Data Envelopment Analysis Research Articles

Research on energy efficiency and carbon efficiency evaluation for copper metallurgy based on data envelopment analysis

Research on energy efficiency and carbon efficiency evaluation for copper metallurgy based on data envelopment analysis

The effect of subsidies and reform options on profit efficiency of trout farms: Focus on energy subsidies

Energy and imported trout egg subsidies hold a pivotal role for Iranian trout farms. They aim to decrease production costs, yet their impact on the profit efficiency of farms remains dubious. The first objective of this paper is to assess how the current subsidy scheme affects the profit efficiency of hatchery and propagation trout farms in Mazandaran, Iran. We examine several subsidy reform scenarios to enhance profit efficiency as a second objective. Standard profit efficiency (SPE) is used to acquire the efficiency of the trout farms using data envelopment analysis. Results show that the majority of farms are inefficient and highly dependent on subsidies. Comparing farms with high efficiency against those with low efficiency as a third aim of research highlights the importance of farms holding a propagation license, engaging in vertical integration, achieving adult trout production surpassing 81 t, and maintaining a fish total feed consumption to trout production ratio below 0.74. Findings from reformation scenarios reveal 1) redirecting the current subsidy towards purchasing the extruder machines for fish feed production, 2) transferring funds to subsidize electricity based on the farm's electricity consumption, and 3) opting for the production of genetically modified eggs gives higher SPE. Reformation can also reduce the burden on public funds and dependency on importation.

Product tracing or component tracing? Blockchain adoption in a two-echelon supply chain management

Consumer awareness of product authenticity and carbon footprint tracing are among the most remarkable reasons for adopting blockchain in the supply chain in today’s world. However, the research literature has not yet examined specific ways to adopt blockchain in the supply chain. This study aims to develop a decision support tool to deal with the adoption of blockchain technology to design a two-echelon supply chain. In this regard, four specific cases for integrating supply chain and blockchain are developed based on types of tracing and block generation authority. In product tracing, green products are investigated throughout the supply chain, while in component tracing, green products are examined between the components of the supply chain. As it is necessary to record and verify the supply chain information by authorities in the blockchain network, in this work, such authorities are taken into account for both links and members of the supply chain. As far as we know, this is the first attempt to classify the various methods of adopting blockchain in Green Supply Chain Management (GSCM) and propose mathematical optimization models related to them. In this line, four Mixed-Integer Linear Programming (MILP) models with the aim of minimizing the costs related to the physical supply chain and blockchain deployment are developed for the integration of the supply chain with blockchain technology. They are treated by the Branch and Efficiency (B&E) algorithm and Simultaneous Data Envelopment Analysis (SDEA) model considering common (cost and service) and innovative (blockchain) criteria. The results showed that link-based and component tracing models are cost-effective. In addition, the cost objective function of green product tracing is more sensitive to the number of blocks than that of component tracing. Eventually, the study provides great opportunities for decision-makers and managers to understand how to adopt blockchain in terms of supply chain network characteristics, cost, transparency, and service.

Research efficiency in Chilean universities: A look from data envelopment analysis

Research efficiency in Chilean universities: A look from data envelopment analysis

Sequential data envelopment analysis: decentralization and solutions for panel data

Sequential data envelopment analysis: decentralization and solutions for panel data

Based on the New Dynamic Network DEA and Malmquist Index of High-Quality Innovation in the New Energy Vehicle Economy Development Research of the Internet of Things

This paper takes the enterprise economic data of new energy vehicles (NEVs) in 2018–2023 as the research background, combined with the performance evaluation theory of the NEV industry, and systematically discusses how to make the high-quality innovative development of NEVs as the research purpose. We use the new dynamic network data envelope analysis (DEA) model, Marmquist Index and other and the Internet of Things internationally recognized, scientific and effective data models as research methods to make an in-depth analysis of the business performance of five representative enterprises on multi-quantitative input-output issues. The research results show that the NEV industry has a good development prospect and economic foundation on the whole, but it still faces challenges such as limited space for core technology progress, insufficient carbon emission reduction and environmental protection planning. At the end, this paper puts forward innovation suggestions such as accelerating technological innovation, optimizing production process and responding to preferential policies and exploring international market.

Comparative Economic Analysis Between Bioenergy and Forage Types of Switchgrass for Sustainable Biofuel Feedstock Production: A Data Envelopment Analysis and Cost–Benefit Analysis Approach

ABSTRACTThe capacity to produce switchgrass efficiently and cost‐effectively across diverse environments can be pivotal in achieving the short‐ and medium‐term Sustainable Aviation Fuel targets set by the U.S. Department of Energy. This study evaluated the economic performance of forage‐ and bioenergy‐type switchgrass cultivars and their response to N fertilization under diverse marginal environments across the US Midwest that included Illinois (IL), Iowa (IA), Nebraska (NE), and South Dakota (SD). Data Envelopment Analysis (DEA) was used to evaluate the efficiency of 23 Decision‐Making Units (DMUs)—cultivar types and N fertilization rate combinations—while a cost–benefit analysis calculated their profitability over 5 years. Results showed that two energy‐type cultivars—“Independence” and “Liberty”—were superior economically to the forage cultivars. Independence performed best with the highest profit margin when fertilized at 56 kg N ha−1, particularly in the US hardiness zone 6a (Urbana, IL). Liberty exhibited the highest profit margins in hardiness zone 5b (Madrid, IA, and Ithaca, NE) at 56 kg N ha−1 and showed exceptional profitability with 28 kg N ha−1 in hardiness zone 6b (Brighton, IL). Switchgrass cultivar “Carthage” showed better efficiency score and profitability results in hardiness zone 4b (South Shore, SD) at 56 kg N ha−1. The profit trends observed in current study sites may indicate broader patterns across similar US hardiness zones. This study provides valuable insights for decision‐makers to optimize input strategies for biomass production of bioenergy switchgrass to meet renewable energy demands.

Factors Influencing Technical Efficiency of the Rice (Oryza sativa) Farming

Increasing production and productivity, primarily done in the rice production centers, is the main focus to reduce the rate of rice imports in Indonesia. Measuring technical efficiency and analyzing factors influencing of rice farming is important in order to achieve maximum production and to obtain maximum profits. This study aims to determine the level of technical efficiency of rice farming analyze factors affecting rice farming. The research location was chosen purposively in Kedungadem, Kalitidu, and Kapas Districts with a sample of 150 rice farmers using simple random sampling. The analytical methods used Data Envelopment Analysis (DEA) with the Variable Return to Scale (VRS) model to measure technical efficiency, while tobit regression analysis to identify factors affecting technical efficiency, and farm income analysis. The research results indicate that the factors significantly affecting technical efficiency are land size, level of formal education, farming experience, and land ownership status. The technical efficiency level of rice farming in the study areas, assessed using the DEA approach under the VRS assumption, was classified to be moderate efficient. However, rice farming in the study sites can be considered as profitable. Keywords: Education, Land ownership, Land size, Variable Return to Scale (VRS).

Equity and efficiency of public health resource allocation in China

ObjectiveTo analyze the equity and efficiency of public health resource allocation in China from 2018 to 2022, and to provide a scientific basis for promoting the development of public health resources in China.MethodsData on public health resources of 31 provincial-level administrative regions in mainland China were extracted from 2018 to 2022, and descriptive analysis, Theil index, and health resource agglomeration degree (HRAD) were used to analyze the equity, and data envelopment analysis (DEA) was used to analyze the efficiency.ResultsThe Theil index of public health resource allocation by population in China ranges from 0.006 to 0.049, and the Theil index contribution rate of the number of beds, health technicians, licensed (assistant) physicians, and registered nurses within region is less than 28.76%. The Theil index of public health resource allocation by geography in China ranges from 0.274 to 0.624, and the Theil index contribution rate of the number of institutions, the number of beds, health technicians, licensed (assistant) physicians, and registered nurses within region is more than 77.05%. The HRAD of public health resources is more than 2.18 in the eastern and central regions, while the HRAD of public health resources is less than 1 in the northeastern and western regions. The overall HRAD/population agglomeration degree (PAD) is less than 1 in the northeastern and eastern regions, and greater than 1 in the central and western regions overall. The scale efficiency and overall efficiency of public health resource allocation in China are not 1, the returns to scale are decreasing, and the DEA is relatively ineffective from 2019 to 2022.ConclusionThe equity by geography is slightly worse than the equity by population, and the inequity by population mainly comes from between regions, while the inequity by geography mainly comes from within regions. There is a contradiction in the equity by population and by geography allocation in the eastern and western regions, and a congruence in the equity by population and by geography allocation in the northeastern and central regions. The DEA of public health resource allocation in China is relatively ineffective in 2019–2022.

Sensitivity assessment of cost allocative efficiency in data envelopment analysis

Nonparametric cost allocative efficiency models in the framework of data envelopment analysis are sensitive to the prices of inputs. Changes in input prices may change the efficiency classification of a decision-making unit. In this sense, it is of interest to determine the ranges for input prices in which the efficiency classification remains unchanged. This paper focuses on sensitivity analysis of cost efficiency of a specific allocative efficient firm. Cost stability region is defined as a region in which the efficiency classification does not change if the input-cost vector is changed in such a way that the new vector belongs to this region. Linearly independent supporting surfaces of the production possibility set are used to define this region. The proposed cost stability regions are used to discriminate the decision-making units. Two illustrative examples (one simple numerical example and one real example) are used to demonstrate the applicability of the proposed approach.

Efficiency of Air Transport Industry in European Union Nations with Regard to Environmental Factors

Purpose: Evaluating the effectiveness of nations by analyzing the relationship between the outcomes of the aviation sector and the environmental resources associated with these outcomes is essential for policymakers to develop environmental regulations and for managers to take suitable actions. This study aims to evaluate the environmental effectiveness of the airline industry in European Union (EU) member states. Methodology: We assessed the efficiency of data from 26 EU countries using Data Envelopment Analysis. Findings: The study's findings determined that Austria, Luxembourg, Hungary, and Ireland had the lowest efficiency levels. Air pollution and greenhouse gas emissions primarily influence the efficiency of these countries. We identify Germany as the least efficient country, specifically when compared to France and Italy. These findings indicate that, despite the EU's implementation of environmental impact legislation, developed member states have not successfully enforced it. Originality: Previous research has not examined the effectiveness of countries in terms of both passenger and flight volumes, as well as environmental considerations such as air pollution, greenhouse gas emissions, kerosene and jet fuel use, energy products, and overall environmental taxation

How to Improve the Efficiency of the New Energy Vehicle Industry: Multiple Paths From Configuration Perspective

ABSTRACTThis study examines regional new energy vehicle (NEV) industry efficiency across 26 Chinese provinces, addressing the need for deeper insights into the spatiotemporal efficiency patterns and configurational pathways influencing NEV development. By employing data envelopment analysis (DEA) to measure efficiency, exploratory spatial data analysis (ESDA) to explore spatial clustering, and fuzzy‐set qualitative comparative analysis (fsQCA) to investigate configuration‐based pathways, this research provides a nuanced understanding of how regional factors shape NEV efficiency. The analysis identifies four distinct configurational pathways: policy bolstering for technological innovation, organizational synergy, market dynamics and regulatory synergy, and structural deficiency type. These findings suggest that developed regions benefit from prioritizing organizational collaboration and technological support, while less‐developed areas may improve efficiency through foundational policy enhancement and regulatory alignment. Furthermore, investing in human capital, technical innovation, and infrastructure can contribute to building a resilient NEV ecosystem. By integrating multiple analytical methods, this study sheds light on the complex interactions shaping NEV efficiency across regions and offers insights for policymakers to enhance the global competitiveness and sustainability of China's NEV industry.

Optimising efficiency and patient-centredness in general hospitals: insights from data envelopment and matrix analysis.

Medical institutions face management challenges from intense competition and an unclear link between patient-centredness and profitability. This study examined the association between efficiency and patient-centredness in general hospitals and identified management strategies to optimise both. Data from the 2021 patient experience evaluation by the Health Insurance Review and Assessment Service and financial statements from the Korea Health Industry Development Institute for general hospitals in South Korea were used. Efficiency scores and patient-centredness were determined for 256 general hospitals using data envelopment analysis (DEA), and their relationships were analysed through matrix analysis. The Kruskal-Wallis and Mann-Whitney tests assessed group differences identified through matrix analysis. Efficiency and patient-centredness can be improved concurrently. Hospitals in the highest efficiency group reported significantly higher average inpatient revenue per 100 beds (179.67) and net profit (158.84) than those in lower-performing groups (p<0.001). Optimal management of hospital beds and specialised diagnostic equipment per 100 beds was associated with higher efficiency scores, while a greater number of doctors and nurses positively influenced patient-centredness metrics. Therefore, general hospitals should invest in personnel and resources to enhance efficiency and patient-centredness, achieving optimal financial and operational outcomes. This study combines DEA and matrix analysis to explore the link between hospital efficiency and patient-centredness, using recent data on patient experience and financials from South Korean hospitals. It identifies strategies to enhance both dimensions.

Unlocking financial inclusion: Indian banks' efficiency in Pradhan Mantri Jan-Dhan Yojana explored through DEA

PurposeFinancial inclusion is a prerequisite for inclusive development. In 2014, the Indian Government introduced the Pradhan Mantri Jan-Dhan Yojana (PMJDY) with a similar objective. The study aims to analyse the effectiveness of banks in the implementation of financial inclusion policy, i.e. PMJDY.Design/methodology/approachTo evaluate the effectiveness of Indian banks, the study used the data over a seven-year period, from 2014–2015 to 2020–2021. Data are analysed by using the data envelopment analysis technique.FindingsThe study discovered that public sector banks performed better than private sector banks (PVBs) in terms of boosting financial inclusion under the PMJDY scheme. In terms of implementing the PMJDY programme, the State Bank of India rated first.Practical implicationsResults recommended that policymakers set goals for banks. In order to encourage consumers to utilise their accounts, banks ought to introduce supplementary financial products and implement incentive programs.Originality/valueThe study is the first of its kind to measure the performance of Indian banks in the implementation of the PMJDY scheme.

Evaluation of agricultural efficiency and influencing factors in the context of sustainable land management

Given the growing global focus on sustainable development, sustainable land management has emerged as a critical concern in contemporary agricultural development. The efficacy of agricultural production and its influencing factors in Shaanxi province of China, from 2012 to 2021, were analyzed using the Data envelopment analysis (DEA)-Banker, Charnes, Cooper model. Input and output indicators of agricultural production were selected for analysis. Inputs consist of land, machinery, water, and fertilizer. Specific indicators include the total sown area of crops, effective irrigated area, total power of agricultural machinery, and total reservoir capacity. Fertilizer inputs include the discounted amount of fertilizer applied for agricultural use. The output indicators considered include the gross output value of agriculture, forestry, animal husbandry, and fishery, the economic value added from agricultural production, and the production of cereal and fruit are all considered output indicators. From 2012 to 2018, the scale remuneration of agricultural production in Shaanxi province increased, suggesting gradual improvement in scale efficiency. Conversely, the efficiency of agricultural production has remained at the &amp;ldquo;DEA strong efficient&amp;rdquo; level from 2019 to 2021, suggesting effective management of scale efficiency. The investigation indicates that the allocation of resources and the administration of agricultural production in Shaanxi province have improved in recent years, contributing to the fostering of sustainable agricultural development.

A novel method of assessing port resilience and its positive ramifications

ABSTRACT Ports play a crucial role in facilitating global trade and logistics, serving as vital hubs that connect countries and continents. However, they are susceptible to disruptions and disasters due to their natural characteristics, while their resilience is essential for maintaining regular operations, especially in the face of disruptions. From the perspective of inputs and outputs, this study evaluates the resilience of nine major Chinese ports from 2011 to 2021, using super-efficiency slacks-based measure network data envelopment analysis (SBM-NDEA). This approach extends beyond evaluating a port’s internal capacities, incorporating urban and economic factors that are critical to ensuring the port’s long-term resilience. The novel method for assessing port resilience and its positive ramifications offers a clearer understanding of the specific stages requiring improvement, thereby enhancing the overall resilience of ports. Specifically, three stages of port resilience are considered: absorptive, adaptive, and restorative. The results reveal that the resilience of different ports exhibits distinct trends in the above three stages. Shenzhen Port demonstrates superior performance in both absorptive and adaptive stages, while Rizhao Port excels in the restorative stage. The research contributes to advancing both academic knowledge and industry practices by offering new insights, methodologies, and practical implications for enhancing port resilience.

Does multiple job holding raise labour use efficiency of the farm operators? Evidence from rural India

ABSTRACT Amid various agro-climatic shocks when farm income becomes volatile, farmers often diversify income by holding multiple non-farm jobs. While the impact of multiple jobholding on overall farm efficiency is documented in literature, very little is known about the impact of multiple job holding on farm labour use efficiency. This is important as participation in non-farm activities alters farmers’ labour allocation decisions between farm and non-farm activities. Using a rich household level panel data from eight Indian states for the period 2010–2014 from Village Dynamics in South Asia (VDSA) Project by International Crops Research Institute for the Semi-Arid Tropics and adopting Data Envelopment Analysis, we estimate labour use efficiency. Our Instrumental Variable Tobit estimation shows that multiple job holding increases farm operators’ labour use efficiency significantly. However, the heterogeneity analysis using sub samples demonstrates that the positive impact of multiple non-farm jobs is enjoyed mostly by medium and large farmers. Also, farmers engaged in wage and salary based non-farm employment experience higher labour efficiency once they hold multiple jobs. Self-employed farmers experience higher labour efficiency only if they earn a threshold level of non-farm income. Since multiple job holding improves farm labour use efficiency, more avenues for non-farm employment to be created for agricultural and rural development.

Developing Agility, Resilience, and Circular Economy Decision-Making Model Based on Data Envelopment Analysis for Evaluating Medical Equipment Suppliers

Developing Agility, Resilience, and Circular Economy Decision-Making Model Based on Data Envelopment Analysis for Evaluating Medical Equipment Suppliers

Optimization of environmental and energy performance of egg production using data envelopment analysis (DEA) and life cycle assessment (LCA).

Intensive farming systems can present different environmental concerns. Among the many animal products, eggs are consumed globally as a cheap, valuable source of protein. Iran is among the top 10 egg producing countries in the world. However, the environmental impact of egg production in Iran is scarcely investigated. This study aims to optimize the environmental and energy performance of egg production in Iran. It utilizes the eco-efficiency method, which combines Data Envelopment Analysis (DEA) and Life Cycle Assessment (LCA). To this purpose, data from 14 pullet breeding farms and 40 egg production farms were collected through in-person questionnaires. The energy performance of egg production is mainly related to the consumption of feed, electricity, and fuel, as well as to the use of equipment. The average energy inputs for pullet breeding and egg production were 270,283.06MJ (per 1000 pullets) and 1,606,307MJ (per 1000 laying hens), respectively. Improved management can save 105,190MJ of energy per 1000 laying hens without compromising output performance. The greatest potential for reducing energy consumption lies in inputs such as fuel and feed. The eco-efficiency method demonstrated that improved management can reduce environmental impact by 5-7%. Through optimization, global warming decreased from 4.40 to 4.13kg CO2 equivalents per kg of egg. For the evaluated impact categories, feed input showed the greatest contribution to environmental impact.

Assessing the Impact of China’s Industry on Health: A Dynamic Three-Stage Bootstrap Model with an Endogenous Fuzzy Directional Distance Function

Evaluating the industrial eco-system is essential for promoting resource efficiency, environmental development, and public health protection. However, traditional Data Envelopment Analysis (DEA) methods are prone to biases and rely on precise numerical values, which pose significant challenges when evaluating the industrial ecosystem in China, particularly given the prevalent data uncertainties and environmental complexities. Additionally, DEA models are typically static, fail to capture the long-term trends and dynamic characteristics of the industrial ecosystem. To address these issues, this study proposes a dynamic three-stage model with an endogenous fuzzy directional distance function. The model integrates the generalized smooth bootstrap method and fuzzy comparison techniques to correct errors and account for data uncertainties, improving the accuracy and scientific validity of eco-efficiency assessments. Chinese enterprises face challenges such as excessive resource consumption, environmental pollution, and health risks, necessitating a more comprehensive and flexible evaluation system to adapt to the complex and dynamic nature of the industrial ecosystem. By focusing on industrial production, environmental governance, and health threats (IPEGHT) in China, the research aims to provide a robust framework for enhancing industrial eco-efficiency in a dynamic and uncertain environment. The results show: (1) The proposed method for selecting endogenous direction vectors is applied to the industrial production stage, thereby identifying the subsequent improvement directions for industrial production in various provinces. (2) The idea of integration is adopted to introduce the generalized smooth bootstrap method and fuzzy mathematics, to conduct a precise and comprehensive evaluation of the IPEGHT industrial eco-system. (3) From 2011 to 2021, China’s IPEGHT industrial eco-system efficiency showed a step-like distribution, and attention needs to be paid to environmental governance. The proposed method’ application can facilitate the integration of DEA and fuzzy mathematics, and fosters a more sustainable industrial eco-system.