Network Data Envelopment Analysis in the Electric Power Industry: A Systematic Literature Review Using PRISMA

When the number of Decision-Making Units (DMUs) is not large enough compared to the total number of input parameters and outputs, traditional Data Envelopment Analysis (DEA) and Network Data Envelopment Analysis (NDEA) models often produce solutions that identify many DMUs as efficient, in addition to obtaining unrealistic weight distributions. In fact, this poor discrimination power and unrealistic weight distribution presented by DEA and NDEA models remain a major challenge, leading to the development of models to improve this performance. Thus, this paper proposes a Multiple Criteria Network Data Envelopment Analysis (MCNDEA), based on relational NDEA models. The idea of this model is to be used in network structures. To test the MCNDEA model, one a real instance linked to an evaluation problem of academic departments of a public university was used. Other instances were also used to validate the proposed MCNDEA, and these tests are included in the supplementary files. Finally, it should be noted that, in summary, the model proposed in this article had greater discrimination power of the analyzed DMUs, being able to identify the most efficient departments in each of the considered stages, besides pointing out to the University Management points of improvement regarding the best use of its resources for each department.

Food security is a global challenge. With rising world population and demand for food being compounded by resource and arable land constraints, raising the efficiency of food production and use has become increasingly important. While much of the research on food security is focused on farm efficiency and productivity, most neglect post-harvest (PH) handling which is critical in determining the availability of food. In this study, we employ the network Data Envelopment Analysis (DEA) model to evaluate the PH efficiency of milling, using data from Kenya’s rice processing industry. The results show lower efficiency scores when using a network DEA model, which reflects its greater discriminatory power when compared to the standard DEA approach. The study also quantified sources of productive efficiency using a fractional regression model and identified storage space and distance to market as having an impact on drying efficiency; while experience, age of mill, servicing and energy type influenced milling efficiency. The results suggest that policy makers should focus on investing in drying technologies and storage facilities to improve drying efficiency. To improve milling efficiency, policy recommendations include enhancing millers’ access to better technologies, investing in reliable sources of energy and providing PH handling workshops to reduce PH losses.

This paper deals with urban sustainable development in China. We propose a network data envelopment analysis (DEA) model with a slack-based measure (SBM) to analyze the eco-efficiency of 284 Chinese cities, enabling us to find a way to open the “black box” in conventional DEA models and introduce social well-being factors into the model, and depict the role of local government in providing public service and improving social well-beings. We set up a framework of urban development by dividing the process of into two steps. The first stage is a production system translating inputs and natural resources into GDP and waste production, which will be inputs to the second stage for distribution and consumption to realize social welfare and environmental protection. The results show eco-efficiency of Chinese cities experienced a significant decrease from 2005 to 2016, which should be mainly attributed to the distribution and consumption processes. Structural differences are described by regions, administrative level and clusters. These results are compared with an existing urban sustainability index system developed by McKinsey and an ANOVA approach is conducted to reveal differences between cities across regions and clusters. This article sheds new light on the understanding of urban sustainable construction and development in China regarding the service performance of local government.

Accurate measurement of regional efficiency is a prerequisite for effective management. Prior studies have expanded on the overall "black box" evaluation with two stages of research and development (R&D) and commercialization, opening up the internal structure of the regional innovation process, but ignoring the independent innovation activities of universities, research institutes, and firms in the R&D stage. We construct a mixed structure with two stages, three actors, and four subsystems, and conduct an empirical analysis of China's provincial samples from 2017 to 2019 by using the network data envelopment analysis (DEA) model. Results show that the efficiency of the R&D stage at the provincial level is generally higher than that of the commercialization stage. However, the three subsystems of the R&D stage perform poorly. Spearman’s rank correlation coefficient suggests that there is a significantly positive correlation between total regional efficiency and commercialization. In addition, we use the k-means method to divide 27 provinces into three clusters, setting a more appropriate improvement benchmark for inefficient provinces. Based on enlightenment of regional tobacco industry, we put forward some proposals for specific stage and specific subsystem.

Assessing the performance of tourism supply chains by using the hybrid network data envelopment analysis model

Energy efficiency of China's industry sector: An adjusted network DEA (data envelopment analysis)-based decomposition analysis

An efficiency measurement model of a university faculty is proposed with additional new sub-functions that produce new output variables, based on the network Data Envelopment Analysis (DEA) model for systems with a hierarchical structure.For production systems composed of hierarchical processes, the system efficiency is well represented as the aggregated performance of the components involved in the system. It is identified that the conventional DEA model ignores internal process activities in a university. Therefore, an improved DEA model based on a network structure that accounts for more activities in a university is proposed to measure its overall efficiency. The impact of major functions of a university are taken into account to represent the output variables in assessing the efficiency. Currently, collaboration activities have been given more attention, so, this variable is suggested as a new output for the hierarchical production system. In order to show the practicality of the model, a hypothetical set of data of 14 faculties has been used as a numerical example. The results show that none of the faculties is relatively efficient since its functions were found to be inefficient. The proposed model enables to help the management of university faculties to identify weaknesses of each function and thus to plan for suitable actions on improving the overall performance of the university.

Urban health efficiency is influenced by both urban planning decisions and the functioning of the public health system. However, there is currently a lack of effective methods to simultaneously examine urban planning and public health when assessing urban health efficiency. This study proposes a two-stage network data envelopment analysis (DEA) model for evaluating urban health efficiency. The urban planning and public health sectors act as interconnected stages where the public facilities and living quality are mediating variables. The urban health efficiencies of 303 Japanese cities are examined using the proposed model, showing that most Japanese cities still have room for urban planning improvement with pure technical efficiency ranging between 0.7 and 0.9. At the same time, most public health sectors of Japanese cities reach pure technical efficiencies larger than 0.95 but are limited by the scale efficiency. Further analysis points out that public health sectors are in decreasing-return-to-scale, meaning that excessive urban scale adversely affects urban health efficiency. Furthermore, cities that joined the Alliance for Healthy Cities (AFHC) performed better on average, suggesting that information sharing and national and international networking can boost urban health. The study shows that the proposed two-stage network DEA model can be applied to analyze urban health efficiency and identify the impact of technology and urban scale in different stages.

In order to measure the efficiency of systems composed of several processes more appropriately, various network data envelopment analysis (DEA) models have been developed. One type of the model, which is able to calculate the system and process efficiencies at the same time, is relational. This paper discusses the relationship between the system and process efficiencies measured from this model, and derives five properties. The first is general to all types of network structure, which states that the efficiency slack of the system is the sum of those of the component processes. This implies that a system is efficient if and only if all its component processes are. The second to fourth correspond to three types of structure, series, parallel, and dynamic. The last states that any unstructured system can be transformed into a series of parallel structures for efficiency decomposition. Numerical examples are used to help explain the idea of each type of decomposition. Efficiency decomposition enables decision makers to identify the processes that cause the inefficiency of a system, and thus to make effective changes to it.KeywordsData envelopment analysisNetworkEfficiency decompositionRelational model

Due to the competitiveness of banking industry and increasing bargaining power of customers, evaluation of the banks’ performance is crucial to better serve the classified customers in a universal system .In this paper, with consideration of segmenting the customers into personal and business ones, methods such as confirmatory factor analysis (CFA) and structural equation model (SEM) have been used in selecting appropriate variables of the network data envelopment analysis (NDEA) model based on network slacks-based measure and consideration of the undesirable variables and shared resources. The SEM model has been used to establish a proper connection between the different dimension of the NDEA model and CFA model has been used to identify the importance of each dimension. Also, the proposed model has been used to measure the Operational and decomposed universal efficiency of one of the Iranian bank branches (Day Bank). The results show that the extracted model provides managers with a suitable perspective in adopting appropriate policies to promote their performance in the different sectors, including deposit attraction, financial serving personal and business banking customers, and profit generation, and also in comparing them in the different dimensions of the model.

The mainstream of development of enterprises in the electric power industry is decentralization, the development of renewable energy sources, the active role of consumers, innovations and ensuring the country's energy independence, which are constantly changing and require constant monitoring and analysis. The article is aimed at highlighting the results of the study of the mainstream development of enterprises in the electric power industry. Methods used in the study: chorological, classification, detailing and generalization, grouping, complex, tabular, etc. The hypothesis of the study was the assumption that the mainstream development of enterprises in the electric power industry is transformed due to changes in history, leaders, determinants and tools. Presentation of the main material. Based on the results of scientific research of the mainstream development of enterprises in the electric power industry, the key economic aspects of their functioning have been identified, the history of the development of the electric power industry has been analyzed, and energy efficiency as one of the determining determinants of the energy complex and the Energy Strategy of Ukraine until 2050 has been outlined. The essence of the concepts of "energy saving" and "energy efficiency" has been clarified and leaders of the energy complex of Ukraine in 2023, which made it possible to form a rating of the most successful companies in the energy sector, which included five leading enterprises owned by the state, but only two managed to increase their income. In terms of management and ownership, the Ukrainian energy system consists of main power lines and generation capacities. The article classifies the types of economic activity according to the Classification of Economic Activities, which covers the supply of electricity, natural gas, steam, hot water and other energy resources through permanent infrastructure — power lines, cable networks, gas pipelines and water pipelines. Ukraine continues to actively implement the Classification of Economic Activities aimed at unifying the classification of industries, which contributes to better interaction between different sectors of the economy and business entities. The originality and practical significance of the study lies in determining the modern aspects of the mainstream development of enterprises in the electric power industry. Conclusions. The mainstream of development of enterprises in the electric power industry depends on market leaders, determinants and tools for the functioning of electric power enterprises. Further research consists in continuing the study of the spatial organization of electric power enterprises, developing mechanisms for adaptation to wartime conditions and post-war recovery, as well as intensifying integration with European energy markets

In this work, the network data envelopment analysis (DEA) model was used to divide the transformation of scientific and technological achievements in colleges and universities into two stages, which makes up for the lack of process measurement in a single DEA model. Also, the relationship between the transformation efficiency of scientific and technological achievements in universities and the development of a low-carbon economy was quantitatively analyzed. The research results show that: (1) the transformation efficiency of scientific and technological achievements of universities in China is increasing year by year and which is significantly higher in the eastern region than that in the central and western regions. (2) The efficiency of the transformation of scientific and technological achievements of the university promotes the reduction of carbon emission intensity and the development of a low-carbon economy, indicating that the improvement of the transformation efficiency of scientific and technological achievements of the university has a good role in promoting the ecological environment protection. However, compared with the developed countries, the quantity and quality of science and technology supply and ecological environment protection in China’s universities are still insufficient. In this regard, the development suggestions are put forward from the aspects of government policy guidance, professional talent cooperation and strengthening the docking between universities and industrial low-carbon economic development. The purpose of this paper is to promote the development of a low-carbon economy by improving the efficiency of scientific and technological achievements transformation in universities, to achieve the goal of ecological environment protection.

The rapid development of the aviation industry has brought about the deterioration of the climate, which makes airline efficiency become a hot issue of social concern. As an important nonparametric method, Data Envelopment Analysis (DEA), has been widely applied in efficiency evaluation. This paper examines 130 papers published in the period of 1993–2020 to summarize the literature involving the special application of DEA models in airline efficiency. The paper begins with an overall review of the existing literature, and then the radial DEA, nonradial DEA, network DEA, dynamic DEA, and DEA models with undesirable outputs applied in airline efficiency are introduced. The main advantages and disadvantages of the above models are summarized, and the drivers of airline efficiency are analyzed. Finally, the literature review ends up with future research directions and conclusions.

First of all, overall economic growth objectives in China are concisely and succinctly specified in this report. Secondly, this report presents a forecast of energy supply and demand for China`s economic growth for 2000--2050. In comparison with the capability of energy construction in China in the future, a gap between supply and demand is one of the important factors hindering the sustainable development of Chain`s economy. The electric power industry is one of China`s most important industries. To adopt energy efficiency through high technology and utilizing energy adequately is an important technological policy for the development of China`s electric power industry in the future. After briefly describing the achievements of China`s electric power industry, this report defines the target areas and policies for the development of hydroelectricity and nuclear electricity in the 2000s in China, presents the strategic position of China`s electric power industry as well as objectives and relevant plans of development for 2000--2050. This report finds that with the discovery of superconducting electricity, the discovery of new high-temperature superconducting (HTS) materials, and progress in materials techniques, the 21st century will be an era of superconductivity. Applications of superconductivity in the energy field, such as superconducting storage, superconducting transmission, superconducting transformers, superconducting motors, its application in Magneto-Hydro-Dynamics (MHD), as well as in nuclear fusion, has unique advantages. Its market prospects are quite promising. 12 figs.

Since the electric power industries throughout the world are undergoing enormous restructuring processes resulting in fiercer competitions than ever, it is necessary for electric power companies, especially Sichuan Electric Power Com- pany (SEPC) as an important part of South China Power Grid Company, to make suitable and feasible strategy for their development. The objective of this study is to construct an approach based on the analytic hierarchy process (AHP) and bal- anced scorecard (BSC) for evaluating SEPC performance, aiming at acting as a ref- erence to electric power industry. The BSC concept is applied to define the hierarchy with four major perspectives (i.e. financial, customer, internal business process, and learning and growth), and performance indicators are selected for each perspective. And then the AHP is used to determine the indicator weights. The results provide guidance to electric power company in the electric power industry in China regarding strategies for improving business process performance. Finally, some suggestions are given for improving the SEPC business processes.KeywordsBalanced scorecardAnalytic hierarchy processPerformance evaluationSichuan electric power companyElectric power industry