Slacks-based Measure Data Envelopment Analysis Research Articles

Provincial-scale assessment of vulnerability and resilience to drought in China

Frequent droughts have caused severe disaster losses in China. Such events can be minimized by enhancing the country's resilience and reducing its vulnerability, where this can ensure socioeconomic stability and sustainable development. Evaluating the vulnerability and resilience to drought is thus crucial for effectively managing the risk of disasters and promoting sustainable socioeconomic development. In this study, we constructed a comprehensive framework to assess the spatiotemporal characteristics of China's vulnerability and resilience to drought at the provincial scale from an input-output perspective by using the Super-Efficiency Data Envelopment Analysis (DEA) model and the Super-Efficiency Slacks-Based Measure DEA (SBM-DEA) model. This study focused on drought drivers, the disaster-forming environment, drought bearers, disaster intensity, and recovery. The results showed that the vulnerability to drought of 42 % of China's provinces decreased from 2010 to 2022, that of only 29 % of the provinces increased, while the status of a majority of provinces improved in general. The center of gravity of the vulnerability to drought moved toward the southwest over time and a spatial clustering of vulnerability was observed, with High-High clusters moving from the north to the south. Moreover, the resilience to drought declined in 36 % of provinces and increased in only 20 %, reflecting poor resilience overall. The center of gravity of China's overall resilience to drought moved northward, with a relatively stable spatial pattern and prominent clusters of Low-Low resilience indicating a pressing need for improvement. Areas with high vulnerability and low resilience were concentrated in inland western and eastern regions, and this highlights the importance of drought prevention and mitigation in provinces like Xinjiang, Inner Mongolia, Jiangxi, and Fujian. The findings here provide valuable insights for mitigating the risk of drought and promoting sustainable socioeconomic development.

Spatial and temporal variation and convergence in the efficiency of high-standard farmland construction: Evidence in China

To assess the efficiency of high-standard farmland construction (HSFC), this study utilized data spanning from 1998 to 2020 obtained from 30 provinces, autonomous regions, and municipalities in China. This assessment was conducted using a three-stage super-efficient slack-based measure data envelopment analysis(SBM-DEA)model. Furthermore, we investigated the spatial and temporal variances and convergence of HSFC efficiency using the Dagum Gini coefficient and convergence analysis. The results firstly show that from 2007 to 2020, China's HSFC efficiency displayed fluctuations and declines, significantly influenced by environmental and stochastic factors. Secondly, it showed that the gap in China's HSFC efficiency has widened, with super-variable density being demonstrated as the primary source of spatial imbalance in HSFC efficiency. Thirdly, it showed that the deviation in the efficiency of HSFC in the central region of China from the average level has shown a gradually declining trend, while the deviation in the efficiency of HSFC in the national, western, eastern, and northeastern regions has not presented a downward trend. Fourthly, it demonstrated that over time, the efficiency of building high-standard agriculture throughout the nation and its four main areas will converge to the same level.

Bridging the gap: coordinating equity and efficiency in older people care resource allocation in China

BackgroundWith the increasing global aging population, how to allocate older people care resources reasonably has become an increasingly urgent international issue. China, as the largest developing country, has made many efforts to actively respond to the challenges of an aging population. However, there are still problems with uneven allocation of older people care resources and low efficiency of allocation. Therefore, this study evaluates the regional differences and dynamic evolution of the equity and efficiency of older people care resource allocation in China from 2009 to 2020, and explores ways to change the current situation.MethodsThe data used in this study were derived from the “China Statistical Yearbook” and the “China Civil Affairs Statistical Yearbook” for the period of 2010–2021. Firstly, the equity of older people care resource allocation was measured using the Gini coefficient, the Theil index, the Older People Care Resource Density Index, and the Older People Care Resource Agglomeration Degree. Secondly, the dynamic Slack-Based Measure data envelopment analysis method was adopted to evaluate efficiency. Lastly, the Z-score is used to normalize the equity index and perform classification matching with the efficiency value. Spatial autocorrelation analysis and hotspot analysis were conducted using GIS technology to examine the dynamic evolution process of older people care resource allocation equity and efficiency, as well as their spatial distribution patterns and coordination across provinces from 2009 to 2020.ResultsThe equity analysis showed that the spatial distribution of various types of older people care resources was uneven, and the differences were mainly due to internal differences within each region, with the largest equity differences observed in western provinces. Currently, older people care resources are mainly concentrated in eastern regions, while the total amount of older people care resources in western regions and some central regions is relatively small, which cannot meet the older people care needs of residents. The efficiency analysis results showed that the efficiency of older people care resource allocation has been improving over the past 12 years, and in 2020, 77.42% of provinces were located on the efficiency frontier with an average efficiency value of 0.9396. Finally, the coordination analysis results showed that there were significant spatiotemporal differences in the equity and efficiency of older people care resources allocation.ConclusionWith the development of society and economy, the total amount and service capacity of older people care resources in China have greatly improved. However, there are still significant spatiotemporal differences in the equity and efficiency of older people care resource allocation. The development of older people care services in central and eastern provinces is unbalanced, and there is a polarization trend in terms of equity and efficiency of older people care resource allocation. Most provinces in western regions face the dual dilemma of inadequate older people care resources and low utilization efficiency. It is recommended that policymakers comprehensively consider population and geographic factors in different provinces, establish relevant allocation standards according to local conditions, improve the redistribution system, and focus on increasing the total amount of older people care resources in underdeveloped provinces while promoting resource flow.

A [formula omitted]-Number Slacks-Based Measure DEA model-based framework for sustainable supplier selection with imprecise information

The focus of this study is to develop a decision-making framework for selecting sustainable suppliers with imprecise information. Sustainable supplier selection poses a significant challenge for managers and decision-makers seeking a long-term competitive edge. Due to the presence of unreliable, or partially reliable imprecise information in practice, incorporation of the reliability degree of imprecise information in the decision models becomes necessary. Since Z-numbers can incorporate the reliability degree of imprecise information, the Z-number-based “Data Envelopment Analysis (DEA)” approach can be used for decision-making. The current study introduces a super-efficiency DEA approach, namely “Z-number Slacks-Based Measure (ZN-SBM)”, which is further used to construct a framework for selecting sustainable suppliers. Unlike the existing Z-number-based DEA approaches, the proposed ZN-SBM model can assume “constant returns-to-scale”, “variable returns-to-scale”, “non-increasing returns-to-scale”, and “non-decreasing returns-to-scale” conditions. Moreover, the developed framework is free from strategic weight manipulation. To demonstrate the efficacy of this framework in sustainable supplier selection, we present a case study of the automotive industry. Further, the robustness of the proposed framework is investigated through a sensitivity analysis. The results of this study reveal that the proposed framework can be effectively applied as a high-performing decision-support tool for decision-making under imprecision in the domain of sustainable supplier selection.

Impact of environmental regulation intensity on the efficiency of sustainable economic growth in the European Union

Environmental pollution is an essential constraint to the sustainable growth of regional economy. This paper uses the super efficiency slacks-based measure data envelopment analysis (SBM-DEA) model to measure the efficiency of sustainable economic growth (ESEG) in the European Union (EU) and applies the spatial econometric model to explore the impact of environmental regulation intensity (ERI) on ESEG in the EU. The results show that the ESEG in the EU shows an N-shaped growth trend and the spatial pattern of “Western Europe > Eastern Europe > Central Europe > Northern Europe > Southern Europe” from 2001 to 2019. The impact of ERI on the ESEG in the EU presents a “U" shape, indicating that increasing ERI first reduces ESGE, and after reaching the turning point of ESGE, continuing to increase ERI will promote ESGE. Further analysis shows the ERI have spatial spillover effect on the ESEG, while the spatial spillover effect in the eastern and western regions of the EU is different. Improving the ERI in the western region is not only conducive to the ESEG of the country but also has a positive spillover effect on neighboring countries. However, the spatial agglomeration effect in the eastern region is not significant. In addition to environmental regulation, labor & capital structure, research and development (R&D) expenditure, GDP per capita and trade value have a significant impact on the ESGE of a country and neighboring countries.

The efficiency evaluation and the spatiotemporal differences of CO2 emissions in China's construction industry

Under the promotion of China's double carbon policy, China's construction industry (CI) is facing the pressure for CO2 emissions (CE) reduction. In order to promote China's high-quality green development, CO2 emissions efficiency (CEE) evaluation in China's CI was crucial. Based on the super-efficiency slacks-based measure–data envelopment analysis (SBM-DEA) model, the Global Malmquist-Luenberger (GML) index, the global and local Moran index in spatial autocorrelation, 11 indicators of CI were selected to evaluate CEE and the spatiotemporal differences of CEE in China's CI 31 provinces from 2000 to 2020 were analyzed. The results indicated the CEE was on the rise on the whole. The average annual CEE of Hainan, Heilongjiang, Tianjin, Shanghai and Xizang was bigger than 1. The CEE of Sichuan, Gansu and Guizhou was around 0.5. The order of CE of CI in China from high to low Was South China, North China, Northeast China, Central China, East China, Northwest China and Southwest China. The GML index increased by 6.25% annually, the average annual TC increased by 11.68%, and the average annual EC increased by 5.21%. The overall CEE of China's CI showed a positive correlation between 2010 and 2015, but the spatial agglomeration was weak.

The effect of electricity market reform on energy efficiency in China

Since 2015, China has embarked on a new round of reforms to further promote marketization of the power sector. The present study evaluates this reform by exploring its impact on energy efficiency in China using a novel integrated approach. First, to distinguish the heterogeneous impacts of the reform on energy production and consumption sectors, this study identifies energy efficiency into production efficiency and utilization efficiency based on the super-efficiency network slacks-based measure–data envelopment analysis (SBM–DEA) with an undesirable output. Thereafter, we identify the impact of the reform on energy production and utilization efficiencies by applying a multi-period difference-in-differences (DID) method. We find that the energy efficiency of most provinces of China is relatively low, and energy production efficiency is generally lower than energy utilization efficiency. Although energy efficiencies of most provinces show an upward trend after 2015, the efficiency gap across provinces has increased over time. Moreover, the market reform has no significant impact on energy production efficiency. However, the reform significantly improves energy utilization efficiency, and this effect is sustainable after the reform. The study findings extend our understanding of the effects of the reform and suggests that this reform introduces heterogeneity in the energy sector. This study also holds significant policy implications for furthering the power system reform and narrowing the energy efficiency gap across regions in China.

Evaluation and comparative analysis of urban public institutions energy-environmental efficiency from the perspective of dual carbon

The ‘dual carbon’ goals are China's long-term development strategy for low greenhouse gas emissions in the mid-21st century, and energy conservation and emission reduction are major decisions and plans made by the Chinese government to achieve the ‘dual carbon’ goals. Energy conservation in public institutions is the focus of China's 14th Five-Year Plan, the accurate evaluation of energy efficiency is a prerequisite for energy conservation in public institutions and an important element in achieving China's dual carbon goals. Therefore, we propose the Slacks Based Measure-Data Envelopment Analysis (SBM-DEA) model considering carbon emissions to evaluate the energy-environmental efficiency of urban public institutions in subtropical regions of China and apply the Gini coefficient to measure the unbalanced development of energy-environmental efficiency in similar institutions. The results demonstrate that: (1) The current energy-environmental efficiency of urban public institutions is 0.83, and there are significant differences in the energy-environmental efficiency of different types of public institutions; (2) The average value of institutional scale efficiency is close to the optimal level, and the main factor currently limiting the energy-environmental efficiency of urban public institutions is pure technical efficiency; (3) The average energy-environmental efficiency of the model considering the unexpected carbon emission indicators of public institutions is 1.82% higher than the model without carbon emission. Due to its non-parametric nature, this method shows good applicability for multi-input and multi-output energy-environmental efficiency assessment, which could be a guideline for quantifying the energy-saving potential of public institutions.

An integrated approach of discrete event simulation and a non-radial super efficiency data envelopment analysis for performance evaluation of an emergency department

An emergency department (ED) has been considered as one of the most congested department in a hospital. The congestion is typically contributed by long waiting time to get medical service, primarily caused by insufficient resource allocation or improper resource configurations. However, how various resource allocation configurations affect ED performance and how their efficiency can correctly be evaluated, using an integrated approach is rarely discussed. This paper thus integrates discrete event simulation (DES) and data envelopment analysis (DEA) to measure ED performance and evaluate the efficiency of potential resource allocation configurations for future performance improvement. For this, a DES model for an ED is first designed and developed. Its performance improvement is then tested using 35 potential resource allocation configurations, and their impacts on the performance are measured. To evaluate their efficiency and identify the optimal configuration, a mixed integer super efficiency of slacks-based measure data envelopment analysis (SE-SBM-DEA) approach dealing with undesirable outputs is proposed. The model utilizes resource allocation as inputs and simulation performance measures as outputs. All inputs were considered as integer, while the outputs were classified into desirable and undesirable in mixed integer-valued data. The desirable real outputs are the utilization of receptionists, nurses and doctors. The undesirable real outputs are the average of patient cycle time and time spent in queues, while the undesirable integer output is average number of patients in queues. The desirable integer output is average number of patients received treatment. The results obtained from the DEA approach show that 21 efficient resource configurations have the capability to increase their inputs, undesirable outputs and/or decrease desirable outputs simultaneously without affecting their efficiency status. The integrated approach helps decision makers manage their healthcare facilities by identifying the sources of inefficiency and (the maximum levels of inputs-undesirable outputs and minimum levels of desirable outputs) to improve and (retain) efficiency.

Optimum combination of heterogeneous environmental policy instruments and market for green transformation: Empirical evidence from China's metal sector

Based on the new structural economics view that the combination of effective governments and efficient markets is the fundamental path to high-quality development, this study investigates how heterogeneous environmental policy instruments combine with marketization to improve the total factor energy-environmental efficiency (TFEEE) in China's metal sector. Utilizing the provincial panel data from 2006 to 2019, a super-efficiency slacks-based measure data envelopment analysis (SBM-DEA) integrated with the global Malmquist-Luenberger (GML) index is employed to estimate the energy-environmental efficiency and its dynamic changes. The evaluation results imply a significant increasing trend in the energy-environmental efficiency, but the overall level is rather low with disparities between sub-sectors and different regions. Using a dynamic panel threshold model, the “strong” version of the Porter Hypothesis is validated that command-and-control environmental policy (CEP), market-incentive environmental policy (MEP), and voluntary environmental policy (VEP) have an optimum stringency range to induce TFEEE growth, while the impact modes are drastically diverse. Further study verifies that higher marketization is conducive to triggering the facilitation effect of heterogeneous environmental policy instruments on the TFEEE but with completely different threshold values of marketization, which decrease sequentially corresponding to VEP, CEP, and MEP.

Role of renewable, non-renewable energy consumption and carbon emission in energy efficiency and productivity change: Evidence from G20 economies

The challenge of achieving sustainable economic development with a secure environmental system is a global challenge faced by both developed and developing countries. Energy Efficiency (EE) is crucial in achieving sustainable economic growth while reducing ecological impacts. This research utilizes the Slack-Based Measure Data Envelopment Analysis (SBM-DEA) and the Malmquist-Luenberger Index (MLI) method to evaluate EE and productivity changes from 1995 to 2020 across G20 countries. The study uses four different input–output bundles to gauge the impact of renewable and non-renewable energy consumption and carbon emissions on EE and productivity changes. The study results show that including renewable energy consumption improves the average EE from 0.783 to 0.8578, but energy productivity declines from 1.0064 to 0.9988. Incorporating bad output (carbon emissions) in the estimation process enhances renewable EE and productivity change, resulting in an average EE of 0.6678 and MLI of 1.0044. Technological change is identified as the primary determinant of energy productivity growth in scenarios 1 and 2, while technical efficiency determines energy productivity change in scenarios 3 and 4. The Kruskal-Wallis test reveals a significant statistical difference between the mean EE and MLI scores of G20 countries.

Regional Differences in PM2.5 Environmental Efficiency and Its Driving Mechanism in Zhejiang Province, China

Improving the digital economy and environmental governance efficiency are important methods for current high-quality economic development. Based on the panel data of 11 cities in Zhejiang, on the eastern coast of China, fine particulate matter smaller than a 2.5 μm (PM2.5) environmental efficiency (PMEE) was measured by the undesirable output Slack-Based Measure-Data Envelopment Analysis (SBM-DEA) model. The fixed effect regression model, the divergences in the difference model and other empirical methods were obtained to test the driving mechanism of social-economic factors on the PMEE. The results showed that: (1) the concentration of PM2.5 was continually decreasing, and environmental quality experienced a continuous improvement in Zhejiang province in the observation period, although cities such as Hangzhou, Jiaxing and Shaoxing have relatively severe PM2.5 pollution. (2) The total average value of PMEE in Zhejiang was 0.6430 over the observation period, while there was still a lot of room for improvement when compared to the production frontier. Additionally, PMEE in each city showed a fluctuating growth trend. Cities with a higher PMEE were mainly Zhoushan, Hangzhou and Ningbo. (3) The level of the digital economy had a positive role in promoting the PMEE, which was statistically significant. The level of pollution control and technological innovation also had a significantly positive effect. However, the ratio of the industrial output value to the gross domestic product (GDP) presented a negative effect on the PMEE. In the future, it is suggested that the development of the urban digital economy should be accelerated in an all-around way to improve the efficiency of government pollution control and to improve the technical efficiency of PM2.5 via innovative technological progress.

THE MEASURE OF AIRPORT EFFICIENCY AND OPERATIONAL CAPABILITIES IN SOUTHERN THAILAND

Eight provinces in Thailand’s south tourism-related airports are expected to push for more significant airport expansion. In response to the expansion of the tourism industry in each province of the southern region and the increasing use of services from people in the provinces and neighboring areas, the problem of airports in the eight provinces consists of inefficiency in operating systems and service management. The construction and expansion of infrastructure projects that do not meet the needs of service users need to be improved. Therefore, this study chose a performance measurement tool to help analyze the data using slack-based measure data envelopment analysis (SBM-DEA) to measure the efficiency and operations of all eight airports quantitatively. In addition, the research team used qualitative data to help determine the problem of the input and output factors of all eight airports and used the Tobit regression model to analyze factors affecting the operational efficiency of all eight airports in the southern region of Thailand. According to the study, Nakhon Si Thammarat Airport (NST), Phuket Airport (HKT), Krabi Airport (KBV), Surat Thani Airport (URT), Hat Yai Airport (HDY) and Chumphon Airport (CMJ) also lacked operational efficiency. Almost all airports should have improved input factors, such as number of check-in counters, terminal area, parking area lots and pit stops. Output factors such as number of flights and number of goods. It was also found that Chumphon Airport (CMJ) and Hat Yai Airport (HDY) were also the least efficient in operation. Furthermore, factors affecting the operating efficiency of all eight airports in the southern region of Thailand can be sorted from most influencing factors to least as follows: Airport condition (X4), security (X3), and airport staff (X1), respectively.

Efficiency: Mutual vs. Stock P-L Insurers

This paper reviews evidence from the U.S. property-liability insurance industry that examines technical efficiency between mutual and stock organizational forms. I exploit a modified slacks-based measure data envelopment analysis methodology to estimate technical efficiency of a property-liability insurer relative to a reference set consisting of all such insurers with the same organizational form. Then, I distinguish relative technical efficiency between insurers’ capacity to maximize social capital (reputational efficiency) and to maximize investment returns (investment efficiency). I document statistically significant evidence that mutual insurers outperform stock insurers in terms of reputational and investment efficiencies. My findings thus reflect a newer appreciation of organizational forms in insurance and illuminate how households make key insurance decisions.

Efficiency evaluation of Chinese provincial industry systems: A dynamic two-stage slacks-based measure with shared inputs

<p style='text-indent:20px;'>How to control industrial air pollution is an urgent policy problem to be solved. Through efficiency evaluation, we can test the implementation effect of the policy, to provide decision support for industrial development. China's provincial industrial system consists of production stage and emission reduction stage. Taking the number of industrial waste gas treatment facilities as a carry-over variable (i.e., connecting multiple periods), this study establishes a dynamic two-stage, slacks-based measure data envelopment analysis (SBM-DEA) model considering shared inputs to evaluate the operating efficiency of China's provincial industrial systems from 2011 to 2019. The results show that (1) The industrial waste gas treatment facilities (carry-over variables) have a significant impact on the overall efficiency and stage efficiency of the industrial system; (2) The average overall efficiency and average stage efficiency of the provincial industrial system have improved during 2011-2019, but they are still inefficient, and the inefficiency has certain geographical characteristics; (3) During the 12th Five Year Plan period (2011-2015), the average efficiency of the emission reduction stage was higher than that of the production stage, but the situation reversed during the 13th Five Year Plan period (2016-2019). This study is of great significance to policy makers of industrial air pollution control.</p>

Study on the spatial correlation network structure of agricultural carbon emission efficiency in China

<abstract> <p>Achieving carbon neutrality requires high efficiency in agricultural carbon emissions. This study employs a super efficiency Slack Based Measure-Data Envelopment Analysis (SBM-DEA) model to measure the Agricultural Carbon Emission Efficiency (ACEE) of 31 provinces, cities, and autonomous regions within the Chinese Mainland from 2001 to 2021. Additionally, it utilizes the modified gravity model and a social network analysis to establish the spatial correlation relationship of ACEE, and extensively investigates the characteristics and transmission mechanism of China's spatial correlation network structure regarding ACEE. The findings reveal the following: 1) The spatial correlation relationship of China's ACEE from 2001 to 2021 exhibits a complex network structure; 2) in terms of the overall network structure characteristics of the spatial correlation, the ACEE network demonstrates a high degree of correlation and displays a stable temporal evolution trend; 3) concerning the centrality network structure characteristics of the spatial correlation, most provinces in China experience a continuous decline in point centrality and near centrality, while the interdependence of the ACEE between provinces increases; and 4) regarding the clustering characteristics of the spatial correlation, variations exist in the correlation among the four plates of the ACEE. However, they mostly assume a mediating role, and in 2021, the ACEE network sectors witnessed a robust interoperability.</p> </abstract>

Economic, Energy and Environmental Efficiency of Road Freight Transportation Sector in the EU

The proper development of transportation constitutes the basis for an effectively functioning economy at the national and global levels. On the other hand, transportation significantly impacts the environment and climate. Sustainable transportation management should therefore include both economic, social and environmental aspects. The article aims to comprehensively assess the economic–energy–environmental efficiency of the 27-road freight transport sector in EU countries in 2019. The research was conducted using the non-parametric Data Envelopment Analysis (DEA) method. The Slacks-Based Measure–Data Envelopment Analysis (SBM-DEA) model was used, taking into account unwanted (undesirable) effects. As non-energy inputs in the DEA model used the labor in the road freight transport sector, stock of registered goods vehicles, and the length of the road network. Moreover, the energy consumption by the road freight transport sector was used as energy inputs in the DEA model. Desirable outputs were taken as road freight transport sector revenues and freight work performed by the sector. GHG emissions expressed in CO2 equivalent were treated as undesirable outputs. The research also adopts energy productivity and GHG emission efficiency indicators. The eco-efficiency of the road freight transport sector in EU countries varies. Ten countries have efficient road freight transport sectors. The efficient road freight transport group included Denmark, Germany, Belgium, Lithuania, Luxembourg, the Netherlands, Poland, Portugal, Slovenia and Bulgaria. They efficiently transformed the inputs into outputs. Five countries were recognized as eco-efficiency followers, including Italy, Finland, Slovakia, Sweden and Romania, and 12 countries were characterized by an inefficient road freight transport sector. Based on benchmarking principles for inefficient road freight transport sectors, the changes in input and output levels were proposed to improve efficiency. The relationship between the economic development of EU countries and the eco-efficiency of the road freight transport sector was also analyzed, indicating a positive relationship between the variables but with weak strength. The main contributions of this article are an extension of previous DEA works that assesses the efficiency of the road freight transport sector, also considering undesirable variables. Research conclusions are particularly important for policymakers in the context of management sustainable transportation development in the EU.

Super-SBM DEA and DTW-based analysis of the energy-environmental efficiency in emerging economies

ABSTRACT Achieving high economic growth rates has always been the primary objective of emerging economies. While some countries have experienced phenomenal economic success in recent years, there is widespread consensus that economic prosperity has been accompanied by rapid environmental degradation. This research aims to empirically investigate whether the development process in emerging economies were environmentally efficient. The study computes and analyses the energy-environmental super-efficiency scores for 14 leading emerging economies from 1980 to 2019 using the Slack-Based Measure Data Envelopment Analysis with undesirable output. The study also conducts a similarity analysis using the Dynamic Time Warping non-parametric approach, while the Dynamic Time Warping Barycenter Averaging-k-means algorithm is performed to assign economies to different clusters according to their energy-environmental super-efficiency. The findings divulge some divergence regarding the magnitude and evolution over time of super-efficiency scores. Four emerging economies, Brazil, The Philippines, Pakistan, and Vietnam, have been the most efficient, while South Africa recorded the worst scores during the same period. The Dynamic Time Warping path analysis suggests the presence of lead-lag relationships between the super-efficiency scores of China, as the reference economy, and the other economies. Finally, the Dynamic Time Warping Barycenter Averaging-k-means algorithm suggests the presence of four clusters.

Use of Failure Mode and Effects Analysis (FMEA) for Risk Analysis of Drug Use in Patients with Lung Cancer

It is crucial to investigate the risk factors inherent in the medication process for cancer patients since improper antineoplastic drug use frequently has serious consequences. As a result, the Severity, Occurrence, and Detection rate of each potential failure mode in the drug administration process for patients with lung cancer were scored using the Failure Mode and Effect Analysis (FMEA) model in this study. Then, the risk level of each failure mode and the direction of improvement were investigated using the Slacks-based measure data envelopment analysis (SBM-DEA) model. According to the findings, the medicine administration process for lung cancer patients could be classified into five links, with a total of 60 failure modes. The risk of failure modes for patient medication and post-medication monitoring ranked highly, with unauthorized use of traditional Chinese medicine and folk prescription and unauthorized drug addition (incorrect self-medication) ranking first (1/60); doctor prescription was also prone to errors. The study advises actively looking at ways to decrease the occurrence and difficulty of failure mode detection to continually enhance patient safety when using medications.

A mixed-integer slacks-based measure data envelopment analysis for efficiency measuring of German university hospitals

Standard Data Envelopment Analysis (DEA) models consider continuous-valued and known input and output statuses for measures. This paper proposes an extended Slacks-Based Measure (SBM) DEA model to accommodate flexible (a measure that can play the role of input and output) and integer measures simultaneously. A flexible measure’s most appropriate role (designation) is determined by maximizing the technical efficiency of each unit. The main advantage of the proposed model is that all inputs, outputs, and flexible measures can be expressed in integer values without inflation of efficiency scores since they are directly calculated by modifying input and output inefficiencies. Furthermore, we illustrate and examine the application of the proposed models with 28 university hospitals in Germany. We investigate the differences and common properties of the proposed models with the literature to shed light on both teaching and general inefficiencies. Results of inefficiency decomposition indicate that “Third-party funding income” that university hospitals receive from the research-granting agencies dominates the other inefficiencies sources. The study of the efficiency scores is then followed up with a second-stage regression analysis based on efficiency scores and environmental factors. The result of the regression analysis confirms the conclusion derived from the inefficiency decomposition analysis.