Dynamic Network Data Envelopment Analysis Research Articles

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.

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.

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.

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.

Efficiency evaluation of China’s high-tech industry with a dynamic network data envelopment analysis game cross-efficiency model

Efficiency evaluation of China’s high-tech industry with a dynamic network data envelopment analysis game cross-efficiency model

Efficiency of funding to rural revitalization and regional heterogeneity of technologies in China: Dynamic network nonconvex metafrontiers

How to assess the performance of funds to support the rural revitalization is closely concerned by both academics and industries. In this paper, taking agricultural loans and financial allocations as inputs, we open the dynamic internal structure of the funding to support the rural revitalization system (FSRRS), including the agricultural support funds system (ASFS) and the rural revitalization system (RRS). With the consideration of regional heterogeneity, we propose the dynamic network data envelopment analysis (DEA) models based on convex and nonconvex metafrontiers to measure the metatechnology-specific technical efficiency (MTE), group-specific technical efficiency (GTE) and technology gap ratio (TGR) of the overall system and subsystems. The proposed models are empirically applied to assess the efficiency of funding to support rural revitalization and regional heterogeneity of technologies for 31 provinces in China during 2017–2020. The results show that: (i) compared to the nonconvex metafrontier model, its convex counterpart underestimates the efficiency of each decision making unit (DMU), resulting in the unfairness of evaluation, in particular for the central and western regions; (ii) there is a difference in the efficiency of the overall system and the subsystems, where the RRS performance is superior to the ASFS performance, implying that the inefficiency of FSRRS is mainly attributed to the low utilization of agricultural support funds; (iii) the period efficiency of the overall system and subsystems show an increasing trend over time, and the magnitudes of increases are different across provinces (regions); (iv) the TGRs of various provinces (regions) exhibit a significant heterogeneity.

Sustainability in the evaluation of urban rail transit considering both firms and passengers perspectives: A dynamic network data envelopment analysis approach

This paper divides the operation of urban rail transit into sustainable production stage and sustainable consumption stage from the perspective of firms and passengers, and includes service input, service output, service consumption in a unified model. A dynamic network epsilon based measure model is proposed to measure the production efficiency, service effectiveness and operational effectiveness of urban rail transit respectively, which is used to evaluate the operational sustainability of urban rail transit. Taking 23 urban rail transit systems in China from 2015 to 2021 as an example, the research results show that urban rail transit production efficiency is superior to service effectiveness, but most urban rail transit operational effectiveness is not high, and a large amount of input redundancy in the current urban rail transit sustainable consumption stage comes from vehicle speed. At the same time, the perennial shortage of passengers and passenger miles is the main reason leading to the low service effectiveness. In addition, there is heterogeneity in urban rail transit service effectiveness among different city sizes, and there is a significant positive correlation between operational effectiveness and service effectiveness. Therefore, improving service effectiveness is the key to ensure sustainable urban rail transit operation.

Enhanced Dynamic Network DEA: A Novel Algorithm for Sustainable Development Efficiency Assessment in “Internet Plus Logistics” Sector

This study introduces the enhanced dynamic network DEA, an innovative algorithmic extension of the foundational data envelopment analysis (DEA), to assess the sustainable development efficiency of Jiangxi Province’s “Internet Plus Logistics” sector from 2002 to 2016. This methodology leverages a comprehensive evaluation indicator system, emphasizing waterway, highway, and railway logistics outputs. The integration of custom algorithms into the CCR and BCC models has provided a deeper insight into efficiency trends and highlighted the need for a shift to an intensive economic model. Key findings pinpoint specific inefficiencies and their causes, emphasizing the value of our method in offering precise insights. Ultimately, this research not only advances the DEA methodological landscape but also offers strategic directions for sustainable development in “Internet Plus Logistics.”

The Effect of Innovation Strategies on the Business Performance of Global Semiconductor Firms

Innovation strategies form the bedrock of sustainable business development in semiconductor firms. Using dynamic network data envelopment analysis (DN-DEA), the performance of the main global semiconductor firms during 2015 to 2019 was evaluated and the effects of intangible assets within their innovation strategies were explored. Operating efficiency (OPE) was found to be greater than R&D efficiency (RDE), and the average overall efficiency of Asian firms was found to be higher than that of American & European (AMEU) firms. A low intangible asset efficiency (ISE) indicates greater operating risks (2017 showed the highest value and 2015 the lowest). Establishing four regions, Region A showed innovation ability, but lacked business performance. Region B showed lack of both progress and operating performance. Region C showed good innovation ability and good operating performance. Region D showed innovation ability, but lack of progress. Thus, innovation achievements and intangible assets are key indicators of global semiconductor companies’ business sustainability.

Incorporating causal modeling into data envelopment analysis for performance evaluation

AbstractThe risk factors in banking have been considered an undesirable carryover variable by the literature. Methodologically, we consider the risk factor using loan loss reserves as a desirable carryover input with dynamic characteristics, which provides a new framework in the dynamic network Data Envelopment Analysis (DEA) modelling. We substantiate our formulation and results using novel techniques for causal modelling to ensure that our dynamic network model admits a causal interpretation. Finally, we empirically examine the impact of risk from various economic sectors on efficiency. Our results show that the inefficiencies were volatile in Chinese banking over the period 2013–2020, and we further find that the state-owned banks experienced the highest levels of inefficiency and volatility. The findings report that credit risk derived from the agricultural sector and the Water Conservancy, Environment and Public Facilities management sector decreases bank efficiency, while credit risk derived from the wholesale and retail sector improves bank efficiency. The results of our innovative causal modelling show that our pioneering modelling on the role of loan loss reserves is valid. In addition, from an empirical perspective, our second-stage analysis regarding the impact of risk derived from different economic sectors on bank efficiency can be applied to other banking systems worldwide because of our successful validation from causal modelling. Our attempt to incorporate causal inference into DEA can be generalized to future studies of using DEA for performance evaluation.

A dynamic multi-stage network data envelopment analysis approach for evaluating performance of wheat farms

PurposeBecause of the importance of the wheat industry in the economy, a real-featured performance measurement approach is essential for the wheat production process. The purpose of this paper is to develop a data envelopment analysis (DEA) model that is fully compatible with the wheat production process so that managers and farmers can use it to evaluate the efficiency of wheat farms for strategic decisions.Design/methodology/approachA dynamic multi-stage network DEA model is developed to evaluate the efficiency of wheat production farms in short-term (two-year) and long-term (eight-year) periods.FindingsThe results of this study show that because of the lack of long-term planning and excessive reliance on rain, most of the investigated regions have no stability in efficiency, and the efficiency of the regions changes in a zigzag manner over time. Among studied regions, only the Hashtrood region has high and stable efficiency, and other regions can follow the example of this region's cultivation method.Originality/valueTo the best of the authors’ knowledge, this study is the first one that uses the dynamic multi-stage network DEA considering every other year cultivation method and direct–indirect inputs in the agricultural section.

Comprehensive evaluation of passenger road transportation through dynamic network data envelopment analysis: A case study of state road transport undertakings in India

AbstractState road transport undertakings (STUs) in India are public utility services that link diverse terrains and remote and hilly areas throughout the country and play a vital role in enhancing public mobility. These organizations are motivated to work through a sense of social responsibility. For example, they operate in low‐revenue‐generating regions to serve the public. Therefore, they require regular performance monitoring and constant efforts toward course corrections. Existing literature on the performance evaluation of STUs ignores the internal structures of the passenger transportation process and treats the process as a “black‐box.” Consequently, it fails to identify the precise cause of inefficiencies, making course corrections in a multistage transportation process difficult. To close this research gap and comprehensively evaluate the performance of STUs, considering their internal structure and based on long‐term optimization, this study employs a slacks‐based dynamic network data envelopment analysis (DNDEA) approach to deconstruct India's publicly owned passenger road transportation process into operations and revenue divisions, subjected to a multiperiod performance evaluation from 2014–2015 to 2017–2018. Moreover, we utilize panel data regression to explore other influential factors not included in the DNDEA, explaining the efficiency variation across STUs. This study is the first to explore the internal structure of STUs in India and perform a comprehensive evaluation of STUs, considering their internal divisions and multiple‐period long‐term optimization. The DNDEA results highlight evidence of capital misallocation in India's public road transport sector. While operational inefficiency can be attributed to improper utilization of resources, price regulation is the major source of inefficiency in the revenue division. Fixed effects panel data regression revealed that STUs with higher bus utilization and passenger lead are more efficient. The contribution of this study lies in its innovative approach of using DNDEA to analyze India's passenger road transportation sector and its inner constructs, providing insights into the efficiency scores of STUs and their dynamic changes in one model. Managers and policymakers can use the findings of this study to revise and frame policies targeted at improving STU efficiency.

Performance evaluation of compulsory education system in Taiwan: A modified dynamic network data envelopment analysis approach

The purpose of this study is to examine changes in the efficiency of Taiwan's compulsory education system between 2011 and 2020, identify the priority school sub-system for improving the system, and determine the input/output inefficiencies responsible for the sub-system inefficiencies. To achieve these objectives, a modified dynamic network data envelopment analysis model is used to assess the efficiency of the compulsory education systems and their internal primary and middle school sub-systems regulated by local governments. The findings indicate that both primary and middle school efficiency are crucial for evaluating the compulsory education system efficiency, and teacher and staff excesses in most local government's compulsory education systems are the primary sources of inefficiency. Therefore, the prompt adjustment of teacher and staff allocation based on student numbers is the primary approach to enhancing system efficiency.

Energy security performance evaluation revisited: From the perspective of the energy supply chain

The previous research on energy security performance (ESP) has often treated the energy security system as a “black box,” meaning that it has not explored the internal composition structure of the system or the linking relationships of the energy supply chain. This study proposes a comprehensive evaluation framework and a comparative study of ESP evaluation in 32 OECD countries over 20 years, dividing the energy system into four processes. A dynamic network Data Envelopment Analysis (DNDEA) model is used to analyze the energy system's overall performance and each process's performance, considering their internal structure and dynamic characteristics. The ESP results show that half of the 32 OECD countries had perfect efficiency scores, while the other half had scores ranging from 0.0222 to 0.74. The study also found more progress in the second half of the 20-year period. In terms of the four individual processes, the total primary energy supply (TPES) and total final energy consumption (TFEC) processes had consistently high scores, while the secondary energy resources (SER) process had room for improvement. Based on a cross-check of the various ESP results over the past 20 years, as well as the ESP in the most recent decade, seven countries (Austria, Canada, Finland, South Korea, Luxembourg, Norway, and Switzerland) were identified as benchmarks for their strong performance, and the study examined the indicators underlying their success. The study also identifies areas for improvement in underperforming countries and determines future directions for improvement.

Assessing the dynamic efficiency and technology gap of airports under different ownerships: A union dynamic NDEA approach

Airport performance assessment is important to a variety of stakeholders. It is particularly relevant to measure airport operational efficiency and the ways in which it can be improved through measurement can be undertaken by examining the relationship between airport ownership and operational efficiency. In the present study, a new model called the union dynamic network data envelopment analysis model has been propounded and has been employed to analyse the dynamic efficiency and changes of technology gaps of 50 European airports with different ownerships in the period 2011–2017 within the meta-frontier framework. The results demonstrate that over the years, even though the dynamic meta efficiency of private majority airports has been the best in both production and sales stages of operation, public corporation airports have been technology leaders amongst other groups of airports. The findings give direction as to what aspects the airport managers and practitioners need to focus on so as to undertake airport performance improvement.

A dynamic network data envelopment analysis cross-efficiency evaluation on the benefits of bus transit services in 33 Chinese cities

ABSTRACT Our objective in this paper is to evaluate the benefits of bus transit. To obtain the more accurate and highly discrimination results, this study establishes an evaluation indicator system from a stakeholder perspective and proposes a novel combined method consisting of dynamic network data envelopment analysis, cross-efficiency evaluation, and Shannon entropy aggregation method. An empirical study of bus transit systems in 33 key Chinese cities from 2016 to 2019 is provided. The results show that the benefit of bus transit in most key cities was ineffective. In contrast to production efficiency, focusing on improving service effectiveness is more conducive to improving the benefits of bus transit. Small cities have higher benefits than large cities. Meanwhile, the benefits of bus transit vary geographically. This evaluation outcome provides a more appropriate basis for decision-making related to the benefits of public transit services, as well as for operational and management studies.

The impact of regulation on the Brazilian water and sewerage companies’ efficiency

Access to sanitation services in Brazil is still deficient, despite the abundant financial resources allocated to it in the last two decades and the objective of the regulatory framework of 2007 of providing universal access and efficient sanitation systems. This article analyzes the impact of the regulatory environment on the water and sewerage companies' levels of efficiency. First, these efficiencies were computed within a dynamic network data envelopment analysis for a sample of 156 Brazilian water and sewerage companies, from 2006 to 2015, considering investments in water, investments in sewage, and operations divisions separately. In the second stage, this research related water and sewerage companies' efficiencies to innovative measures of the regulatory environment by using a panel data model, with data from 2006 to 2015. The efficiency analysis revealed low levels of overall and divisional efficiencies, highlighting the importance of evaluating efficiency over time, and of considering the providers’ internal structure, to identify inefficiencies that may compromise the achievement of regulatory objectives. The regression results indicate that the impact on the overall and divisional efficiencies depends on the choice of regulatory incentives, the intensity of the application of those incentives, and even the number of regulatory authorities.

Performance evaluation for health‐care sectors using a dynamic network data envelopment analysis approach

AbstractThis study examines performance of provincial health‐care system in China, using a dynamic network data envelopment analysis (DEA) approach. We focus on efficiency improvements both within provincial health‐care system and within two separate internal sub‐divisions. The administration division engages in financial management while the medical care division provides medical care services. Then there are two main results. First, the average overall efficiency score of provincial health‐care system is 0.9316 from 2010 to 2017. Second, the productivity progress in administration division is lower than that in medical care division, and the technical advances contribute most of the productivity progress. The research gap and the innovation of this paper lie in three aspects: First, this paper opens the black box of health production function and use the network DEA to analyze Chinese provincial health‐care system and its inner two constructs. Second, this paper discusses the efficiency scores as well as dynamic changes in one model. Finally, this paper tries to reveal the regional heterogeneity of static efficiency as well as the dynamic efficiency changes.

Efficiency evaluation for urban industrial metabolism through the methodologies of emergy analysis and dynamic network stochastic block model

Frequent economic activities in cities have exacerbated irreversible environmental degradation. It is urgent to balance the relationship between economic growth, resource investment and environmental protection. With the concept of urban metabolism, this study attempts to clarify the internal structure of urban system metabolism and the metabolic relationship between specific economic sectors. And then, it determines the metabolic level of current urban industrial development by means of metabolic efficiency evaluation, which can help more accurately reveal the sustainability of urban metabolic activities. Based on them, this study proposes a metabolic efficiency evaluation model combined with emergy analysis and slack-based measure dynamic network Data Envelopment Analysis (DEA). Through the multi-period and multi-stage network DEA model, the internal structure of urban industrial metabolism is opened. And considerring industrial waste as an undesirable carryover will be regarded as additional inputs in future period to reflect the impact on industrial metabolic efficiency. Using the proposed model, the industrial metabolic efficiency of 18 first-tier cities in China from 2016 to 2020 was analyzed. It is found that all cities are inefficient, which indicates that all evaluated cities need to make appropriate adjustments to improve their weak stages. In response to the specific problems of inefficiency in each city, an improvement framework is proposed to help each city better realize the sustainable development of the urban economy.