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In December 2019, a novel coronavirus broke out in Wuhan City, Hubei Province, and, as the center of the coronavirus disease 2019 (COVID-19) epidemic, the economy and production throughout Hubei Province suffered huge temporary impacts. Based on the input–output and industrial pollution emissions data of 33 industrial industries in Hubei from 2010 to 2019, this article uses the non-parametric frontier analysis method to calculate the potential production losses and compliance costs caused by environmental regulations in Hubei's industrial sector by year and industry. Research has found that the environmental technology efficiency of the industrial sector in Hubei is showing a trend of increasing year-on-year, but the overall efficiency level is still not high, and there is great room for improvement. The calculation results with and without environmental regulatory constraints indicate that, generally, production losses and compliance costs may be encountered in the industrial sector in Hubei, and there are significant differences by industry. The potential production losses and compliance costs in pollution-intensive industries are higher than those in clean production industries. On this basis, we propose relevant policy recommendations to improve the technological efficiency of Hubei's industrial environment, in order to promote the high-quality development of Hubei's industry in the post-epidemic era.
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A body of empirical literature exists which sets out how the accommodation industry performs across a range of locations. However, research on tourism regions in terms of its accommodation industry remains underdeveloped, especially in the Covid-19 pandemic when tourism faced unprecedented adversity and need to find a way to move forward. In an attempt to address this and take the Australian accommodation industry as a case study, this paper sought to investigate the efficiency of Australian tourism regions in the accommodation industry for the period of 2014/15–2017/18. The findings clearly showed that Australian tourism regions had seen significant growth in terms of their efficiency in the accommodation industry over the surveyed period. The Australian commercial large cities, namely Sydney, Melbourne, Brisbane, and the Goal Coast, represent perhaps the best example, having obtained a higher efficiency than all other tourism regions. Exogenous factors, such as the occupancy rate, the average daily rate, the number of international visitors and the number of domestic visitors overnight were identified as influencing the technical efficiency score of tourism regions, with policy formulation and implementation identified as being key to improving the efficiency of the accommodation industry at the regional level for a post-Covid-19 period. [ FROM AUTHOR] Copyright of International Journal of Hospitality & Tourism Administration is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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PurposeThis study models the effects of the COVID-19 pandemic on the performance of the private health-care sector in the Middle East and North Africa (MENA) countries. This paper aims to address the economic, societal and sustainability of the health-care sector.Design/methodology/approachData were collected from Bloomberg and the sample consists of 534 firm-year observations from 55 firms listed over 2010–2020. The authors apply panel data and control for the country and governance effects.FindingsThe authors found heterogeneous results regarding the three sub-sectors. The pandemic has a negative effect on the accounting and market performances of the "Pharmaceutical companies” and an insignificant impact on "Healthcare Management and Facilities Services.” Moreover, the impact of COVID-19 on health-care firms' performance depends on the country's economic classification and the degree of regulatory and governance frameworks.Research limitations/implicationsFurther studies may consider a larger sample and other regions. It is recommended to address the health-care sector's challenges to invest in new technologies such as "digital twin” and predictive and personalized medicine. It is worth testing model development theory and its effects on speeding up and designing models to ensure the proper functioning and developing mathematics to determine uncertainties in patient data and model predictions.Originality/valueTo the best of the authors' knowledge, this paper is novel as it is unique in modeling the impact of COVID-19 on the health-care public companies in the MENA region. The findings pinpoint firms' and countries' heterogeneous impacts on financial and market performances.
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With the advent of healthy visions, two of the trends that have become extremely important in the supply chain in recent decades are corporate social responsibility (CSR) and sustainability, which have affected the activities of buyers and suppliers. The next trend that is emerging is the vision of creating shared value (CSV), which wants to move the supply chain toward solving social problems in a completely strategic way. This research intends to develop a step-by-step framework for evaluating and segmenting suppliers based on CSV criteria in the supply chain. In the first stage, the criteria for creating sustainable shared value (CSSV) are obtained through existing activities in the field of CSR. The obtained criteria are then divided into two categories, strategic and critical, and then the weight of each criterion is obtained using the best–worst method (BWM). In the next step, based on the Kraljic model, the suppliers are divided into four clusters using the preference ranking organization method for enrichment evaluation (PROMETHEE) technique. This framework helps the buyer to conclude and select purchasing decisions and relationships with suppliers through the lenses of CSV and sustainability.
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PurposeThe paper analyzes the relative technical efficiency of the transition economies of the Western Balkans in the period 2007-2021, in comparison with the former countries with a socialist state system, today members of the European Union (EU), based on selected macroeconomic indicators and panel data.Design/methodology/approachData envelopment analysis (DEA), i.e. its extension, DEA Window analysis, is applied. Total technical efficiency, as a prerequisite of economic efficiency, is decomposed into pure technical efficiency (PTE) and scale efficiency (SE). Bootstrapping method and Mann-Whitney U test were used to check the robustness of the obtained results, i.e. efficiency values.FindingsThe results show that in 2020, all observed countries recorded a significant drop in economic efficiency as a result of a general, disproportionate drop in the value of selected macroeconomic variables, which occurred due to the global economic crisis and the slowdown in economic activity caused by the COVID-19 pandemic. This drop in efficiency was significantly greater in the former socialist states, now members of the European Union, which showed their greater sensitivity to global crises. None of the observed economies in the observed period was relatively efficient, that is, at the level of best practice, which occurred primarily as a consequence of the inefficiency of business conditions expressed in the economies of scale.Research limitations/implicationsThe main limitation of this study stems from the very nature of the concept of DEA efficiency, which is relative in nature. Also, the results and their interpretation are also significantly influenced by the choice of model variables, as shown by Labaj et al. (2013), as well as a small number of decision-making units (DMUs). The mentioned limitations prevent unambiguous interpretation and generalization of the obtained results.Practical implicationsThe study may be of importance to economic policy makers in macroeconomic decision-making. The application of the DEA concept in measuring the technical efficiency of national economies is a useful tool in the analysis of macroeconomic performance and a benchmarking approach for positioning and achieving competitive advantage on the international market.Originality/valueSince research of this type is very limited, the results of this study make a theoretical and empirical contribution to the literature, creating a basis for future research and reexamination. The application of the DEA concept in measuring the technical efficiency of national economies is a useful tool in the analysis of macroeconomic performance and a benchmarking approach for positioning and achieving competitive advantage in the international market.
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The aim of this paper is to provide a tool for finding investments in the stocks of energy firms that achieve both good financial and reasonable environmental, social, and governance (ESG) performance. Our methodology entails two steps and is based on diversification-consistent DEA models. The first step involves constructing a financially efficient frontier of investment portfolios by applying the model originally proposed by Branda (Omega 52:65–76. 10.1016/j.ejor.2007.04.014, 2015). In the second step, a new DEA model is proposed in order to find the ESG-efficient portfolios among the ones already identified in the first step and to rank them with respect to their ESG performance. This model is parameterised by a weighting system that allows us to assign different importance to the various ESG outputs. Additionally, the proposal allows an evaluation of both ESG and financial efficiency related to the financial energy market over two periods (the pre-COVID-19 and COVID-19 periods), considering renewable energy and non-renewable energy firms both jointly and separately. The results support the better financial performance of the renewable energy stock market compared with that of the non-renewable energy market. © 2023, The Author(s).
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As human lifespan increases and the need for elderly care grows, the demand for healthcare services and its associated costs have surged, causing a decline in the operational efficiency of universal healthcare. This has created an imbalance in medical services across different regions, posing a long-standing challenge for the public. To address this issue, strategies to enhance the capacity, efficiency, and quality of healthcare services in various regions must be developed. The appropriate allocation of medical resources is a fundamental requirement for countries to establish a robust healthcare system. This empirical study utilized data envelopment analysis (DEA) to evaluate the efficiency of medical service capacity and identify potential improvement strategies for counties and cities in Taiwan during the period from 2015 to 2020. The results of this study show that (1) the annual average efficiency of medical service capacity in Taiwan is approximately 90%, indicating that there is still room for a 10% improvement; (2) among the six municipalities, only Taipei City has sufficient healthcare capacity, whereas the efficiency of the remaining municipalities needs improvement; and (3) most counties and cities demonstrated increasing returns to scale, indicating a need to scale up the capacity of medical services as appropriate. Based on the findings of this study, it is recommended that medical personnel be increased accordingly to balance the workload, a favorable working environment be provided to stabilize the medical workforce, and urban-rural medical disparities be balanced to improve service quality and reduce cross-regional health services. These recommendations are expected to provide a reference for society as a whole to promote and enhance public health policies, leading to a continual improvement of the quality of medical services.
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Traditional retailers (bricks-and-mortar) have been continuously increasing online sales. However, not all retail companies were able to respond to the increasing sales with the same efficiency level as their competitors. This paper aims to propose a dynamic model – incorporating principles of Optimal Control Theory (OCT) into a Data Envelopment Analysis (DEA) model - for measuring the performance of retailing companies' cost efficiency. It also aims to contribute through the application by investigating the impact of the pandemic on companies from the most prominent developing market in Latin America, Brazil. Twenty-one companies publicly traded in the São Paulo Stock Exchanges (B3) between the third quarter of 2018 (3Q2018) and the third quarter of 2020 (3Q2020) were investigated. Also, six measures - initial inventory cost (IIC), final inventory cost (FIC), net operating income (NOI), cost of goods sold (COGS), cost of the purchased product (CPP), and plant, property, and equipment (PPE) – were considered. In this way, the findings have implications for researchers and practitioners. Practitioners can discover which competitor(s) is (are) adopting the best practices at each operational aspect (e.g., inventory cost). Additionally, the proposed method can be replicated in other markets (developing or not) and for other categories of retailing companies (e.g., small- and middle-sized). Further research directions are presented, and their implications are discussed.
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En las últimas décadas, los inversores se han preocupado no sólo de obtener rentabilidad de sus carteras, sino también de casar ese rendimiento con valores éticos relacionados con el mantenimiento del medio ambiente, la responsabilidad social y la gobernanza. Surge así la llamada Inversión Socialmente Responsable, siendo los fondos de inversión socialmente responsables uno de sus instrumentos más importantes. En este trabajo, hemos utilizado el análisis envolvente de datos (DEA) para analizar el impacto del COVID-19 sobre la eficiencia de fondos de inversión socialmente responsables del Reino Unido. Para ello hemos dividido nuestro periodo de estudio en dos: pre-COVID y COVID. De esta forma podremos concluir si hay diferencia respecto a la eficiencia en los fondos según su nivel de sostenibilidad y el periodo analizado. Los resultados obtenidos nos permiten concluir que en el periodo pre-COVID los fondos más eficientes pertenecen al grupo de los de mejor calificación ESG. Si bien este grupo también es el que más se ha visto afectado por la pandemia. Lo contrario se concluye para el grupo de los de menor calificación ESG.Alternate :In recent decades, investors have been concerned not only with obtaining returns on their portfolios, but also with matching these returns with ethical values related to environmental protection, social responsibility and governance. Thus arises the so-called Socially Responsible Investment, being socially responsible mutual funds one of its most important instruments. In this paper, the data envelopment analysis (DEA) has been considered to analyze the impact of COVID-19 on the efficiency of UK socially responsible mutual funds. For this, we have divided our study period into two: pre-COVID and COVID. In this way we will be able to conclude whether there is a difference in the efficiency of the funds according to their level of social responsibility and the analyzed period. The results obtained allow us to conclude that in the pre-COVID period the most efficient funds belong to the group of those with the best ESG rating. Although this group is also the one that has been most affected by the pandemic. The opposite is concluded for the group of those with the lowest ESG rating.
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The transportation industry is characterized as a capital-intensive industry that plays a crucial role in economic and social development, and the rapid expansion of this industry has led to serious environmental problems, which makes the eco-efficiency analysis of the transportation industry an important issue. Previous research paid little attention to the regulatory scenarios and suffered from the incomparability problem, hence this paper aims to reasonably estimate the eco-efficiency and identify its evolutionary characteristics. We measure the eco-efficiency and the corresponding global Malmquist–Luenberger productivity index using a modified model of the data envelopment analysis framework, in which different regulatory constraints are incorporated. Based on the empirical study on the transportation industry of thirty provinces in China, we find that the eco-efficiency of Chinese transportation industry experienced a slight increase during 2015–2016, a sharp decline during 2016–2017, and a continuous rise since year 2017. The Middle Yangtze River area was the best performer among the eight regions in terms of eco-efficiency, while the Southwest area was placed last. The global Malmquist–Luenberger productivity index showed an earlier increase and later decrease trend, which was quite consistent with the reality of the variation of inputs and outputs and the emergence of COVID-19. Moreover, the best practice gap change was found to be the main driven force of productivity. The empirical results verify the practicability of our measurement models and the conclusions can be adopted in guiding the formulation of corresponding policies and regulations.
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PurposeThis paper aims to present a hybrid approach to measure the efficiency of virtual contact centers (VCCs) started during the pandemic and benchmark them for service performance. The results are used to plot the VCC's efficiency score (performance) and customer perception (Importance) to propose appropriate strategies.Design/methodology/approachUsing the survey method, 854 responses were collected from customers who used VCC services during the pandemic. This data was then employed to assess the performance of VCCs using SERVPERF and DEA methods, followed by the development of the model for performance analysis.FindingsResults reveal the ranking of different VCCs started during the pandemic for the telecom company using SERVPERF and DEA methods. Further, the performance analysis model highlighted the strategies appropriate for each VCCs.Practical implicationsThe findings add to the body of knowledge on how multiple service units of a large organization can assess service efficiency utilizing a combination of SERVPERF-DEA. The present work also contributes to the performance analysis field by proposing a model to assess the service centers and provide improvement guidelines.Originality/valueThe work is one of the first to assess the service efficiency of the VCCs started during the pandemic by using a unique hybrid approach of SERVPERF and DEA. This approach provides a direction to whom to benchmark and to what degree service quality should be improved. Further, the study proposes a unique performance analysis model based on performance scores and customer perception.
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This study evaluates the working capital management (WCM) super-efficiency in UAE firms and determines how the COVID-19 crisis may affect WCM super-efficiency from a statistical perspective. Data envelopment analysis (DEA), difference tests, and Tobit regression techniques are used. Integration of DEA with Tobit regression is required to recognize the potential statistical consequence of COVID-19 on the super-efficiency of WCM. The results show that WCM super-efficiency is moderate and requires decision-makers' corrective measures to attain best practices. The study results show no significant difference in WCM super-efficiency, and COVID-19 does not significantly influence WCM super-efficiency. The results would rouse decision-makers' interests, who would look into the firm's efficiency and weak spots. They would then take major steps to improve efficiency and achieve the best practices. Stakeholders such as managers, financiers, and investors may need these results to monitor how firms manage their assets and liabilities. We contribute to the literature by investigating and evaluating firms' WCM super-efficiency pre and post the COVID-19 pandemic employing a unique technique based on DEA super-efficiency and examining whether COVID-19 has affected WCM super-efficiency to extend the scope of knowledge and stressing the importance of sound WCM, especially in periods of economic distress. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.
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Financial distress is a research topic in finance that has attracted attention from academia following past financial crises. Although previous studies associate financial distress with several elements, the relationship between distress and ESG has not been broadly explored. This paper investigates these issues by elaborating a Dynamic Network DEA model to address the underlying connections between accounting and financial indicators. Thus, a model that includes profit and loss, balance sheet, and capital and operating expenditures indicators is demonstrated under the dynamic network structure to compute financial-distress efficiency scores. Then, the impact of carryovers is considered for the accurate calculation of efficiency scores for the three substructures. The influence of contextual variables, such as socioeconomic and macroeconomic variables, and whether the firm owns an ESG Risk Score or not, is assessed through a stochastic non-linear model that combines three distinct regression types: Simplex, Tobit, and Beta. The results indicate that firms that hold an ESG Risk Score are less prone to be in financial distress, and Governance Score is negatively associated with financial distress efficiency.
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Purpose: The aim of this study is to analyze Turkey's blood collection efficiency at the regional level between 2018 and 2021 and discuss managerial implications. Design/methodology/approach: The authors utilize data envelopment analysis (DEA) to evaluate the efficiency scores of the 18 regions for which the Turkish Red Crescent is responsible. The data set is obtained from the General Directorate of Blood Services in the Turkish Red Crescent. Finding(s): The results reveal that the efficient regions over the years did not substantially change, and regions that were consistently efficient for a four-year period are identified. Another finding is that COVID-19 did not affect the blood collection efficiency of the regions. Moreover, the findings illustrate that concentrating on the operations would contribute more to the blood collection efficiency than changing the scale size. Furthermore, the authors observe that the service population is by far the most important variable in determining the efficiency of the regions. Originality/value: In this study, the authors present a multi-dimensional perspective on the performance evaluation of blood collection operations. In addition, the authors present blood bank managers' feedback on the performance evaluation model, outlining managerial implications. Furthermore, the authors explore the effects of the pandemic on blood collection in Turkey and illustrate the changes in efficiency throughout a distinct period that incorporates the pandemic. The study would provide a guide for blood bank managers to improve the performance of their organizations.Copyright © 2023, Emerald Publishing Limited.
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The emergency department (ED) is one of the most critical and high-risk sections of the health system. Providing quality services at a fast pace is vital in this ward since it directly affects people's lives. The COVID-19 pandemic has turned into a serious challenge for physicians and emergency departments (EDs). The growing number of patients who refer to EDs creates congestion, which will reduce the quality of services. Consequently, managing and operating EDs will be more urgent during this pandemic. Considering this problem, we first used data envelopment analysis (DEA) to evaluate the performance of EDs in the central provinces of Iran. Then, sensitivity analysis was used to determine the main factors affecting the efficiency of this ward. Accordingly, the high number of admitted patients, the congestion of the ward, and the long time required to report the COVID-19 test results were found to be the most influential factors. Finally, drawing on the results of sensitivity analysis, we advance a number of measures to improve these three and other related indicators. Furthermore, appropriate strategies were presented for improving health, COVID-19 management, key performance indicators, and safety indicators in accordance with the results of strengths-weaknesses-opportunity-threat (SWOT) analysis.
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COVID-19 , Humans , Pandemics , Emergency Service, Hospital , Hospitals , IranABSTRACT
This study uses three data envelopment analysis models to determine the production efficiency of biohydrogen which is produced from macroalgae and other sources by dark fermentation. The efficiency of macroalgae is greatest in batch mode for S. Japonica using a sDFMEC process at pH 5.3, 35 degrees C, 1 g COD/L and a hydrogen production rate (HPR) of 0.34 L/L/h. The highest efficiency is using an internal circulation batch reactor in continuous mode for beverage waste water. The HPR and substrate concentration are the most important factor of biohydrogen efficiency, and efficiency and temperature are the most important factors of HPR. Malaysia and India are the two economies that most benefit from increased production efficiency due to the use of macroalgae. Increasing biohydrogen yield efficiency will improve macroeconomic growth and establish a renewable hydrogen and biohydrogen industry, which is especially efficient related to the economic recovery during the COVID-19 pandemic. (c) 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
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The aim of the paper is to propose a method for evaluating the performance of football clubs based on the method of Data Envelopment Analysis. The article also deals with the impact of the reprisals caused by the Covid-19 pandemic, which limited fans' access to the stadiums as well as the football competitions themselves. Professional English football clubs playing in the English Premier League were selected for empirical analysis. The performance evaluation of English football clubs is an important reference for team managers, the management of individual clubs and the selected competition as a whole. One of the two most frequently used DEA models, the CCR model, was used to analyze the relative efficiency of football clubs. The study focuses on clubs operating in the highest English football competition during the seasons 2017/18 to 2020/21.
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PurposeThe purpose of this paper is to explore the relationship between Dow Jones Islamic Market World Index, Islamic gold-backed cryptocurrencies and halal chain in the presence of state (regime) dynamics.Design/methodology/approachThe authors have used the Markov-switching model to identify bull and bear market regimes. Moreover, the dynamic conditional correlation, the Baba, Engle, Kraft and Kroner- generalized autoregressive conditional heteroskedasticity and the wavelet coherence models are applied to detect the presence of spillover and contagion effects.FindingsThe findings indicate various patterns of spillover between halal chain, Dow Jones Islamic Market World Index and Islamic gold-backed cryptocurrencies in high and low volatility regimes, especially during the COVID-19 pandemic. Indeed, the contagion dynamics depend on the bull or bear periods of markets.Practical implicationsThese present empirical findings are important for current and potential traders in gold-backed cryptocurrencies in that they facilitate a better understanding of this new type of assets. Indeed, halal chain is a safe haven asset that should be combined with Islamic gold-backed cryptocurrencies for better performance in portfolio optimization and hedging, mainly during the COVID-19 period.Originality/valueTo the best of the authors' knowledge, this paper is the first research on the impact of the halal chain on the Dow Jones Islamic Market World Index return, Islamic gold-backed cryptocurrencies returns in the bear and bull markets around the global crisis caused by the COVID-19 pandemic.
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Purpose: The purpose of this study is to evaluate the performance of mutual funds during the COVID-19 pandemic with environmental, social and governance (ESG) criteria. The main research question is whether mutual fund performance differs with respect to the level of the mutual fund's ESG score. Design/methodology/approach: The data set contains global fund data, and mutual fund performance is analyzed using two types of data envelopment analysis (DEA) models: the DEA portfolio index (DPEI) and the range direction measure (RDM) DEA. Propensity score matching and logistic regression are also applied. Findings: The results reveal that: nonequity mutual funds present significantly higher performance compared to the performance of equity mutual funds;mutual funds with high ESG scores are associated with significantly higher performance compared to those with low to medium ESG scores;funds with high ESG scores experience higher performance irrespective of their type;and efficiency scores derived from the RDM DEA are significantly higher than those derived from the DPEI model. Research limitations/implications: Investors, fund managers and market participants can benefit from the findings of this study and improve their investment decision-making process, including more sustainable funds in their portfolios. Regulators and policymakers should further promote or even require the inclusion of more sustainable investments in the financial products offered by institutional investors. The main limitation of the study is related to data availability regarding the ESG score of mutual funds. Originality/value: To the best of the authors' knowledge, this is the first study that provides robust evidence in support of a positive association between ESG scores and mutual fund performance during the pandemic-induced crisis applying a DEA methodology. © 2023, Emerald Publishing Limited.