conventional risk and return framework by incorporating additional financial factors and addressing data uncertainty, which allows for a thorough examination of portfolio outcomes while accommodating investor preferences and conservatism levels. The initial phase employs a super-efficiency DEA model to streamline asset selection by identifying suitable investment candidates based on efficiency scores, setting the stage for subsequent portfolio optimization. The second phase leverages the Extended GP (EGP) framework, which facilitates the comprehensive incorporation of investor preferences to determine the optimal weights of the efficient assets previously identified within the portfolio. Each goal is tailored to reflect specific financial factors spanning both technical and fundamental aspects. To tackle data uncertainty, robust optimization is applied. The research contributes to the robust GP (RGP) literature by analyzing new RGP variants, overcoming limitations of traditional and other uncertain GP models by incorporating uncertainty sets. Robust counterparts of the EGP models are accordingly developed using polyhedral and combined interval and polyhedral uncertainty sets, providing a flexible representation of uncertainty in financial markets. Empirical results, based on real data from the Tehran Stock Exchange comprising 779 assets, demonstrate the superiority of the proposed approach over traditional portfolio selection methods across various uncertainty settings. Additionally, a comprehensive sensitivity analysis investigates the impact of uncertainty levels on the robust EGP models. The proposed framework offers guidance to investors and fund managers through a pragmatic approach, enabling informed and robust portfolio decisions by considering efficiency, uncertainty, and extended financial factors.

Can carbon emission trading improve regional eco-efficiency? Based on the environmental innovation perspective.

This paper uses green innovation and environmental pollution as the mediating variables to construct a mediating effect model to investigate whether China's carbon emission trading policy can improve regional eco-efficiency by reducing regional environmental pollution and stimulating green innovation. This study is based on panel data from 30 provinces and municipalities directly under China's central government and autonomous regions from 2003 to 2019. The eco-efficiency of these provinces is measured using the super-efficiency DEA model and the difference-in-difference method (DID). The results show that (1) China's emission trading policy significantly improves regional ecological efficiency and the per capita GDP. The improvement can effectively improve regional ecological efficiency. (2) The mediating effect of green innovation and environmental pollution is significant. That is, China's carbon emission trading policy further improves regional ecological efficiency by stimulating more green innovation and reducing the synergy brought by environmental pollution. (3) There are differences in the feedback of this impact mechanism between different regions: It shows the characteristics of the western region being more significant than the eastern region. The central region has no significant effect. The research conclusion can provide a policy reference for the subsequent unified promotion of the construction of a carbon emission trading market nationwide and a theoretical basis for helping to achieve the "dual carbon" goal.

Performance Test, Index System Establishment, and Comprehensive Evaluation of Earthquake Rescue Robots

To effectively enhance the adaptability of earthquake rescue robots in dynamic environments and complex tasks, there is an urgent need for a comprehensive evaluation method that encompasses establishing an evaluation index system, testing performance indexes, and conducting performance evaluation. Firstly, four main criterion and twenty-three sub-criterion indexes are established by conducting a comprehensive review of existing assessment measures for rescue robots across diverse domains. These indexes are validated through test modules developed by the National Earthquake Response Support Service to obtain corresponding values for each criterion. Moreover, a method for establishing the index system is proposed based on the fuzzy clustering analysis and grey correlation analysis methods. This method effectively addresses issues related to excessive subjectivity, redundancy, and ambiguous stratification of indexes. Subsequently, the DEMATEL is employed to scrutinize the interrelationships and causal connections among each index within the established index system, leading to the identification of input and output indexes based on the analysis outcomes. Finally, as an empirical example, three earthquake rescue robots are comprehensively evaluated and ranked using the super efficiency DEA model. Alongside analyzing results regarding input redundancy and output deficiency, targeted improvement suggestions are provided for each earthquake rescue robot. Additionally, comparison analysis with the entropy weight method and VIKOR method verifies the effectiveness of our proposed method.

Allocating the fixed cost as a complementary input in two-stage system: A DEA approach

The existing research on fixed cost allocation (FCA) in two-stage system data envelopment analysis (DEA) models typically regards the fixed cost as an additional input for each decision-making unit (DMU). However, these models overlook the prevalent real-world scenario where fixed costs act as complementary inputs in actual production processes. This study proposes a general two-stage network DEA model that incorporates the fixed cost as a complementary input to optimize the allocation scheme. First, we construct a functional relationship between the efficiency scores of DMUs and their allocated fixed costsusing a modified super-efficiency DEA model, which effectively classifies DMUs and solves infeasible solutions within the variable returns to scale (VRS) framework. Then, we propose a fair and unique allocation model based on fairness and efficiency maximization principles. Specifically, we allocate fixed costs based on the operational scale for inelastic DMUs while equitably increasing the efficiency scores for elastic DMUs. Finally, a numerical example and an empirical study on subsidy allocation among 30 provinces demonstrate the rationality and acceptability of our approach.

Efficiency Characteristics and Evolution Patterns of Urban Carbon Metabolism of Production-Living-Ecological Space in Beijing-Tianjin-Hebei Region

This study explored the carbon metabolism efficiency of a production-living-ecological space system, which is of great significance for regional factor integration and spatial optimization. In this study, the material flow analysis method was introduced to establish a framework for evaluating the carbon metabolism efficiency of the production-living-ecological space system, and the super-efficiency DEA model and Malmquist index were used to empirically analyze the spatio-temporal distribution, dynamic change, and evolution patterns of the carbon metabolism efficiency of production-living-ecological space in the Beijing-Tianjin-Hebei Region, China, from 2000 to 2020 on the basis of the urban metabolic perspective. The results showed that:① the carbon metabolism efficiency of the production-living-ecological space showed a fluctuating growth trend, indicating the significant spatial differentiation of carbon metabolism efficiency in each city. There was a low overall carbon metabolism efficiency level, with a distribution pattern of being high in the middle and low in the north and south. ② The Malmquist index showed that the Total Factor Productivity (TFP) of carbon metabolism efficiency was greater than 1, and both the Technical Change (TC) and Pure Efficiency Change (PEC) were less than 1, in which the TFP showed an increasing trend, whereas there was no significant contribution of technological progress or pure technical efficiency to carbon metabolism efficiency. The total factor productivity of more than 50% of the cities showed an improving trend, only 38.46% of which made technological progress in improving carbon metabolism efficiency, and more than half of the urban pure technical efficiency showed a decreasing trend, in which the technical efficiency change and scale efficiency change were greater than 1 in most cities. ③ There were different types of carbon efficiency characteristics in each city, and according to the movement rules of the corresponding points in the quartile map, the evolution patterns of tourism industry efficiency were classified into stable, reciprocating, progressive, and abrupt. Therefore, local governments should adopt differentiated strategies to reasonably allocate spatial resources of production-living-ecological space and improve the technical level and scale efficiency, so as to improve the efficiency of urban carbon metabolism.

Research on the environmental benefits of marine tidal energy and its impact on regional economic structure

Tidal power generation, being one of the earliest and largest developed new energy technologies, has evolved into a mature and increasingly competitive source of energy. This article delves into the evaluation of tidal energy's socioeconomic impact, establishing a connection between its environmental benefits and regional economic development. The focus is on marine economic efficiency, and the super-efficiency DEA model is employed to gauge this efficiency. The study conducts a thorough analysis of the green ocean economic efficiency in three major regions, introducing the Malmquist efficiency index for a comprehensive understanding of changing trends. Utilizing an economic effect model, the research explores the contribution of tidal energy development to regional economic growth, delving into industry-related effects. Through these analyses, we aim to provide a clearer and more comprehensive insight into the positive influence of tidal energy on regional socioeconomics. This understanding is pivotal for guiding sustainable tidal energy development and formulating relevant policies.

Research on the Water Environment Governance of Hangzhou Bay Based on the DEA–Tobit Model

With rapid urbanization and industrialization, Hangzhou Bay faces significant pressure in water environment governance. This study, based on panel data from 2011 to 2021 in Zhejiang’s Hangzhou, Jiaxing, Shaoxing, and Ningbo, employs the Super-Efficiency DEA model to assess water environment governance performance. The Tobit model analyzes external environmental factors. Findings reveal fluctuating water governance efficiency during the study period, with inefficiencies from 2012 to 2019, followed by significant improvement from 2019 to 2021. Key factors impacting governance include urban water environment performance in Hangzhou, urban residents’ disposable income, population density, and secondary industry GDP development. A higher urban income enhances environmental awareness and governance performance, while population density and industrial GDP intensify resource use, energy consumption, and wastewater discharge, worsening governance pressures and performance. This research offers insights for enhancing water environment governance in Hangzhou Bay, aiding in the formulation of protection plans and management policies. Additionally, it provides valuable experiences for watershed governance globally.

Analysis of regional differences in green energy efficiency in countries along “the Belt and Road” Initiative zone—Based on super efficiency DEA model and Malmquist index method

This study uses the super-efficiency DEA model and Malmquist index analysis to evaluate the green energy efficiency of 58 countries along “the Belt and Road” Initiative zone from 2012 to 2021 and uses Tobit regression to analyze the external environmental influences on their green energy efficiency. The results of the study show that in the static analysis, The overall green energy efficiency of 58 countries along the “the Belt and Road” initiative area is low, and there are obvious regional differences; In terms of dynamic analysis, the Malmquist Index shows a slight fluctuation trend from 2012 to 2021. Tobit regression models show that external factors such as economic strength, energy consumption structure, industrial structure, and R&D expenditure are significantly and positively related to green energy efficiency. Based on this, this study proposed that countries should make good use of their resource advantages to improve the overall green energy efficiency of “the Belt and Road” Initiative zone according to local characteristics; strengthen inter-regional cooperation and exchange among countries, and implement outbound strategies to create a favorable development environment for green energy efficiency in “the Belt and Road” Initiative zone. Create a favorable development environment for green energy efficiency in “the Belt and Road” Initiative region.

DOES ENERGY EFFICIENCY MATTER FOR POVERTY ALLEVIATION AND ECONOMIC GROWTH? A FRESH EMPIRICAL INSIGHT FROM AN ASIAN PERSPECTIVE

Globally, everybody deals with poverty as a shared societal issue. It is still unclear how to investigate its causes and create new paradigms for policy, but it offers many promising directions for academic study. The use of technological innovation in this environment for social change to address poverty reduction is also an important issue. Consequently, this study investigates how effective poverty reduction may be accomplished in Asia through technological innovation and financial development. The super-efficiency data envelopment analysis model and system generalized method of moments were utilized in the present study together with data from 2010 to 2020 for an empirical estimate. The data show that different areas have effectively reduced poverty over time. However, Asia’s overall effectiveness in reducing poverty is rather unevenly distributed geographically. The significance of poverty reduction in Asia is positively impacted by technical advancement and financial prosperity. The effects of globalization on the efficacy of poverty reduction are negligible. This study presents some policy insights for decision makers based on the empirical findings.

Effect of Fiscal Expenditure for Supporting Agriculture on Agricultural Economic Efficiency in Central China—A Case Study of Henan Province

The policy guidance and financial support for industrial development from public finance provide an important guarantee for practicing green and circular development of agriculture. By sorting out the development context of fiscal support for agriculture in Henan province in different historical stages, this paper analyzes the development status of fiscal support for agriculture and the agricultural circular economy in the province. Relying on data envelopment analysis (DEA), it measures the efficiency of the agricultural circular economy in Henan province in 2013–2019 using the Charnes, Cooper, and Rhodes (CCR) model, the Banker, Charnes, and Cooper (BCC) model, and super-efficiency DEA models and empirically analyzes the effect of the fiscal expenditure for supporting agriculture on the efficiency of the agricultural circular economy using the fixed effect model. According to the results, (1) the expenditure on comprehensive agricultural development of Henan Province was mainly supported by the government’s fiscal funds to such a degree that the proportion of fiscal funds from the central government exceeded 40% throughout the year. Particular stress was laid on the land governance projects of comprehensive agricultural development in the province. (2) The overall development level of the agricultural circular economy in Henan Province was low, and there were considerable gaps between cities (counties). Under the super-efficiency DEA model, only Hebi City, which ranked first in terms of average efficiency, achieved relative efficiency. (3) The fiscal expenditure for supporting agriculture had a positive incentive effect on the efficiency of the agricultural circular economy in Henan province, and the incentive effect became more significant after the time effect was controlled. Accordingly, this paper puts forward some targeted policy suggestions, which enrich the existing research on fiscal support for agriculture and agricultural circular economy at both theoretical and practical levels.

Design of DEA water efficiency evaluation model for cotton field irrigation in Xinjiang

Abstract Current irrigation water use efficiency assessment methods cannot accurately predict irrigation water use, leading to greater errors in water use efficiency assessment. Therefore, a new method based on data envelopment analysis (DEA) model is proposed to evaluate the irrigation water use efficiency of cotton fields in Xinjiang. The super efficiency DEA model is established by introducing the super efficiency DEA method and adjusting the predicted amount and actual amount of irrigation water use. Genetic algorithm is used to improve the super-efficiency DEA model. The indexes obtained include the indexes reflecting water resources conditions, water use situation and economic aspects, and the statistical sequence model of cotton field irrigation water information is established. Given the demand and actual usage of irrigation water for cotton fields, the numerical relationship between the demand and usage was defined by integrating the two indices as the index data set. The experimental results show that the proposed method can accurately predict the water consumption of cotton field irrigation, and the efficiency of irrigation water consumption can reach 90%.

Exploring the Measurement of Regional Forestry Eco-Efficiency and Influencing Factors in China Based on the Super-Efficient DEA-Tobit Two Stage Model

This paper adopts the super-efficient DEA (data envelopment analysis) model to measure the forestry eco-efficiency (FECO) of 30 Chinese provinces and cities from 2008 to 2021, and then introduces the Tobit model to explore the influencing factors of FECO to better understand the sustainable development level of forestry. It draws the following conclusions: (1) The average value of FECO in China is 0.504, which is still at a low level, and the FECO of each region has significant regional heterogeneity; the provinces with higher FECO are mainly concentrated in the eastern region, while the FECO of the central and western regions is lower; (2) In terms of the main factors affecting FECO in China, the regression coefficients of market-based environmental regulations are significantly positive in the national, eastern and central regions, while they are significantly negative in the western region. The coefficient of impact of scientific research funding investment on forestry industry eco-efficiency is negative and shows a significant promotion effect in the eastern region, but the elasticity coefficient in the central and western regions is negative but not significant. Economic development has a positive but insignificant effect on FECO, with the eastern region showing a positive correlation, while the central and western regions are insignificant. Industrial structure has a significant negative effect on FECO in the national, eastern and central regions, but the effect of industrial structure on FECO in the western region is not significant. The effect of foreign direct investment on FECO was negative for the national, central and western regions, but the central region did not pass the significance test, while the eastern region reflected a significant promotion effect.

Effects of Vertical Fiscal Imbalance on Fiscal Health Expenditure Efficiency-Evidence from China.

Improving fiscal health expenditure efficiency is an inherent requirement of the strategy of "healthy China" and "high-quality development". The outbreak of COVID-19 has highlighted the importance of efficient health system. First, this paper systematically sorts out the multiple theoretical mechanisms of the positive and negative relationship between vertical fiscal imbalance and fiscal health expenditure efficiency. Secondly, a comprehensive index system, including the quantity and quality of medical services, is constructed, and the super-efficiency DEA model is used to measure fiscal health expenditure efficiency. There are obvious differences between eastern and western regions. Finally, the fixed effect model is constructed to carry out empirical research and it is found that the vertical fiscal imbalance in China has an overall positive and significant impact on the fiscal health expenditure efficiency, which is mainly achieved by optimizing the resources allocation between primary medical institutions and hospitals. Heterogeneity analysis shows that transfer payment scale has a corrective effect on the vertical fiscal imbalance's effect. The result of quantile regression shows that the impact of vertical fiscal imbalance is not constant, and it gradually turns from positive to negative along with the improvement of fiscal health expenditure efficiency.

Analyzing Efficiency and Productivity Changes of Turkish Textile Firms

This study addresses the analyzing of efficiency and productivity change of 19 Turkish textile firms for the period 2014-2020 which are quoted to stock market. For the efficiency analysis super-efficiency DEA model is employed which contains three inputs and two outputs. The efficiency results are given in yearly base. For productivity analysis stage Malmquist Productivity Index is used including TECI, TCI and TFPI values. According to results, none of the firms increased their total factor productivity through 2014 to 2020. Furthermore, there isn’t any significant difference between the average of efficiency, TECI, TCI and TFPI values before and during COVID-19 pandemic. This study contributes to the literature with covering seven-year period including COVID-19 pandemic period in the analyses.

Micro-depots site selection for last-mile delivery, considering the needs of post-pandemic parcel recipients

The pandemic has changed consumer habits, leading to an increase in parcel delivery and changing consumer requirements. Last-mile delivery has become more important than ever. Parcel delivery providers face a major challenge, as research shows that many consumers will maintain the same shopping habits as during the pandemic. It is, therefore, necessary to find sustainable and not just short-term solutions for the last-mile delivery. Identifying suitable locations for micro-depots in urban areas and delivery with e-cargo bicycles can be one of them. This article has two objectives: (1) to determine whether the changes brought by Covid-19 affect the selection of the appropriate micro-depot site and to what extent; and (2) whether the extension of the Analytical Hierarchy Process (AHP) by evaluating the technical efficiency of micro-depo sites locations changes the ranking of most favourable locations and to what extent. We first gathered existing criteria for selecting a suitable micro-depot location through a literature review. Then, a qualitative and quantitative analysis were performed to check suitability of criteria and complement the current set of criteria with potential new criteria resulting from Covid-19. A real numerical example of one of the past researches was selected to perform Delphi and super-efficiency Data Envelopment Analysis (DEA) analysis. Results of Delphi analysis, where the AHP was applied, revealed that Covid-19 had not affected the type of stakeholders' demands (city administration, citizens and logistics companies) taken into account, but their importance. However, upgrading the AHP with a super-efficient DEA model has completely changed the order of the most relevant micro-depot locations.

Research on Development Efficiency of Circular Economy of Silk Road Economic Belt: Based on Super Efficiency DEA Model

Research on Development Efficiency of Circular Economy of Silk Road Economic Belt: Based on Super Efficiency DEA Model

基于碳排放约束的北京市社区生态效率评价

PDF HTML阅读 XML下载 导出引用 引用提醒 基于碳排放约束的北京市社区生态效率评价 DOI: 10.5846/stxb202202170373 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学青年基金项目（72004215）；国家自然科学青年基金项目（72104223） Evaluation of community's ecological efficiency in Beijing based on carbon emission constraint Author: Affiliation: Fund Project: National Natural Science Foundation of China(72004215);National Natural Science Foundation of China(72104223) 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:在"双碳目标"的背景下，社区作为生态文明建设的基本单元，其碳排放核算及生态效率评估尤为重要。基于家庭消费视角，采用碳排放系数法和消费者生活方式法核算社区居民碳排放，并运用超效率DEA模型评估社区生态效率，最后通过计量分析识别生态效率影响因素。研究结果显示：（1）社区居民人均碳排放的评估结果呈现出商品房社区（528.85kgCO2/月）>单位社区（475.66kgCO2/月）>传统社区（368.33kgCO2/月）的关系；（2）生态效率的评估结果呈现出传统社区（111.04%）>商品房社区（108.78%）>单位社区（105.70%）的关系；（3）社区管理工作参与意愿、家庭光照条件会对社区生态效率产生积极影响；此外，年龄结构（中青年人口占比）对商品房社区的生态效率有消极影响，受教育程度的提升则会提高生态效率。进一步提出针对三类社区特点的转型发展策略，为全国不同类型社区生态转型和绿色低碳发展提供参考范式和决策支持。 Abstract:In the context of dual carbon goal, as the basic unit of urban and rural ecological civilization construction, community carbon emission accounting and ecological efficiency evaluation are particularly important. From the perspective of household consumption, this paper adopts the carbon emission coefficient method and consumer lifestyle method to calculate the carbon emission of community residents, and uses the super-efficiency DEA model to evaluate the community ecological efficiency, and finally identifies the influencing factors of ecological efficiency through econometric analysis. The results showed that:(1) the per capita carbon emission of community residents indicated the order of commercial housing community (528.85 kgCO2/month) > unit community (475.66 kgCO2/month) > traditional community (368.33 kgCO2/month); (2) The ecological efficiency presented the traditional community (111.04%) > commercial housing community (108.78%) > unit community (105.70%); (3) Willingness to participate in community management and household lighting conditions had positive effects on community ecological efficiency. In addition, the age structure (the proportion of young and middle-aged population) had a negative impact on the ecological efficiency of commercial housing communities, while the improvement of education level would improve the ecological efficiency. Furthermore, the transformational development strategies based on the characteristics of the three types of communities were proposed to provide a reference paradigm and decision support for the ecological transformation and low-carbon development of different types of communities in China. 参考文献 相似文献 引证文献

Health System Efficiency of OECD Countries with Data Envelopment Analysis

Purpose: This study is aimed at measuring the efficiency of 37 OECD countries for 2020 using the Data Envelopment Analysis (DEA) method. Besides, it is aimed at ranking the efficient decision making units by using the super-efficiency DEA model. Design/methodology/approach: In the study, analyses were carried out with input-oriented Charnes, Cooper and Rhodes (CCR), input-oriented Banker, Charnes and Cooper (BCC) models and super-efficiency models of these models by using 4 inputs and 3 outputs. Findings: As a result of the analysis, 14 countries in the CCR model and 20 countries in the BCC model were efficient. According to the results of the super-efficiency models, the efficient countries were ranked. Research limitations/implications: The limitations of the study are the analyses are based on input-oriented DEA models and the research was conducted in OECD countries. Originality/value: Performance evaluation of health systems has gained importance in recent years. Many countries are making efforts to improve their health systems. Due to epidemics such as COVID-19, OECD countries, like many countries around the world, have increased the share of health expenditures in GDP. Because of this situation, the evaluation of the performance of OECD countries in the field of health has emerged as a very important research topic.

A Study on the Spatial–Temporal Evolution of Innovation Efficiency in Chinese Universities in the Context of the Digital Economy

With the rapid development of knowledge and the digital economy, it is a crucial to understand the role of the digital economy in improving the innovation efficiency of universities. Using the panel data of universities in 31 Chinese provinces from 2013 to 2020, this paper measures the regional innovation efficiency of Chinese universities and examines the impact of the digital economy on universities’ innovation by employing the super-efficiency DEA model along with the Malmquist index, kernel density estimation and Theil index. The analysis shows the following: (1) The digital economy has a significant positive impact on the efficiency of university innovation, but there is still much room for improvement. (2) In terms of the dynamic evolution of innovation efficiency, Chinese university performance shows a trend toward declining innovation efficiency, and the issue of inadequate investment in technical innovation is discovered, which urgently needs to be addressed. The findings of this paper offer empirical support for understanding the relationship between digital economy growth and university innovation productivity with important ramifications for the innovative expansion of higher education institutions in emerging nations.

Research on the Impact of Environmental Regulation on Total Factor Energy Effect of Logistics Industry from the Perspective of Green Development

This study uses the super efficiency DEA model to evaluate the logistics industry’s total factor energy efficiency in various Chinese provinces, autonomous regions, and municipalities, and examines the relationship between environmental regulations and the total factor energy efficiency. The results show that environmental regulations can help improve the logistics industry’s total factor energy efficiency. This study further analyzes the threshold effect of environmental pollution control investment level, quality of labor, and logistics industry development level in environmental regulations on the logistics industry’s total factor energy efficiency. The results showed that the level of investment in environmental pollution control in environmental regulations has a significant single threshold effect on logistics industry’s total factor energy efficiency. The quality of labor has a significant double threshold effect on environmental regulation’s impact on the logistics industry’s total factor energy efficiency. Logistics industry development level has a significant double threshold effect on the impact of environmental regulation on logistics industry’s total factor energy efficiency.