Dynamic Data Envelopment Analysis Research Articles

Renewable Energy Generation Efficiency of Asian Economies: An Application of Dynamic Data Envelopment Analysis

Renewable Energy Generation Efficiency of Asian Economies: An Application of Dynamic Data Envelopment Analysis

Interval efficiency estimation using relational dynamic DEA approach: Case of Indian banks

Interval efficiency estimation using relational dynamic DEA approach: Case of Indian banks

Improving energy-related efficiency towards SDG7 in China: What role does energy poverty play?

The improvement of energy-related efficiency has promoted energy-sustainable development in China; however, it may be inhibited by energy poverty. This paper constructs an index system to measure China's energy poverty. Subsequently, we evaluate energy-related efficiency towards SDG7 comprised of energy production efficiency and energy sustainable utilization efficiency using a dynamic two-stage data envelopment analysis model. Furthermore, we adopt fixed effect models to quantify the impact of energy poverty on improving energy-related efficiency and the underlying mechanism. The findings indicate that: (1) China's energy poverty situation gradually improves from 2011 to 2020. The energy-related system's performance is medium due to the poor performance in its energy production stage in 30 provinces during 2011-2020. Energy-related efficiency is greater in areas with a higher response to SDG7. (2) The impact of energy poverty on improving energy-related efficiency is significantly negative. Addressing energy poverty significantly improves energy-related efficiency in regions characterized by a high energy poverty index and low energy-related efficiency. However, it bears no impact in regions with a low energy poverty index and high energy-related efficiency. (3) The moderating effect of technological innovation effectively improves energy-related efficiency, whereas the marketization level has an inverse effect. Consequently, this paper suggests several policy implications.

Resilience-sustainability assessment of electricity supply chain under uncertainty: a new fuzzy dynamic network DEA based on rang adjusted measure

Resilience-sustainability assessment of electricity supply chain under uncertainty: a new fuzzy dynamic network DEA based on rang adjusted measure

An Efficiency Evaluation and Driving Effect Analysis of the Green Transformation of the Thermal Power Industrial Chain: Evidence Based on Impacts and Challenges in China

The high carbon emissions and pollution of China’s thermal power industry chain have exacerbated environmental and climate degradation. Therefore, accelerating the green transformation process is of great significance in promoting the sustainable development of enterprises. This study selected 30 listed thermal power enterprises in China as research objects, analyzed their data from 2018 to 2022, set targeted input–output indicators for different stages, and used a two-stage dynamic data envelopment analysis (DEA) model to evaluate and measure the efficiency of the green transformation of Chinese thermal power enterprises. In addition, this study also uses the logarithmic mean Divisia index (LMDI) method to analyze the driving effects of green transformation. The results indicate that in terms of overall efficiency, there is a significant difference in the overall performance of these 30 thermal power enterprises, with a large difference in average efficiency values. Efficiency values are related to enterprise size. In terms of stage efficiency, the average efficiency value of thermal power enterprises in the profit stage was significantly higher than that in the transformation stage, and the profitability of Chinese thermal power enterprises was better. In terms of sub-indicator efficiency, the efficiency of each indicator shows a “U”-shaped trend, and there is a certain correlation between the operating costs and revenue of thermal power enterprises, the market value of green transformation, and related indicators. In addition, the most important factor affecting the efficiency of green transformation is the sewage cost they face, whereas their operational capabilities have the least impact on their green transformation. In this regard, thermal power enterprises should increase their investment in the research and development of key technologies for thermal power transformation and continuously optimize their energy structure. The government will increase financial support for thermal power green transformation enterprises and correspondingly increase emission costs.

Evaluating Bank Efficiency with Risk Management by Optimal Common Resource and Three-Parallel Two-Stage Dynamic DEA Model

Evaluating Bank Efficiency with Risk Management by Optimal Common Resource and Three-Parallel Two-Stage Dynamic DEA Model

Efficiency evaluation of intellectual capital for value creation: a case study of the semiconductor industry in Taiwan

PurposeThis study constructs an efficiency evaluation framework for assessing the human, structural and relational capital in the semiconductor industry of Taiwan. Furthermore, we analyze whether there are significant differences in efficiency across different levels concerning the industry supply chain (upstream, midstream and downstream), employee service tenure, capital scale and company establishment years.Design/methodology/approachThis study focuses on Taiwanese semiconductor companies, utilizing data sourced from the Taiwan Economic Journal (TEJ) Database for the period spanning 2017 to 2021, encompassing a total of five years. Due to the nondisclosure of intangible asset values by all companies, an effort was made to ensure a comparable baseline by excluding companies with incomplete or missing data. Finally, empirical analysis was conducted on a sample of 64 companies using the dynamic network data envelopment analysis method.Findings(1) Overall efficiency demonstrates structural capital as the most prominent, followed by relational capital, while human capital shows relatively poorer efficiency. (2) To enhance the efficiency of intellectual capital, priority should be given to improving the efficiency of outputs related to intellectual property rights such as patents. (3) The midstream segment exhibits the best efficiency in both structural and relational capital. (4) Companies with longer employee service tenures exhibit superior efficiency in human capital in the long run. (5) Companies with extended establishment years and larger capital scales demonstrate superior efficiency in both human and structural capital.Originality/valueReflecting on past literature, scholars have primarily focused on the relationship between intellectual capital and firm efficiency, often emphasizing the overall efficiency of intellectual capital. However, within organizations, human capital, structural capital, and relational capital are interrelated. This study, for the first time, assesses the efficiency of these three components within an organization. The research addresses the challenges in analyzing the efficiency of intellectual capital and introduces a highly contemporary approach – dynamic network data envelopment analysis (DNDEA). Using the semiconductor industry in Taiwan as a case study, this paper conducts empirical analysis in a captivating and worthy industry. Therefore, the ideas presented in this paper are original.

Efficiency analysis of China's urban water supply utilities using a dynamic multiactivity network DEA model

Urban water scarcity and severe consumption challenges are crucial for improving performance in the urban water supply industry. Urban Water Supply Utilities (UWSUs) perform the primary task of providing tap water to city residents, and regulators use benchmarks to monitor UWSU operations. To assess the efficiency of UWSUs in detail, this study introduces a dynamic two-stage network data envelopment analysis (DEA) model with shared inputs and shared carryover. This model decomposes UWSU operations into water production (WP) and water distribution (WD) subprocesses. By combining dynamic features with network DEA, the study extends the static network DEA to a more general case for evaluating UWSU efficiency. The study sample includes 246 UWSUs from 24 provinces in China over the period 2016–2018. The analysis covers overall efficiency, period efficiency, subprocess efficiency, and regional disparities among the sampled water utilities. The findings indicate that the average efficiency of the UWSUs was 0.643 during 2016–2018, with slightly lower efficiency in the WP subprocess. UWSUs in the eastern provinces outperformed those in the central and western provinces, which require significant improvements. To enhance the performance of China's water supply sector, accelerated market competition and infrastructure improvements are necessary.

Evaluation of Chinese commercial bank efficiency and influencing factors: a three-stage dynamic data envelopment analysis approach

Evaluation of Chinese commercial bank efficiency and influencing factors: a three-stage dynamic data envelopment analysis approach

Developing an efficiency evaluation model for the circular economy in Europe

ABSTRACT The aim of this work is to develop a model for evaluating the efficiency of the Circular Economy (CE) in Europe. In this context, we have developed a dynamic efficiency model of the CE, the Dynamic Network Data Envelopment Analysis (DNDEA) model (Tone and Tsutsui 2014), with the purpose of it being utilized to determine the degree of progress of the policies on the CE, the degree of compliance with those policies, as well as to determine the factors that are associated with a greater or lesser efficiency. The results obtained indicate that the factors which have most affected the dynamic inefficiency have been: the Imports from the EU countries, the Exports to the non-EU countries, and the Gross Value Added. The patents that are related to Waste Management, Recycling, and Persons Employed in the CE sector have been the factors that have added the greatest efficiency. The contribution of this work lies in the development of a new model for the measurement of the dynamic efficiency of the CE at the macroeconomic level in Europe, while considering the relationships between the results and the resources that are allocated to the CE, and establishing a period of implementation and execution.

Understanding the role of energy sector in the outbreak of epidemic in China: An analysis based on SEIDR epidemic model, dynamic input-output model and resource allocation DEA model

The global epidemic has triggered severe health crises and economic downturns, while energy sector plays an important role in the complicated sector interdependence. In such context, to gain a deeper understanding of the energy sector's role during epidemic outbreaks, this study develops a new methodological framework. The framework first combines SEIDR epidemic model with dynamic input-output model and resource allocation DEA model, linking epidemiological and socioeconomic aspects. Empirically, this study focuses on China's economy by constructing an energy-manufacturing-service system. Our main conclusions are summarized as follows. First, the epidemic generates substantial effects on energy sector, while the size of effects is sensitive to the settings of some key parameters. Second, the energy sector suffers the most significant decline in total output and capital due to the epidemic, particularly in Shandong and Gansu. Conversely, Beijing and Chongqing have shown the least changes, indicating a more resilient performance in comparison to other provinces or province-equivalents. Finally, a well-designed resource allocation strategy can reduce inefficiency, and then reduce the economic losses possibly caused by the epidemic. The output of energy sector has reduced by 29.5%, indicating a need for targeted interventions and strategies to boost its performance.

Performance evaluation of the global airline industry under the impact of the COVID-19 pandemic: A dynamic network data envelopment analysis approach

The COVID-19 pandemic posed unprecedented challenges to the airline industry, necessitating a focus on maintaining high efficiency for profitability. This study assesses the efficiency of 26 international airlines from 2019 to 2022 using a dynamic network data envelopment analysis (DNDEA) methodology. The model accounts for the dynamic effect between two consecutive periods and incorporates an internal structure to evaluate airline performance across multiple dimensions. It enables the assessment of overall, period-specific, and stage-specific efficiencies. The findings reveal that while overall efficiency is moderately high on average, no airline achieved full efficiency during the pandemic. Efficiency decreased notably from 2019 to 2020, with a partial recovery but not a return to pre-pandemic levels by 2022. Operational performance remains satisfactory and stable, while service and financial performance exhibit lower efficiency, especially among low-cost airlines compared to full-service counterparts. Additionally, the study explores airlines' environmental impact by considering greenhouse gas emissions. Comparative analysis with a dynamic DEA model without internal structure highlights theoretical contributions, and the study offers managerial insights for airline leaders and policymakers.

Relationship between recycling, circular economy and eco‐innovation in Europe. Application of a dynamic network data envelopment analysis model

AbstractMonitoring of European‐level circular economy (CE) efficiency requires more research than does currently exists in the body of literature on CE. In this regard, this research aims to answer two research questions. Firstly, to be efficient in the implementation of CE at a macroeconomic level, should there be a relationship between the efficiency of the three phases of CE (efficiency in recycling, efficiency in the implementation of CE and efficiency of eco‐innovation)? To answer this question, we use decoupling theory. Secondly, are the three phases of CE related from the point of view of dynamic efficiency? To answer this question, we use dynamic efficiency theory.In accordance with both of these theories, we establish a circular relationship between recycling, CE and eco‐innovation. We test this circular relationship through the application of the dynamic network data envelopment analysis (DNDEA) model of Tone and Tsutsui. The analysis is based on Eurostat data for the period of 2016 to 2022 for 27 European countries.This work contributes to the advancement of the research via (1) the development of a model for measuring the transversal and longitudinal efficiency of the CE and (2) the findings of positive and significant relationships between the efficiency ratios of the three fundamental phases (recycling, CE and eco‐innovation). This leads us to affirm that the countries studied that have managed to be efficient in recycling have also been in the implementation phase of CE and eco‐innovation.

Dynamics, regional heterogeneity and robustness of fiscal poverty alleviation efficiency in China: dynamic network DEA and Bootstrap resampling methods

This paper aims to tackle the issues of evaluating the dynamic performance of fiscal poverty alleviation in 22 Chinese provinces (regions) over 2016–2019. First, we open up the internal structure of the fiscal poverty alleviation system (FPAS) and clarify its input-output process as a two-stage series system consisting of the public investment process and poverty reduction process. On this basis, we construct dynamic network DEA models with and without carryover activities for measuring the period efficiency and overall efficiency of FPASs (i.e., FPAS efficiency) and the period efficiency and overall efficiency of evaluation indicators (i.e., indicator efficiency), and also prove the relationship between the two proposed models. Second, we combine the proposed dynamic network DEA models and Bootstrap resampling method to assess the robustness of FPAS efficiency for exploring the risk of returning to poverty for each FPAS. The results show that: (i) the carryover activities have some impact on the FPAS efficiency and indicator efficiency; (ii) the period efficiency shows an upward trend, and most of FPASs or evaluation indicators have been at high efficiency in the sample period, but there is still regional heterogeneity; (iii) there are some differences between the indicator efficiency and there are some inconsistencies between them and the FPAS efficiency; (iv) bootstrap resampling results indicate that several FPASs have a great risk of returning to poverty.

Discretionary investment managers evaluation in pension fund: Shared input dynamic network DEA approach

Investment trust corporations (ITCs) constitute one of the financial industry's subsectors, and their evaluations of fund management performance play a crucial role. With the recent increase in the number of ITCs and their assets, how the Public Service Pension Fund management board (PSPFMB) of Taiwan makes investment decisions regarding multiple companies has become a critical issue. Using the shared input dynamic network data envelopment analysis approach (SDNDEA), we empirically estimate the performance efficiency scores of the funds of 34 ITCs and analyze the performance of the manufacturing structures of their internal networks. Our results indicate that the PSPFMB should consider the effects of being entrusted with decisions on efficiency. Employing K-means clustering techniques, we investigate the operational characteristics of each group and identify the differences among them. Moreover, this research identifies significant externalities related to ownership structures, indicating that the PSPFMB should consider the effects of such structures on efficiency in the context of entrusting decisions. Thus, the PSPFMB can make optimal investment decisions based on our ITC evaluation and selection model and help pension funds achieve stable long-term investment benefits.

Spatiotemporal effect and influencing factors of the total factor energy efficiency: Evidence from the urban agglomerations in China

Amidst the ongoing global energy quandary, the imperative to augment energy efficiency emerges as a strategic response to counteract energy profligacy and propel sustainable development initiatives. This study aims to assist policymakers in gaining a more accurate understanding of the temporal and spatial complexity and dominant variables of total factor energy efficiency at the urban agglomeration level, thereby providing empirical insights for promoting a comprehensive improvement of the existing energy development framework. Based on the dynamic DEA model, this article utilizes an improved common frontier dynamic super-efficiency SBM model to conduct a quantitative analysis of total factor energy efficiency across 19 urban agglomerations in China. The influence factors of total factor energy efficiency are analyzed using spatial kernel density and geographical detectors at both temporal and factor levels. The research findings indicate that: (1) Total factor energy efficiency primarily fluctuates at a mid to low level, with a general decline to below 0.5 after 2018; (2) Significant regional heterogeneity is evident among Chinese urban agglomerations, displaying a “high in the northwest, low in the southeast” regional characteristic; (3) With time lag, the negative spatial spillover effect among regions further intensifies, becoming heterogeneous when the total factor energy efficiency of local urban agglomerations reaches 1.5 or above; (4) The singular and interactive effects of research funding become the main influencing factors of regional differentiation, and the integration of multiple factors is a key driver for enhancing total factor energy efficiency in the new era.

Are Brazilian Higher Education Institutions Efficient in Their Graduate Activities? A Two-Stage Dynamic Data-Envelopment-Analysis Cooperative Approach

Higher education evaluation presents itself as a worldwide trend. It aims to improve performance due to its importance for economic and personal growth. Graduate activities are essential for Brazilian research and innovation systems. However, previous studies have disregarded the importance of this educational level and have evaluated efficiency by jointly considering teaching and research or only undergraduate courses. Therefore, this study contributes to Brazilian reality by proving a national graduate activities efficiency evaluation that considers them as a two-stage system (formative and scientific production stages). The study provides three main methodological contributions by presenting a new centralized two-stage dynamic network data envelopment analysis (DNDEA) model with shared resources. Besides measuring efficiency, an efficiency decomposition based on a leader–follower assumption shows managers how much efficiency can alter when one of the stages needs to be prioritized. Finally, a new framework based on modified virtual inputs and outputs provides a bi-dimensional representation of the efficiency frontier. Results indicate the usefulness of the approach for ranking universities, and the need to improve scientific production, highlighting the negative impacts of COVID-19 on the formative process efficiency and showing no significant regional discrepancies regarding performance.

Panel Data Analysis of Subjective Well-Being in European Countries in the Years 2013–2022

Panel Data Analysis of Subjective Well-Being in European Countries in the Years 2013–2022

Assessing the Drivers of Sustained Agricultural Economic Development in China: Agricultural Productivity and Poverty Reduction Efficiency

Poverty eradication is a crucial element of SDG 1. Whether the financial resources invested by the Government provide a critical impetus for deeply impoverished rural areas needs to be studied by quantitative analysis. Therefore, this study presents a theoretical analytical framework for agricultural production–government poverty reduction. It divides the poverty reduction process into two stages, agricultural production and poverty reduction, from the perspective of sustainable agricultural development. The comprehensive measurement and spatio-temporal evolution analysis of China’s agricultural production and poverty reduction efficiency are conducted using a novel dynamic two-stage DEA model, which incorporates non-expected factors. The study found that (1) China’s agricultural production and poverty reduction efficiency exhibit overall poor performance, characterized by two poles of differentiation. (2) The agricultural production efficiency score is higher in the northern region than in the southern region, while the poverty reduction efficiency score is higher in the eastern region compared to the western region. (3) The coupling and coordination between China’s production efficiency and poverty reduction efficiency are inadequate.

Allocating Benefits Due to Shared Resources Using Shapley Value and Nucleolus in Dynamic Network Data Envelopment Analysis

Shared resources are common among supply chain partners and also occur in multiple linked stages of an internal network. The sharing of these resources impacts the organization’s profits. This study is focused on the potential benefits of resource sharing on a three-stage network system and on the profit improvement allocation. Previous treatments concentrate on defining optimal proportions to allocate resources and disregard the impacts of allocations to promote cooperation and are limited to static evaluations. Data Envelopment Analysis performs the decision-making units (DMUs) efficiency measurement. Methodological advances have resulted in models that analyze their internal structure and temporal impacts on efficiency. We propose an integrated cooperative game and dynamic network DEA that considers known quantities of resources used in each stage and the time effects to optimize the system’s profit. Each DMU stage is a player, and we investigate performance before and after resource sharing. Using Shapley value and Nucleolus, it is possible to allocate the benefits obtained based on the marginal contributions of each stage, providing incentives to motivate and maintain cooperation. A numerical example is used to illustrate the method. The results confirm the identification of inefficient DMUs and that sharing resources allows for profit increase for all of them.