Evaluation of Green Logistics Efficiency in Jiangxi Province Based on Three-Stage DEA from the Perspective of High-Quality Development

The high-quality development of the logistics industry plays an important role in high-quality economic development. Green logistics is attracting more attention, owing to environmental concern. Based on the five concepts of “innovation, coordination, green, openness and sharing” of high-quality economic development, the input–output indicators of green logistics efficiency (GLE) have been designed. The correlation between the green logistics input and output indicators have been analyzed by Pearson, and the green logistics efficiency of 11 cities in Jiangxi Province has been calculated by three-stage DEA. The evolutionary characteristics of the high-quality development of green logistics efficiency in Jiangxi Province were analyzed and evaluated. The conclusions were achieved as follows: (1) Nanchang, Xinyu and Ganzhou city are at the forefront of efficiency, and are less affected by environmental factors. The logistics efficiency of other cities is obviously affected by environmental factors. (2) The comprehensive technical efficiency (TE) of green logistics in Jiangxi Province is strongly influenced by scale efficiency (SE). The poor scale efficiency reduces the comprehensive technical efficiency of green logistics. (3) There is a positive correlation between high-quality economic development and logistics efficiency. In these cities of Jiangxi province (Nanchang, Ganzhou, Jiujiang, etc.) the share of total economy and green logistics efficiency is high. This study proves that Jiangxi province is moving towards high-quality economic development due to good environmental protection. (4) In 2017, Jiangxi Province was recognized as one of the national ecological civilization pilot region by the State Council. Green logistics efficiency in Jiangxi Province showed an inflection point in 2017, indicating that the green concept is becoming more and more popular. From the government to enterprises, the province has achieved initial results in promoting the transformation of the economic development mode. It aims to provide reference for the high-quality development of other provinces.

Genicular artery embolization as a novel treatment for mild to moderate knee osteoarthritis: protocol design of a randomized sham-controlled clinical trial

Introduction Knee osteoarthritis is a common disease with pain as the most prevalent symptom. Previous cohort studies have shown genicular artery embolization to reduce pain symptoms in patients with mild to moderate knee osteoarthritis. Patients resistant to conservative therapy but not eligible yet for surgical treatment due to young age or comorbidities may profit from an effective and sustained pain reduction treatment. This study is a randomized sham-controlled trial to evaluate the efficacy of genicular artery embolization in patients with knee osteoarthritis. Methods and analysis Fifty-eight patients with mild-to-moderate knee osteoarthritis will be recruited and randomly allocated to the treatment or control group in a 1:1 ratio. Participants in the treatment group will undergo genicular artery embolization. Patients in the control group will undergo sham treatment. Outcome measurements will be assessed at baseline and after 1, 4, 8, and 12 months with questionnaires, pressure pain threshold testing, and MR imaging. The MR imaging protocol is designed to (semi)quantitatively assess osteoarthritis in the knee joint. The primary outcome is the change from baseline of the Knee injury and Osteoarthritis Outcome Score (KOOS) pain subscale after 4 months. Secondary outcomes include change in osteoarthritis-related questionnaires, pressure pain threshold, and OA-related MRI features, particularly synovitis and bone marrow lesions. Ethics and dissemination This trial will determine the efficacy of genicular artery embolization compared to a sham treatment. This is of importance to assess before proceeding to larger-scale efficiency studies and, ultimately, implementing this treatment into day to day clinical practice. Trial registration ClinicalTrials.gov NCT03884049. Registered on 21 March 2019

Spatial Distribution and Regional Difference of Environmental Efficiency Based on Carbon Reduction Goals: Evidence From China

China will strive to achieve carbon peak by 2030 and carbon neutralization by 2060 cooperating with the system dominated by carbon intensity control and supplemented by total carbon emission control. This paper analyzes the environmental efficiency index of China; the empirical results show that the average growth rate is 4.5% from 2006 to 2017. A further decomposition of changes on scale efficiency and pure technical efficiency indicates that the pure technical efficiency maintains a long-term growth, and scale efficiency shows a fluctuant tendency. The abovementioned changes show that various methods in China such as industrial structure adjustment and promotion of the development of high and new technologies have obtained a certain effect. From the perspectives of regional differences, the average changes of environmental efficiency in eastern, central, and western regions as well as most of provinces and cities are all on the increase. On the space layout, a trend has been presented that the average changes in central regions exceed those in eastern regions, while the average changes in western regions are comparatively lower than those in eastern regions.

Evaluating the Operational Efficiency and Quality of Tertiary Hospitals in Taiwan: The Application of the EBITDA Indicator to the DEA Method and TOBIT Regression

This study estimates the efficiency of 19 tertiary hospitals in Taiwan using a two-stage analysis of Data Envelopment Analysis (DEA) and TOBIT regression. It is a retrospective panel-data study and includes all the tertiary hospitals in Taiwan. The data were sourced from open information hospitals legally required to disclose to the National Health Insurance (NHI) Administration, Ministry of Health and Welfare. The variables, including five inputs (total hospital beds, total physicians, gross equipment, fixed assets net value, the rate of emergency transfer in-patient stay over 48 h) and six outputs (surplus or deficit of appropriation, length of stay, the total relative value units [RVUs] for outpatient services, total RVUs for inpatient services, self-pay income, modified EBITDA) were adopted into the Charnes, Cooper and Rhodes (CCR) and Banker, Charnes and Cooper (BCC) model. In the CCR model, the technical efficiency (TE) from 2015–2018 increases annually, and the average efficiency of all tertiary hospitals is 96.0%. In the BCC model, the highest pure technical efficiency (PTE) was in 2018 and the average efficiency of all medical centers is 99.1%. The average scale efficiency of all medical centers was 96.8% in the BBC model, meaning investment can be reduced by 3.2% and the current production level can be maintained with a fixed return to scale. Correlation coefficient analysis shows that all variables are correlated positively; the highest was the number of beds and the number of days in hospital (r = 0.988). The results show that TE in the CCR model was similar to PTE in the BCC model in four years. The difference analysis shows that more hospitals must improve regarding surplus or deficit of appropriation, modified EBITDA, and self-pay income. TOBIT regression reveals that the higher the bed-occupancy rate and turnover rate of fixed assets, the higher the TE; and the higher number of hospital beds per 100,000 people and turnover rate of fixed assets, the higher the PTE. DEA and TOBIT regression are used to analyze the other factors that affect medical center efficiency, and different categories of hospitals are chosen to assess whether different years or different types of medical centers affect operational performance. This study provides reference values for the improvable directions of relevant large hospitals’ inefficiency decision-making units through reference group analysis and slack variable analysis.

SMEs’ financial risks in supply chain trade with large companies: The case of Italian automotive component industry

Becoming a supplier of large companies is traditionally considered to be positive for small and medium enterprises’ (SMEs) competitiveness. Small businesses can take several advantages by joining supply chain trade with large companies such as scale efficiency and productivity as well as technological and managerial abilities, product and process innovation, market positioning, and reputation. However, not everything is convenient per se. The subcontracting by large companies might provide some financial criticalities that need to be faced and properly managed by SMEs to exploit supply chain benefits without affecting financial stability and losing competitiveness. In this direction, the literature on supply chain finance has recently focused on financial issues related to working capital optimization in terms of accounts payable, receivable, and inventories. Adopting this perspective, the study contributes to a better understanding of SMEs’ financial constraints in supply chains driven by large companies by investigating a sample of small Italian firms, which operate in the metal casting industry and by comparing firms joining and not joining the automotive supply chain.

Technical and Scale Efficiency of the Brazilian Municipalities’ Water and Sanitation Services: A Two-Stage Data Envelopment Analysis

Seeking to “ensure availability and sustainable management of water and sanitation for all” is an admirable Sustainable Development Goal and an honourable commitment of the United Nations and its Member States regarding the human right to safe drinking water and sanitation services (WSSs). However, the majority of countries are not on target to achieve this by 2030, with several of them moving away from the best practices. Brazil is one of these cases, given, for example, the existing asymmetries in the access to water supply and sanitation service networks. For this reason, we propose a benchmarking exercise using a two-stage Data Envelopment Analysis to measure the technical and scale efficiency of the Brazilian municipalities’ WSSs, noting their contextual environment. Our results point towards low mean efficiency scores, motivated by the existence of significant scale inefficiencies (the vast majority of municipalities are operating at a larger than optimal scale). Furthermore, the Water source was found to be a statistically significant efficiency predictor, with statistically significant differences found in terms of Ownership and Geography. Ultimately, we suggest policy-making and regulatory possibilities based on debureaucratization, the implementation of stricter expenditure control policies, and investment in the expansion of WSSs.

Development of Fracturing Technology for Deep Shale Gas in South Sichuan, China

Under the condition of high ambient temperature and high confining pressure，the physical & mechanical properties and in-situ stress state of deep shale will change noticeably. Normally, the deep-shale formation has high horizontal stress difference (about 11∼21 MPa, 1595∼3045 psi), high fracture-closure pressure gradient (about 0.023∼0.025 MPa/m, 1.017∼1.105 psi/ft), high breakdown pressure gradient (larger than 0.03 MPa/m, 1.327 psi/ft), low mechanical brittleness (about 42%∼55%), low difference between the vertical and the horizontal stresses (about 3∼5MPa, 435∼725 psi). The complex geological characteristics of deep shale increase the difficulity of fracturing: 1) effect of brittle/ductile transition under high confining pressure; 2) non-uniform propagation of multi-cluster fractures is more prominent; 3) the migration of proppant is difficult in narrow fracture network; 4) high friction and high pumping pressure; 5) more stringent requirements for fracturing tools; 6) high requirements for fracturing scale, efficiency and economy. To address above challenges, this paper presents a comprehensive overview of latest researching and applicable techniques about deep-shale fracturing (3500<TVD<3800 m, 11482∼12467 ft), including: 1) new evaluation methods on fractured shale quality and fracability, considering vertical stress difference coefficient and effective confining stress; 2) non-uniform propagation of fractures in multi-clusters perforation; 3) reveal the transport mechanism of proppant in narrow fracture network; 4) optimization of high performance fracturing fluid systems to enlarge the ESRV in deep shale; 5) development of a new staged fracturing tool for deep-shale fracturing, including dissoluble bridge plug and toe delayed sleeve; 6) an integrated geoscience and engineering simulation to optimize the treatment parameters and to achieve the best fracturing efficiency in the deep shale strata. The hydraulic fracturing technique for deep shale gas with the depth of 3500∼4500 m (11482∼14763 ft) has formed preliminarily. The hydraulic fracturing technology for deep shale gas (TVD≥3500∼3800 m, 11482∼12467 ft) have made a breakthrough in Sichuan basin, China, and significant progress has also made in 3800-4500m TVD (12467∼14763 ft). The research results and techniques introduced in the paper have been successfully applied to more than 100 wells in the Sichuan basin. The test production of part fractured well can reach (10∼31)×104 m3 per day (0.35∼1.09×107 SCF/day), which basically realizes the economical and effective development for deep shale gas.

Measuring Technical Efficiency of Hospitals affiliated with Shahrekord University of Medical Sciences, Using a Combination Method Data Envelopment Analysis (DEA) – Principle Component Analysis (PCA)

Background: Measuring the efficiency of hospitals due to the high proportion of budget allocated to them on the one hand, and the need to ensure the best practices regarding the use of scarce resources on the other hand, is of particular importance. The purpose of this study is to evaluate the technical efficiency of the affiliated hospitals of Shahrekord University of Medical Sciences by using a combination of Principal Component Analysis and (PCA) & Data Envelopment Analysis (DEA). Methods: This was an analytical and cross-sectional study measuring the technical efficiency of all 8 hospitals affiliated to Shahrekord University of Medical Sciences. The required information was collected from the medical records unit of each hospital. For better differentiation between efficient and inefficient units, and the increase of research accuracy and further differentiation between hospitals in terms of efficiency, at first, 17 indicators were selected to assess and adjust these parameters to 3 components proportional to the number of the hospitals by using PCA and SPSS 16 software. After doing the PCA, 7 studied input variables became 7 principal components among which the first input component reflecting the 83 % of scattering data was selected as principal input component, and for being more influenced by human resource variables, it was named as a human resource index. Furthermore, among the output variables, the first 2 output components, which represented 76% of the variance of the data, were selected as the 2 principal components of the output for the study, which were mostly affected by these variables, respectively, the number of admissions and length of stay. Then, the modified input and output components were entered into the software Windeap 2.1 and the technical efficiency of hospitals and their rank were calculated by assuming constant and variable efficiency with respect to the scale. In order to evaluate the effect of using the combined method instead of the conventional method of efficiency measurement, the results of the PCA - DEA method were compared with the results of the conventional DEA method. Results: The result of DEA on the selected components showed the capacity to upgrade the Technical Efficiency (TE) of hospitals is 15 % (TE: 0.852). Moreover, out of 8 hospitals, 1 hospital was increasing return to scale, 3 decreasing returns to scale and 4 constant returns to scale. The technical efficiency of 3 hospitals was 1 (TE = 1), 2 hospitals had the technical efficiency between 0.80 to 1 (1 > TE > 0.80) and that in 3 hospitals was less than 0.80 (TE < 0.80). The scale efficiency for 50 % of hospitals and the management efficiency for 62/5 % of them were equal 1. Conclusion: The average of total technical efficiency, management efficiency and scale efficiency were calculated to be 0.999, 1 and 0.999, respectively based on the usual comprehensive analysis method; while using the combined method, the average total technical efficiency, management efficiency and scale efficiency were 0.852, 0.947 and 0.902 respectively. The results confirm that the use of PCA method, due to its important role in reducing alignments, increases research accuracy and better differentiates between hospitals in terms of efficiency.

Technical Efficiency of Universities in Telangana State through Data Envelopment Analysis (DEA) Approach

In this present research paper we analyze the universities data by CCR, BCC models through Data Envelopment Analysis (DEA) approach for the State of Telangana. To know the Performance of student’s university wise in state of Telangana. University wise Performances is presented along with technical efficiency, Pure Technical Efficiency, Scale Efficiency, CRS, VRS, Reference set and Peers. Measuring the Technical Efficiency (TE) and Pure Technical Efficiency (PTE) of the universities by CCR, BCC Model through DEA approach.

Big Data Analysis of e-Commerce Efficiency and Its Influencing Factors of Agricultural Products in China

At present, the e-commerce industry of agricultural products plays a pivotal role in promoting income growth and helping rural revitalization. This paper collected relevant data in the recent 8 years (2012 to 2019) and used the DEA model and Tobit model to analyze the correlation degree between the efficiency and various influencing factors in China. DEA analysis results show that, in recent years, three efficiencies are quite different: the comprehensive efficiency and scale efficiency show an upward trend, while the pure technical efficiency remains at a high level. Tobit model results show that the number of urban Internet users, rural Internet users, logistics practitioners, the development of national economy are negatively correlated with e-commerce efficiency; the length of traffic construction has no significant correlation; the level of agricultural mechanization has a significant positive correlation. Hence, the paper puts forward four suggestions.