Modified Data Envelopment Analysis Research Articles

Spatial differentiation and influencing factors of red tourism resources transformation efficiency in China based on RMP-IO analysis

This study employs modified data envelopment analysis (DEA) models and spatial autocorrelation methods to analyze the characteristics of red tourism transformation efficiency and categorize them into efficiency zones. By utilizing geographic detector models, the interactive driving mechanisms behind spatial differentiation are revealed, providing valuable insights for the high-quality transformation and development of China's red tourism economy. The application of modified DEA models facilitates the evaluation of red tourism resource transformation efficiency by decomposing comprehensive efficiency into single-factor efficiency for individual input and output variables. The results indicate that: (1) Expansion of tourism factors is crucial for achieving red tourism resource transformation in China, with low efficiency in resource endowment investment acting as the primary constraint. (2) Local spatial correlation between production efficiency and resource transformation efficiency demonstrates a decreasing trend from east to west, leading to the classification of China’s red tourism resources into five types of efficiency zones. (3) Endogenous ability factors predominantly affect red tourism resource transformation efficiency, with interaction between internal and external factors driving spatial differentiation.

Transitions towards green productivity in Africa: Do sovereign debt vulnerability, eco‐entrepreneurship, and institutional quality matter?

AbstractImproving green productivity (GP) is critical for achieving global sustainable green development. Yet, past efficiency studies on the African continent have ignored Africa's GP, estimation, and driving factors. Specifically, the role of sovereign debt vulnerability, environmental entrepreneurship, and institutional quality in ensuring Africa's green productivity development is lacking. Therefore, this study built a meta‐frontier biennial weighted modified data envelopment analysis (DEA) model to evaluate green productivity across resource‐intensive and non‐resource‐intensive African countries from 2010 to 2019. Further, the study adopted the global Malmquist‐Luenberger productivity index (GML) to investigate the dynamic changes in African green productivity growth. The results suggest that only a few African countries are efficient, implying more room for improvement for the other countries. The heterogeneity of green productivity across the resource's classification exhibits significant disparity. The technology gap also prevails among the two resource classifications of African countries. The GML index indicates that Africa's green productivity is mainly explained by technical change instead of efficiency change. The bootstrap truncation regression suggests an inverted U‐shaped nexus between growth and green productivity in Africa and resource‐intensive countries (RIC). Green environmental entrepreneurship positively affects green productivity in Africa. On the components of institutional quality, we observed that the rule of law positively influences green productivity in non‐resource‐intensive countries (NRIC) and the whole of Africa. In contrast, political stability, government effectiveness, voice and corruption negatively affected green productivity in NRIC. Also, foreign direct investment (FDI) and sovereign debt vulnerability negatively correlate to green productivity in Africa as a whole and NRIC, respectively. The findings of this study aid in raising awareness of green productivity in developing countries, which is crucial in boosting global green development.

A new cross-efficiency meta-frontier analysis method with good ability to identify technology gaps

Cross-efficiency evaluation and meta-frontier analysis (MFA) have been widely used to measure performance in many areas. However, cross-efficiency MFA (CMFA) has rarely been studied due to its potential violation of the basic MFA property, that is, the efficiency relative to the group frontier is not less than that relative to the meta-frontier. In this paper, we deduce the conditions under which the cross-efficiency score generated by the current CMFA method relative to the group frontier is smaller than that relative to the meta-frontier, and the conditions under which the current CMFA method is unable to identify the technical gaps between the group frontiers and the meta-frontier. To guarantee the basic property and identify technical gaps, we introduce a new CMFA method, where the efficiencies relative to the group frontiers are first cross-evaluated by the traditional cross-evaluation approach and then those relative to the meta-frontier are cross-evaluated by using modified data envelopment analysis models. Compared with the existing CMFA method, our approach has the following advantages: it can successfully ensure that the cross-efficiencies and cross-efficiency scores relative to the group frontiers are not less than those relative to the meta-frontier; it has a good identification of technology gaps and provides more detailed information about the inefficiency; all the mathematical programming models involved in our CMFA method are feasible. Theoretical analyses and numerical examples support the practicality and superiority of our method.

Impacts of positive and negative corporate social responsibility on multinational enterprises in the global retail industry: DEA game cross-efficiency approach

This study aims to investigate the effects of corporate social responsibility (CSR) on corporate performance in the global retail industry. We adopt the modified data envelopment analysis (DEA) game cross-efficiency approach in assessing the longitudinal efficiency of a sample of 414 listed retail firm-year observations given by Forbes 2000 between 2013 and 2018. The performance result indicates that the Americas retail industry is growing steadily and continues to dominate other regions. Not only the retail industry but all industries in Europe have severe environmental safety rules and management requirements in business operations, hence, Europe also scored high in both the overall environmental index in CSR and all their component indices. Additionally, panel regression revealed that the environmental dimension in CSR is significantly and directly correlated to firm performance. This study’s findings will provide practitioners and policymakers with managerial and strategic implications to enhance their efficiency by applying the CSR dimension in the retail industry.

An integrated socially responsible-efficient approach toward health service network design.

Despite the fact that medical responses are crucial for saving precious lives during any humanitarian crisis (e.g., the COVID-19 pandemic), healthcare infrastructure in many communities are partially covered or are not covered yet. In order to strengthen the health system response to such crisis, especially in low- to middle-income communities, this paper extends a novel multi-objective model for designing a health service network under uncertainty which simultaneously considers efficiency, social responsibility, and network cost. For efficiency, a modified data envelopment analysis model is introduced and inserted into the proposed model to decrease the inefficiency of healthcare facilities belonging to the different tiers of the health system. For social responsibility, two measures of job creation and balanced development are incorporated into the extended model. This is not only considered to cope with the increased numbers of patients and disaster victims to healthcare facilities but also to deal with the challenge of the economy and the livelihoods of people during the crisis. Moreover, a novel mixed possibilistic-flexible robust programming (MPFRP) approach is developed to protect the considered network against uncertainty. To show the applicability of the extended model, a real-world case study is presented. The results reveal that contrary to fuzzy programming models, the MPFRP performs well in terms of social responsibility (72%), cost (8%), and efficiency (28%) and is able to make a trade-off between these three measures. In this study, the resilience level of the designed network is not addressed while disregarding any short-term stoppage owing to internal or external sources of disruption in designing may bring about a considerable loss.

Energy, environmental, and economic efficiency in fossil fuel exporting countries: A modified data envelopment analysis approach

Abstract Due to increasing concerns about high energy consumption and global warming, the energy and environmental efficiency have gained considerable attention of researchers and policymakers. The purpose of this study is to examine the energy, environmental, and economic (E3) efficiency in fossil fuel exporting countries during 2015-2017, using traditional Data Envelopment Analysis (DEA) and a bargaining game cross-efficiency DEA approach. Based on the results, the average energy, economic and environmental efficiencies are equal to 0.77, 0.8, and 0.26, respectively. The results of DEA approach show that the efficiency performances are different in each country, and it is not possible to accurately determine the equilibrium points considering all three measures. Therefore, the efficiency performance of E3 is examined by an integrated model of bargaining game cross-efficiency DEA. Obtaining the product of Nash bargaining payoffs, the countries are ranked in terms of efficiency performance. Countries including China, Oman, Bahrain, Romania and Poland have the top five rankings, respectively. Countries with lowest five rankings include Gabon, Saudi Arabia, Albania, Algeria and Georgia, respectively. Comparing the results of the DEA approach and Nash bargaining game-DEA model shows that the second model is more suitable for ranking due to the unique solution.

Technical efficiency in health production: A comparison between Iran and other upper middle-income countries

ObjectivesTo achieve sustainable health development, health systems need to constantly enhance their efficiency, through for instance reducing waste of resources. This study aimed to measure the efficiency in producing health in Upper Middle-Income Countries (UMICs) with a focus on Iran. MethodA modified data envelopment analysis (DEA)-based Malmquist Productivity Index (MPI) was used to assess the changes in health productivity. Panel data was extracted from databases of the World Health Organization and the World Bank for the period of 2009–2015. ResultsThe efficiency score of 13% of countries was higher than 0.8, while the score of all countries was above 0.5. The average score of Iran performance was 0.791 during the period. On average, performance improved in 15 countries, while it declined in 20 countries during the study period. ConclusionDifferent countries have implemented various health reforms to improve efficiency. We envisage, policy makers in the UMICs locate their health system performance and plan to improve it in line with the local specifications, along with the global pathway towards universal health coverage and sustainable health development ultimately.

A two-stage model for monitoring the green supplier performance considering dual-role and undesirable factors

PurposeThe purpose of this paper is to monitor the environmental efficiency of suppliers in the presence of undesirable output and dual-role factors with static and dynamic aspects. Meanwhile, it also aims to explain the main reason for the low efficiency of suppliers.Design/methodology/approachThe authors propose a modified data model considering undesirable output and dual-role factors. The study integrates the modified data envelopment analysis model into the distance function of the Malmquist–Luenberger index. Moreover, this study uses the global benchmark technology to formulate a two-stage model. To verify the validity of this model, a model application is conducted on an automotive spare components company in China.FindingsThe results identify the unique status of dual-role factors based on the global optimality of the model and then categorize inefficient suppliers in an individual evaluation cycle. In addition, each supplier is projected on a frontier curve after obtaining the improved data. Furthermore, through the status plot of M-L and its components, this paper concludes that efficiency scale change is the main reason for the gap in ecological performance between different suppliers.Research limitations/implicationsThe proposed model considers both undesirable output and dual-role factors; however, variables with different features, such as imprecise, fuzzy and qualitative characteristics, can be embedded into the presented two-stage model.Originality/valueEvaluating green suppliers through multiple consecutive evaluation cycles will aid a company in effectively managing its key suppliers. Furthermore, the evaluation provides policy guidance for further improvement of suppliers.

Estimations of operational efficiencies and potential income gains considering the credit risk for China’s banks

This paper proposes a method framework to estimate operational efficiencies and potential income gains considering the credit risk for banks. The method refers to the optimization of operational income, interest income, and non-performing loan amounts. As main innovations, potential interest income gains from credit technology improvement and loan provision reduction are detected. Operational capability restriction is considered by an inverse-like DEA model. Based on an empirical study of Chinese banks, some suggestions are obtained: (1) diverse operational efficiencies are observed for bank groups. Operational efficiencies of rural commercial banks became worse after going public. (2) For city-owned and rural commercial banks, the investment performance and financial services should be improved to increase operational incomes. Excessive loan provision should be cautious to forbid more non-performing loans. (3) Credit risk technology improvement should be addressed by state-owned and rural commercial banks. Their operational inefficiencies are mainly from weak credit risk control.Research HighlightsA modified data envelopment analysis for output optimisation is proposed.Potential interest gains have been decomposed into parts for different causes.Operational capacity restrictions are considered in potential output estimations.The approach is applied to measure banks’ operational performance in China.Future suggestions for bank groups are provided in the empirical study.

An innovative super-efficiency data envelopment analysis, semi-variance, and Shannon-entropy-based methodology for player selection: evidence from cricket

The increasing interest in club cricket and online fantasy cricket league games raises the importance of player selection from the perspective of financial and sports performance. Most previous studies focus only on player efficiency and ignore consistency and the player’s importance in a team strategy. This scenario motivates us to design a holistic player selection method based on a player’s efficiency, consistency, and importance in a team strategy. For efficiency measurement, we apply a modified data envelopment analysis (DEA) method, namely, the non-increasing return-to-scale ‘super-efficiency DEA model,’ that provides improved results compared with the conventional Banker, Charnes, and Cooper DEA model in the presence of a higher number of efficient players. We design a modified consistency index based on the semi-variance approach. Unlike the existing methods that apply a player-specific reference frame to capture variability, we use a common reference frame that calculates the consistency in a more effective manner. We aggregate different consistency indices into a single consistency index using Shannon’s entropy concept and introduce a novel ‘value index’ to determine player importance, which can also be used as an indirect measure of the player’s fitness level. Finally, we design a player performance index by aggregating the efficiency and consistency scores using the Shannon-entropy method and incorporating the value index. We perform a rigorous numerical analysis to determine the all-time best one-day international Cricket XI team for the time span of January 5, 1971 to March 29, 2015. Next, we explain the advantages as well as rationale behind the improvement in the proposed measures compared with the existing methods and highlight the key insights. Finally, we perform a comparative analysis of the proposed team, the team announced by the ICC in 2011, and the team announced by the BBC in 2015.

Industrial carbon abatement allocations and regional collaboration: Re-evaluating China through a modified data envelopment analysis

China’s commitment to significantly reducing carbon emissions faces the twin challenges of focusing costly reduction efforts, whilst preserving the rapid growth that has defined the country’s recent past. However, little work has been able to meaningfully reflect the collaborative way in which provinces are assigned targets on a sub-national regional basis. Suggesting a modified data envelopment analysis (DEA) approach which recognises the two objectives of income maximization and pollution abatement cost minimisation, this paper introduces the potential collaboration between industrial units to the modelling framework. Our theoretical work exposits the roles collectives of industrial decision making units may play in optimising against multiple target functions. Considering the period 2012–2014, we illustrate clearly how China’s three regional collaborations interact with the stated aims of national policy. Developed eastern China may take on greater abatement tasks in the short-term, thus freeing central and western China to pursue the economic growth which will then support later abatement. Policy-makers are thus given a tool through which an extra layer of implementation can be evaluated between the national allocation and setting targets for regional individual decision making units. China’s case perfectly exemplifies the conflicts which must be accounted for if the most economical and efficient outcomes are to be achieved.

Eco-efficiency Convergence and Green Urban Growth in China

Eco-efficiency measures if economic growth and environmental protection are effectively balanced. To understand the path of green urban growth in China, this article examines the converging patterns of eco-efficiency for 191 Chinese cities within 2003 and 2013. Two types of modified Data Envelopment Analysis (DEA) methods and spatial modeling approach are adopted in empirical analyses, with cities grouped based on three types of heterogeneities that facilitate the formation of potential convergence clubs. We find that major Chinese cities are β-converging in their eco-efficiency scores and are forming place-based convergence clubs in terms of geographical location, environmental policy, and resource endowments. Less efficient clubs are converging at a faster speed toward low-level steady states, while more efficient clubs are reaching separate high-level equilibria with relatively slow rates and longer half-life. We further raise corresponding policy implications that aim at retarding or reversing the ongoing trend of eco-efficiency deterioration.

Estimation of carbon efficiency decomposition in materials and potential material savings for China's construction industry

As an important source of carbon emissions, the carbon emission performance of construction materials should be measured for China's construction industry. This paper proposes a modified data envelopment analysis (DEA) to analyze the carbon efficiency decomposition and potential material reduction for regional construction industries. As the main innovation, the carbon efficiency decomposition of cement, steel, and aluminum is estimated. To achieve the minimal regional carbon intensities, modified potential material reductions are estimated by creatively identifying correlations between the material consumption and economic outputs. This paper conducts an empirical study of China's regional construction systems from 2006 to 2015. Some conclusions are achieved. The carbon efficiencies of construction materials are inefficient in most regions, which are derived from the inefficient material consumption. All of the decomposed carbon efficiencies are decreasing from the east to the west with enlarging geographic disparities from 2006 to 2015. The consumption for each construction material is optimized for China's regions. Some policy implications are also provided.

Efficiency Analysis of Healthcare System in Lebanon Using Modified Data Envelopment Analysis

The inflow of refugees from Syria into Lebanon necessitates a robust and efficient healthcare system in Lebanon to withstand the growing demand for healthcare service. For this purpose, we evaluate the efficiency of healthcare system in Lebanon from 2000 through 2015 by applying a modified data envelopment analysis (DEA) model. We have selected four output variables: life expectancy at birth, maternal mortality ratio, infant mortality rate, and newly infected with HIV and two input variables: total health expenditure (% of GDP) and number of hospital beds. The findings of the paper show improvement in the efficiency of the healthcare system in Lebanon after the widespread of the health system reform in 2005. It also shows that reduction in health expenditure does not necessarily reduce efficiency if operational and technical aspect of the healthcare system is improved. The study infers that the healthcare system in Lebanon is capable of withstanding the increase in health demand provided further resources are made available and the existing technical and operational improvement are maintained.

Will Pollution Taxes Improve Joint Ecological and Economic Efficiency of Thermal Power Industry in China?: A DEA‐Based Materials Balance Approach

SummaryPrevious studies of the efficiency of Chinese electricity industry have been limited in providing insights regarding policy implications of inherent trade‐offs of economic and environmental outcomes. This study proposes a modified data envelopment analysis method combined with materials balance principle to estimate ecological and cost efficiency in the Chinese electricity industry. The economic cost and ecological impact of energy input reallocation strategies for improving efficiency are identified. The possible impacts of pollution taxes upon the levels of sulfur dioxide (SO2) emissions are assessed. Estimation results show that (1) both energy input costs and SO2 could be reduced through increasing technical efficiency. (2) It is possible to adjust energy input mix to attain ecological efficiency, and, correspondingly, SO2 would be reduced by 15%. (3) The Chinese electricity industry would reduce its unit cost by 9% if optimal ecological efficiency is attained and reduce its unit pollution by 13% if optimal cost efficiency is attained, implying that there are positive ecological synergy effects associated with energy cost savings and positive economic synergy effects associated with SO2 pollution reductions. (4) Estimated shadow costs of SO2 reduction are very high, suggesting that, in the short term, the Chinese electricity industry should pursue cost efficiency instead of ecological efficiency, since alternative abatement activities are less costly and some of the abatement cost could be further offset by energy input cost savings. (5) There would be no significant difference between the impacts of pollution discharge fees and pollution taxes on SO2 emissions levels because of the relatively low pollution tax rate.

Assessing the efficiency of the accounting industry using multiactivity network DEA: evidence from Taiwan

AbstractAccounting firms are highly specialized and subject to government recognition through professional licenses. Accordingly, in assessing an accounting firm's performance, the performance measurement system should be generic enough to provide an integrated view of important factors from different perspectives. However, traditional performance measurements are based on several predefined factors that provide a partial view of the system or are limited to a single activity, thereby ignoring their interactions. This study proposes a modified data envelopment analysis model with multiactivity and network techniques on accounting firms. It creates a realistic approach to adequately measure the efficiency of the accounting industry and to suggest possible improvements for accounting firms. To verify the effectiveness of the model, we assessed the performance of 298 Taiwanese accounting firms in 2010 with three parallel‐connected activities and two series‐connected performance management processes. The results show that Taiwanese accounting firms greatly benefit from service processes and taxation activities.

Evaluating the efficiency of cloud services using modified data envelopment analysis and modified super-efficiency data envelopment analysis

Several cloud services with comparable functionality are now available to customers at different prices and performance levels. Often, there may be trade-offs among different functional and non-functional requirements fulfilled by different cloud providers. Hence, it is difficult to evaluate the relative performances of the cloud services and their ranking based on various quality of service attributes. In this paper, we propose a modified data envelopment analysis and a modified super-efficiency data envelopment analysis for evaluating the cloud services and their efficiencies considering user preferences. We compare these methods of cloud service selection based on sensitivity analysis, adequacy to changes in DMUs, adequacy to support decision making and modeling of uncertainty. The comparison helps customers to choose a cloud service that is most suitable to their requirements and also creates a healthy competition among the cloud service providers.

A comparative study between Modified Data Envelopment Analysis and Response Surface Methodology for optimisation of heterogeneous biodiesel production from waste cooking palm oil

Biodiesel is a clean renewable fuel which is an alternative source of diesel fuel in compression ignition engines without any modification. According to previous research, the importance of biodiesel production through heterogeneous transesterification of waste cooking palm oil (WCPO) over Sr/ZrO2 catalyst has led to developing a new mathematical algorithm called Modified Data Envelopment Analysis (MDEA). MDEA, a hybrid of Data Envelopment Analysis (DEA) with Neural Network (NN), was proposed for experiment design of multi-response problems. It was validated with Response Surface Methodology (RSM), which is a statistical method. This method was developed to maximise Fatty Acid Methyl Ester (FAME) yield and five decision variables were considered. The optimum amount of methanol to oil molar ratio, catalyst loading, reaction temperature, reaction time on Ester yield, and free fatty acid (FFA) conversion were calculated via MDEA method. The obtained results showed that the derived optimal parameter-setting of the proposed method, MDEA, is more reliable and accurate than RSM. The errors of predicted Ester yields are 5% and 14% in MDEA and RSM. The calculated errors of conversions are 3% and 19% in MDEA and RSM.

From equality to diversity: Classifying Russian universities in a performance oriented system

Over the last few decades, performance-based funding models of universities have been introduced and have made universities build and implement different strategies to enable them to compete and be viable in changing circumstances. In turn, national governments are focused on providing universities with more opportunities to run efficient programmes that advance higher education. This paper includes a detailed review of various taxonomies for structuring university. More importantly, it develops a typology of higher education institutions that is relevant for the Russian context. The Ward method is used to cluster universities on the basis of university distinctions in terms of the availability of resources, education, and research and development. This typology of universities is verified by assessing their efficiency score gained from modified Data Envelopment Analysis, incorporating universities' heterogeneity. Finally, the paper gives a decision tree for classifying universities bearing in mind their diversity. It might be expanded for a broader set of inputs and outputs, namely external project-based research funding modes and cooperation between universities and industry to pursue the development of innovation. The results can be used for shaping targeted policies aimed at particular university groups.

Total-factor energy efficiency in China’s sugar manufacturing industry

Purpose – The purpose of this paper is to evaluate the total-factor energy efficiency (TFEE) in China’s sugar manufacturing industry using firm-level data from 2002/2003 to 2012/2013 crushing seasons, and further explore the determinants of TFEE. Design/methodology/approach – Modified data envelopment analysis is used to measure the TFEE of each sugar mill during the crushing seasons. Then heteroskedastic fractional probit model is applied to estimate the determinants of TFEE because of the bounded nature of TFEE and heteroskedasticity of unbalanced panel. Findings – The results show that throughout the crushing seasons, the average TFEE is 0.57; there are spatial differences of TFEE in Guangxi sugar industry, highest in southern area; the TFEE of foreign-owned sugar mills is larger than that of private-owned and state-owned sugar mills; the larger the enterprise size, the higher the TFEE; private ownership, large size, raw material, safe productivity, total recovery rate as well as technical progress can improve TFEE significantly. Originality/value – This paper analyzes TFEE using a rich data set at firm level, allowing the existence of firm heterogeneity, as well as being complementary to the study of energy efficiency in China’s sugar industry. Moreover, ownership structure is involved in the determinants of TFEE, which is rarely done in literature. Lastly, heteroskedastic fractional probit model is employed to recognize the bounded nature of TFEE as well as selection bias of unbalanced panel to study the determinants of TFEE.