Measure Data Envelopment Analysis Research Articles

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.

Evaluation of undergraduate academic programs through data envelopment analysis and time-to-degree estimates at Spanish public universities

This article proposes nonparametric and parametric methods for conducting meaningful evaluations of academic programs. In particular, it proposes the use of data envelopment analysis (DEA) along with regression analysis for the evaluation of Spanish public universities' undergraduate curricula. Unlike the radial DEA models, which assume an equiproportional expansion of all outputs to achieve efficiency, the current study also relies on the use of non-radial DEA models for assessing the efficiency of Spanish public universities. A non-radial DEA measure (the so-called Russell measure) allows for unlike proportional augmentations in each positive output. In this study, non-radial DEA measures allow us to identify different levels of inefficiency for each output considered (social sciences and non-social sciences degrees). Specifically, the results show that the inefficiency in the production of scientific and technical degrees is greater than that in the production of humanities and social sciences degrees, although there are differences among institutions. Bachelor's degree production time is also estimated, and a duration analysis explains the time to degree. A worrying result is the "excessive" time it takes for a university to produce four-year undergraduate degree programs. The mean graduation time is 5.7 years. The Cox proportional hazards regression shows that a shorter time to graduation is associated with higher teaching quality as well as a higher faculty-to-student ratio. Parametric survival analysis using a lognormal distribution with gamma frailty also verifies these latter results.

A data envelopment analysis model for opinion leaders’ identification in social networks

Through Online Social Networks (OSNs) such as Instagram, X (Twitter), and Facebook, employing Opinion Leaders (OLs) is becoming integral to companies’ strategies for influencing the public. The graph-based methods are one of the most important approaches for finding OLs in OSNs. Social Network Analysis (SNA)-based OLs finding methods deal with a considerable amount of data due to using entire relationships between all of the users in a network, which makes the algorithms time-consuming. Our main goal is to introduce a new method of OLs discovery that works with fewer data and maintains or improves performance metrics. Consequently, a new application of the Data Envelopment Analysis (DEA) method is presented here for OLs identification in social media. Another contribution of this paper is introducing a new framework (OL-Finder Evaluator or OLFE) for validating the OLs’ detection algorithms under imbalanced datasets. DEA methods, when compared with SNA methods, have the advantage of being able to apply over non-graph-based datasets and to work with substantially smaller datasets. In contrast, SNA methods require transparent relationships between people. In this study, we compare both DEA (including CCR and BCC) and SNA measures (including “Betweenness (BC),” “Degree (DC),” “Page Rank (PRC),” “Closeness (CC),” and “Eigenvector (EC)” centralities) on a real Instagram network for OLs detection. Compared with SNA, our proposed method can identify OLs with considerably fewer data. Besides the advantages of DEA for time-saving, close competition exists between the DEA and the SNA methods. On average, DEA performs better in accuracy, precision, recall, and F1-score performance metrics.

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.

Coupling coordination degree of industrial solid waste prevention and treatment efficiencies and its driving factors in China

Both prevention and treatment are crucial for reducing industrial solid waste (ISW). The primary objective of this study is to explore the coupling coordination degree (CCD) of China’s provincial ISW prevention and treatment from the perspective of efficiency analysis during 2011–2020 and then investigate its driving factors in three steps. The first step is to develop a base point network slacks-based measure data envelopment analysis model to address the issue where the indicators (ISW discharged, ISW stored) of some regions are zero during the evaluation of the ISW prevention and treatment efficiencies. Secondly, the CCD model is constructed to investigate the CCD of ISW prevention and treatment efficiencies. Finally, the driving factors of the CCD are explored using the spatial Tobit model. The results show that: (1) In 76.67% of regions, the prevention efficiency is higher than treatment efficiency, and in 23.33% of regions, the treatment efficiency is higher than prevention efficiency. The prevention efficiency of the entire country exhibits a steady downward trend, while the treatment efficiency, on the whole, is increasing. (2) The regions with high coordination are mainly situated in the east, those with moderate coordination are primarily located in the central region, and those with basic coordination are mostly located in the west. Only three regions (Jiangxi, Guangxi, Shaanxi) exhibit moderate imbalance. (3) The improvement of CCD mainly depends on industrial servitization and industrial structure, while property structure, ISW treatment investment intensity, and traffic infrastructure construction significantly impede the increase of the CCD.

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.

Spatiotemporal dynamics and anthropogenic drivers of geological hazard prevention efficiency in China

Rapid socio-economic development and the large-scale anthropogenic activities aggravated the risk of geological hazards, endangering human life and property safety. Understanding the geological hazard prevention efficiency (GHPE) and driving factors is important for promoting the sustainable development, there are few quantitative studies have investigated the GHPE and anthropogenic drivers in China. This study employed the super-efficiency slack based measure-data envelopment analysis (SBM–DEA) model with undesirable outputs and Malmquist–Luenberger (ML) index to investigate the spatiotemporal distribution of GHPE from static and dynamic perspectives. Additionally, the geographically and temporally weighted regression (GTWR) model was utilized to identify the spatial heterogeneity of anthropogenic drivers on GHPE in China. Results showed that GHPE showed a spatial difference of eastern > central > western China, with only 38.71 % provinces were in an optimal prevention condition of the GHPE. An average annual growth rate of GHPE was 5.8 % in China, with a distribution pattern characterized by central > eastern > western China. Furthermore, the spatial heterogeneity of anthropogenic drivers affecting GHPE varied greatly across different regions. Our findings highlighted investment in environmental protection had obviously positive effects on the GHPE, whereas urban population density had markedly inhibited effects in most provinces. Low GHPE was more prevalent in regions with relatively backward economic and technological levels. Effective measures were proposed to promote regional high-quality and sustainable development.

How does civil aviation achieve sustainable low-carbon development? — An abatement–cost perspective

With the rapid development of civil aviation, carbon emissions have brought severe environmental problems. Realizing efficient and sustainable carbon emission reduction is of great significance for achieving green development in civil aviation sector. Therefore, in the process of pursuing civil aviation carbon emission reduction goals, it is necessary to further consider how to achieve emission reduction at the lowest cost. Based on the accurate carbon emission performance evaluation, the carbon abatement cost among different representative airlines have been systematically compared. The main work and findings of this study can be summarized in the following three aspects. Firstly, a new nonparametric shadow price measurement method was constructed based on the Slacks-Based Measurement Data Envelopment Analysis (SBM-DEA). This can better reflect the essence of efficiency evaluation and the calculated shadow price results are more consistent with the real market. Secondly, the average value of carbon emission efficiency has experienced a fluctuating downward trend from 2011 to 2017, indicating that the carbon emission efficiency of global airlines has decreased. Thirdly, the average value of the shadow price is generally between 313.4 and 398.4 dollars/ton, showing an “up-down-up” trend, and reaching a peak of 398.4 dollars/ton in 2014. This can provide a basis for low-carbon policy makers in the civil aviation sector, and also provide reference for different types of airlines to achieve low-cost emission reduction.

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.

Spatial Network and Driving Factors of Agricultural Green Total Factor Productivity in China

Agricultural green total factor productivity (AGTFP) is an important indicator to reflect the sustainability level of agriculture. The AGTFP network reflects the spatial correlations of the AGTFP among regions; thus, exploring its network structure and influencing factors can provide targeted policy guidance to the coordinated development of the agriculture sector. This study builds an epsilon-based measurement data envelopment analysis (EBM-DEA) model to calculate 31 provincial AGTFPs in China from 2002 to 2020. Then, social network analysis (SNA) was utilized to explore the characteristics of the AGTFP network, and the quadratic assignment procedure (QAP) was applied to find its external influencing factors. We reached four central conclusions: (1) Overall, there was a gradual upward trend of AGTFP in China during 2002~2020, and the average value rose from 0.75 in 2002 to 0.90 in 2020, but there were some differences among regions. (2) There is a complex and stable network characteristic of AGTFP; the average network density is 0.3753, and the average network efficiency is 0.4714. Meanwhile, some eastern and central areas, such as Henan, Anhui, Hubei, Hebei, Jiangsu, etc., have relatively high centrality and are a bridge in the entire network. (3) The AGTFP network can be divided into eight blocks, including two net beneficial blocks (the central-eastern provinces with high centrality); two net spillover blocks, including the provinces located in the developed urban areas (Beijing, Tianjin, Shanghai, and Jilin), the underdeveloped northwest regions (Ningxia, Qinghai, Xinjiang, and Tibet). The other areas are two-way spillover blocks. (4) Transportation development gap, technological progress gap, and the similarities of the agricultural industry structure are critical factors influencing the AGTFP network. Hence, improving the efficiency of the logistics and transportation industry, promoting technology transfer from developed areas to underdeveloped areas, and developing characteristic agriculture are all conducive to promoting the whole region’s AGTFP. Our research provides policy implications for sustainable agricultural development in China and other developing countries.

Rajiv Banker: Management Accounting Virtuoso

ABSTRACT This article documents and celebrates the immense contributions of Professor Rajiv Banker (1953–2023) to management accounting. After a brief history of his career, we document his prolific output and impact. We organize our overview of his contributions to management accounting into four broad streams, as follows: cost drivers and systems, managerial drivers of cost behavior, performance measurement and compensation, and data envelopment analysis for productivity measurement in organizations. JEL Classifications: M10; M40.

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 Effect of Regulations on Port Efficiency: An Empirical Study using Regulatory Quality and Control of Corruption Index

A key determinant influencing port performance is the governance aspect. Since the port plays a crucial role in logistics supply chain systems, its performance determinants should be evaluated. Data from 57 ports worldwide was analyzed to investigate how regulations affected their efficiency. First, we utilized the Data Envelopment Analysis (DEA) to obtain the measurement of the port's technical efficiency. Then, the econometric estimation is used to examine the role of regulation on port’s technical efficiency. The findings from the econometric estimation suggests that Regulatory Quality (REGQ) and Control of Corruption (CORR) were positively correlated with the port’s technical efficiency One important contribution of the study is the implementation of DEA-L in the DEA measurement as to include the external variables in the analysis. This study suggests the government should improve the process by enhancing the application of high-technology items and digitization that are able to ease the bottleneck at port.

Technological drivers of dry port efficiency in Brazil

PurposeThis paper aims to identify the scale efficiency of dry ports in Brazil and its main technological drivers.Design/methodology/approachThis paper uses the Data Envelopment Analysis (DEA) model in two stages. The first stage of the DEA was used to measure the efficiency of the dry ports. In the second stage, the Bootstrap Truncated Regression (BTR) was applied to explore the relationship between efficiency and the factors analyzed. The inputs, outputs and contextual variables for this analysis were extracted from the secondary database provided by Revista Tecnologística.FindingsIn the first analysis stage, a high level of idleness was verified in the operations. The contextual variables in the second stage were significant: Certification, Warehouse Management System (WMS), barcode and Radio Frequency Identification (RFID). Results corroborate the positive impact of Information Technology (IT) coordination processes on logistics performance.Practical implicationsResults show that dry ports operate below their technical and operational capacity and that the sector's lack of regulation in Brazil can facilitate and encourage the use of ports and marine terminals by importers and exporters.Originality/valueApplication of two-stage DEA measures efficiency as a sectoral benchmarking tool.

A study of primary health care service efficiency and its spatial correlation in China

BackgroundChina’s primary health care system has undergone major changes since the new round of medical reform in 2009, but the current status of primary health care institution service efficiency is still unsatisfactory. The purpose of this study is to compare and evaluate the China’s primary health care institution service efficiency and provide a reference for improving the efficiency and promoting the development of primary health care institution.MethodsBased on panel data of 31 provinces (municipalities directly under the central government and autonomous regions) in mainland China from 2011 to 2020, using the super efficiency slack-based measure-data envelopment analysis model, to analyze the data from a static perspective, and the changes in the efficiency of primary health care services were analyzed from a dynamic perspective by using the Malmquist index method. Spatial autocorrelation analysis method was used to verify the spatial correlation of primary health care service efficiency among various regions.ResultsThe number of Primary health care institutions increased from 918,000 in 2011 to 970,000 in 2020. The average primary health care institution service efficiency in the northeastern region including Jilin (0.324), Heilongjiang (0.460), Liaoning (0.453) and northern regions such as Shaanxi (0.344) and Neimenggu (0.403) was at a low level, while the eastern coastal regions such as Guangdong (1.116), Zhejiang (1.211), Shanghai (1.402) have higher average service efficiency levels. The global Moran’s I showed the existence of spatial autocorrelation, and the local Moran’s I index suggested that the problem of uneven regional development was prominent, showing a contiguous regional distribution pattern. Among them, H–H (high-efficiency regions) were mainly concentrated in Jiangsu, Anhui and Shanghai, and L-L regions (low-efficiency regions) were mostly in northern and northeastern China.ConclusionThe service efficiency of primary health care institution in China showed a rising trend in general, but the overall average efficiency was still at a low level, and there were significant geographical differences, which showed a spatial distribution of “high in the east and low in the west, high in the south and low in the north”. The northwestern region, after receiving relevant support, has seen a rapid development of primary health care, and its efficiency was steadily improving and gradually reaching a high level. The average primary health care institution service efficiency in the northeastern region including the northern region of China was at a low level, while the average efficiency in the eastern coastal region and some economically developed regions was high, which also verifies the dependence and high symbiosis of primary health care institution service efficiency on regional economy.