Spatial effects of township health centers' health resource allocation efficiency in China.

Introduction: China is a large agricultural nation with the majority of the population residing in rural areas. The allocation of health resources in rural areas significantly affects the basic rights to life and health for rural residents. Despite the progress made by the Chinese government in improving rural healthcare, there is still room for improvement. This study aims to assess the spatial spillover effects of rural health resource allocation efficiency in China, particularly focusing on township health centers (THCs), and examine the factors influencing this efficiency to provide recommendations to optimize the allocation of health resources in rural China. Methods: This study analyzed health resource allocation efficiency in Chinese rural areas from 2012 to 2021 by using the super-efficiency SBM model and the global Malmquist model. Additionally, the spatial auto-correlation of THC health resource allocation efficiency was verified through Moran test, and three spatial econometric models were constructed to further analyze the factors influencing efficiency. Results: The key findings are: firstly, the average efficiency of health resource allocation in THCs was 0.676, suggesting a generally inefficient allocation of health resources over the decade. Secondly, the average Malmquist productivity index of THCs was 0.968, indicating a downward trend in efficiency with both non-scale and non-technical efficient features. Thirdly, Moran's Index analysis revealed that efficiency has a significant spatial auto-correlation and most provinces' values are located in the spatial agglomeration quadrant. Fourthly, the SDM model identified several factors that impact THC health resource allocation efficiency to varying degrees, including the efficiency of total health resource allocation, population density, PGDP, urban unemployment rate, per capita disposable income, per capita healthcare expenditure ratio, public health budget, and passenger traffic volume. Discussion: To enhance the efficiency of THC healthcare resource allocation in China, the government should not only manage the investment of health resources to align with the actual demand for health services but also make use of the spatial spillover effect of efficiency. This involves focusing on factors such as total healthcare resource allocation efficiency, population density, etc. to effectively enhance the efficiency of health resource allocation and ensure the health of rural residents.

Innovation Efficiency, Productive Performance and Undesirable Outputs across European Regions: Are there any missing links?

We introduce an analytical methodological framework that links knowledge generation efficiency with economic efficiency and the corresponding environmental impact for 199 European Regions during 2000-2018, using a benchmarking approach and especially a chain network DEA technique. A clear trade-off between knowledge generation efficiency and productive performance emerges. European regions which exhibit high innovation efficiency enjoy higher overall performance compared to their counterparts. In a second stage, we investigate the convergence patterns of the examined regions with respect to all the three facets of the estimated efficiency where the coexistence of multi-type convergence clubs is revealed.

Nitric oxide is involved in the cardioprotection of neonatal rat hearts, but not in neonatal ischemic postconditioning.

The cardioprotective effect of ischemic preconditioning (IPC) and ischemic postconditioning (IPoC) in adult hearts is mediated by nitric oxide (NO). During the early developmental period, rat hearts exhibit higher resistance to ischemia-reperfusion (I/R) injury, contain higher levels of serum nitrates, and their resistance cannot be further increased by IPC or IPoC. NOS blocker (L-NAME) lowers their high resistance. Wistar rat hearts (postnatal Days 1 and 10) were perfused according to Langendorff and exposed to 40 min of global ischemia followed by reperfusion with or without IPoC. NO and reactive oxygen species donors (DEA-NONO, SIN-1) and L-NAME were administered. Tolerance to ischemia decreased between Days 1 and 10. DEA-NONO (low concentrations) significantly increased tolerance to I/R injury on both Days 1 and 10. SIN-1 increased tolerance to I/R injury on Day 10, but not on Day 1. L-NAME significantly reduced resistance to I/R injury on Day 1, but actually increased resistance to I/R injury on Day 10. Cardioprotection by IPoC on Day 10 was not affected by either NO donors or L-NAME. It can be concluded that resistance of the neonatal heart to I/R injury is NO dependent, but unlike in adult hearts, cardioprotective interventions, such as IPoC, are most likely NO independent.

Green transformation and performance synergy efficiency of china's thermal power enterprises on the basis of the environmental tax burden.

Global climate change and the collection of environmental protection taxes are accelerating the green transformation of thermal power enterprises. This study selected Chinese thermal power listed companies as samples and used a dynamic three-stage (operational, green transformation, and market performance) network DEA model to evaluate their transformation efficiency and corporate performance. This paper incorporates targeted indicators such as ESG (environment, society, governance) and stock prices into the model and conducts a comparative study on the basis of macro policies and the geographical location of the enterprise. A comparative analysis was conducted on the efficiency of enterprises before and after the adjustment of the environmental tax burden, using the environmental tax burden as an exogenous variable. Thus, the following conclusions can be drawn: there is a certain positive correlation between the collaborative efficiency of the two links of thermal power enterprises and the economic development of their respective regions. Moreover, the green transformation efficiency of most thermal power enterprises is superior to the market performance efficiency. The environmental tax burden mainly improves the overall efficiency of thermal power enterprises by improving their operational efficiency and efficiency in the green transformation stage without affecting market performance. To further improve efficiency, thermal power enterprises should actively communicate with stakeholders to strive for more financial relief.

Regional coordinated development of low-carbon sports industry in China.

This study develops a systematic modeling framework, comprising a prediction model, a super-SBM model, and a spatial autocorrelation analysis model, to explore the spatial-temporal evolution tendencies of development efficiency within China's 30 regions in the low-carbon sports industry from 2006 to 2025. This framework aims to provide theoretical insights for the formulation of more targeted policies. Based on the empirical findings, the main conclusions of this study are as follows: (1) The optimal buffer operator grey prediction model demonstrates the highest accuracy among the prediction models examined. (2) The development efficiency curves of the 30 regions exhibit a significant increasing trend from 2006 to 2021, with values generally peaking between 0.4 and 0.6. (3) Notably, the disparity in development efficiency between developed and less developed regions is expected to progressively widen. (4) The development efficiency of the low-carbon sports industry across the 30 regions typically displays high-high clustering and low-low clustering during China's four five-year plan periods. This underscores the importance and urgency of promoting regional coordinated development within the low-carbon sports industry.

What explains the operational efficiency of listed commercial banks in China? Evidence from a three-stage DEA-tobit modeling analysis.

Based on the actual situation of listed commercial banks in China, this study utilizes a three-stage DEA model to eliminate external macro-environmental factors and random error factors. As a result, the study objectively measures the true efficiency values of 42 listed commercial banks in China from 2015 to 2021. On this basis, a Tobit model is constructed to analyze the micro-level factors influencing the operational efficiency of listed commercial banks in China. Empirical research shows that the operational efficiency values in the first stage are significantly lower than those in the third stage. Analyzing the proportion of banks with an efficiency value of 1, it is found that state-owned banks and joint-stock banks account for a large proportion. The proportion of city commercial banks decreases significantly, while agricultural banks and commercial banks have the lowest proportion. In addition, the Tobit regression results show that bank size, innovation level, profitability, and development capacity have a significant positive impact on the operational efficiency of listed commercial banks in China at the current stage. Based on the above empirical results and analysis, specific measures are proposed to improve the operational efficiency of listed commercial banks in China. Based on the above empirical results and analysis, the study finally suggests the following specific measures to enhance the operational efficiency of listed commercial banks in China: 1. Strengthening technological investment to achieve diversified operations and cultivate new niche markets; 2. Emphasizing intermediate business income to enhance market competitiveness; 3. Undertaking digital transformation and upgrading to improve sustainable profitability.

Performance of power generation: A dynamic productivity and efficiency analysis.

This study evaluates the performance dynamics of Oman's principal part of electricity generation. Emphasis is placed on capturing the influence of the COVID-19 pandemic on the industry's performance indicators. We utilised the Malmquist Index method to analyse the changes in overall performance indicators over time. This approach allows us to distinguish between efficiency and technology changes. In addition, we employed the analysis of variance approach to test hypotheses related to COVID-19. Data is collected from twelve electricity producers across Oman's power sector. These consist of companies listed on the Stock Exchange Market in Oman, accounting for about 60 % of the total electricity production in the Sultanate. The predominant findings indicate that COVID-19 detrimentally impacted the sector's aggregate performance in 2020 but had a swift recovery in 2021. The analysis of the sample firm's productivity indices verifies that the decline in productivity in 2020 due to the Pandemic is attributable to a decrease in average efficiency indices and a negative shift in the projected frontier. These are probable consequences of the recessionary effects caused by the Pandemic. Despite a considerable decrease in average efficiency scores, a positive change in the frontier has facilitated a rapid recovery in 2021. This recovery can be attributed to the implementation of advanced technical upgrades in particular enterprises, which began as early as 2018/2019, well before the onset of the Pandemic.

Performance evaluation of facility locations using integrated DEA-based techniques.

Facility location, particularly in the context of international investments by global enterprises, stands out as a paramount concern within the purview of top management's strategic decision-making process. The selection of a suitable location plays a pivotal role in determining the ultimate achievement of organizational objectives. The process of selecting an appropriate location requires the comprehensive analysis of a substantial volume of data, encompassing diverse tangible and intangible evaluation criteria that may exhibit inherent conflicts. This paper addresses the challenge of determining the best location for a manufacturing facility by employing alternative performance measures within the framework of the data envelopment analysis (DEA) model. In a performance evaluation process, not only positive but also negative aspects should be determined. This paper, therefore, proposes a double-frontier DEA-AR model, which is an integrated approach that incorporates the efficient frontier, anti-efficient frontier, and assurance region weight restrictions, with the aim of increasing the discrimination ability of the DEA method. An efficient frontier evaluates the information of each location from a positive viewpoint, while the worst side is evaluated by an anti-efficient frontier. The technique of weight restrictions, which allows incorporating expert opinion into the assessment, is also applied with both frontiers to restrict the regions of weights to some specific area. The prescribed approach is illustrated by a numerical example of selecting the best location among ten different countries under consideration of 22 selection criteria obtained from PEST analysis. The results show that the proposed alternative performance measures significantly improve discrimination capability, enabling the ranking of candidates based on their suitability for the optimal location.

Measurement and evaluation of agricultural technological innovation efficiency in the Yellow River Basin of China under water resource constraints.

Improving the efficiency of agricultural technology innovation is an inevitable requirement for ecological protection and sustainable agricultural development in the Yellow River Basin. Under the background of prominent water resources constraints in the Yellow River Basin, the actual level and regional differences of agricultural technology innovation efficiency in the basin are analyzed, which will provide theoretical basis and data reference for the development plan of agricultural modernization in the Yellow River Basin. The construction of evaluation index system and the choice of method are the main factors that affect the measurement results. Therefore, this paper first selects input indicators such as water-saving technology level and output indicators such as total agricultural output value to construct an innovative evaluation index system of agricultural technology innovation efficiency in the Yellow River Basin under the consideration of water resources constraints. Secondly, the three-stage DEA model was used to eliminate the interference of external environmental variables, and the overall and regional agricultural technology innovation efficiency of the Yellow River Basin during 2011-2020 was measured with the data of prefecture-level cities under the constraint of water resources. Finally, from the perspective of the whole and the region, the spatio-temporal dynamic evolution law is analyzed and evaluated. The results show that: on the whole, the agricultural technology innovation efficiency in the Yellow River Basin is good and rising in a wave trend, the adjusted pure technology efficiency increases, while the scale efficiency decreases. From the regional perspective, although there is regional heterogeneity, the overall development trend is good, and the lower Yellow River has the highest efficiency, followed by the upper reaches and the middle reaches. From the perspective of the change law, the spatio-temporal evolution distribution shows a multi-polarization trend, and the different regions in the upper, middle and lower reaches show great differences. Therefore, promoting the innovation of water-saving technology and the integration of agricultural science and technology, promoting the integration of production, study and research, and strengthening the regional linkage mechanism are helpful to improve the competitiveness of agricultural science and technology and achieve sustainable agricultural development in the Yellow River Basin.

The Regional Total Factor Productivity Changes of Healthcare Delivery in China: A Bootstrap Malmquist Data Envelopment Analysis.

Improving the productivity of healthcare delivery and optimizing the allocation of regional healthcare resources are crucial for the health providers. The objective of this study is to evaluate the productivity dynamics of healthcare delivery at the regional (provincial) level in China, to provide evidence-based policy implications. After a review of literature, actual number of open beds, number of occupational or assistant doctors, number of registered nurses, and number of other staff were selected as input variables. The number of diagnostic visits and number of discharged inpatients were adopted as the output indicators. The panel data of 31 provinces in mainland China from 2010 to 2019 were extracted from Health Statistics Yearbook. Bootstrap-Malmquist Data Envelopment Analysis (DEA) model was used to measure the total factor productivity changes (TFPC) and its components. During the study period, the analysis of total factor productivity (TFP) in China revealed a declining trend with an average annual decline of 0.9% (ranging from 0.860 to 1.204). For each of the 31 provinces, the annual TFP scores varied from 0.971 to 1.029. On average, technical efficiency changes (TEC) had showed a downward trend from 2010-2011 (0.980) to 2013-2014 (0.982), and then an upward trend in 2014-2015 (1.029) and the following three consecutive years since 2016-2017 (1.000, 1.013, 1.009). Similarly, the trend in technological changes (TC) was consistent with the TEC from 2010-2019, which fluctuated between 0.969 and 1.011 on average per year at the provincial level. Notably, the point of inflection appeared at 2013-2014. Regional healthcare inputs and outputs in mainland China saw an upward trend from 2010 to 2019. However, TFPC, TEC, and TC decreased across all 31 provinces. TFP experienced a declining trend from 2010 to 2014, followed by growth until 2019. This may be related to the new healthcare reform being implemented since 2009, as service efficiency and capacity may undergo a reversal at the beginning of the reform.

How to play the role of fiscal subsidies? Based on the research of photovoltaic industry in China--Based on SBM-DEA and FGLS methods.

Fiscal compensation may play either an incentive or a crowding-out role in the different enterprises of the PV industry. First, a model for evaluating the efficiency of fiscal compensation was designed. Then, an empirical analysis of the influencing factors using a panel data model was made. Results showed that fiscal compensation had an incentive effect on 73.3 % of enterprises, but it had a crowding-out effect on the remaining enterprises. The average efficiency of fiscal compensation for enterprises in the PV industry is 1.117. The average efficiency of fiscal compensation for the front-end and back-end enterprises was 1.002 and 1.231, respectively. The impact of fiscal compensation on China's photovoltaic industry has shown a downward trend over time, and the role has also changed from an incentive effect to a crowding-out effect. The size of the enterprise and the intensity of fiscal compensation will affect the efficiency of fiscal compensation. There is an inverted U-shaped relationship between the intensity of fiscal compensation in China's photovoltaic industry and the efficiency of fiscal compensation. The larger the enterprise, the more efficient the fiscal compensation will be.

Evaluating China's primary healthcare services' efficiency and spatial correlation: a three-stage DEA-Malmquist model.

Introduction: Enhancing the efficiency of primary healthcare services is essential for a populous and developing nation like China. This study offers a systematic analysis of the efficiency and spatial distribution of primary healthcare services in China. It elucidates the fundamental landscape and regional variances in efficiency, thereby furnishing a scientific foundation for enhancing service efficiency and fostering coordinated regional development. Methods: Employs a three-stage DEA-Malmquist model to assess the efficiency of primary healthcare services across 31 provincial units in mainland China from 2012 to 2020. Additionally, it examines the spatial correlation of efficiency distribution using the Moran Index. Results: The efficiency of primary healthcare services in China is generally suboptimal with a noticeable declining trend, highlighting significant potential for improvement in both pure technical efficiency and scale efficiency. There is a pronounced efficiency gap among provinces, yet a positive spatial correlation is evident. Regionally, efficiency ranks in the order of East > Central > West. Factors such as GDP per capita and population density positively influence efficiency enhancements, while urbanization levels and government health expenditures appear to have a detrimental impact. Discussion: The application of the three-stage DEA-Malmquist model and the Moran Index not only expands the methodological framework for researching primary healthcare service efficiency but also provides scientifically valuable insights for enhancing the efficiency of primary healthcare services in China and other developing nations.

Research on financing and technological innovation efficiency of China's energy-saving and environmental protection enterprises.

Green, low-carbon circular economy and the development model of energy-saving and environmental protection are emerging worldwide, and the world's economies have taken the energy-saving and environmental protection industry as a strategic emerging industry to cultivate and develop. Coordinating finance and technological innovation is crucial to promoting the healthy development of Energy-Saving and Environmental Protection Enterprises (ESEPEs). According to industry classification, this paper divides 121 ESEPEs into 12 categories as research objects. Firstly, the DEA-SBM model is used to calculate financing efficiency (FE) and technological innovation efficiency (TIE). Subsequently, the changes in the two efficiencies are analyzed from the perspectives of time series, industry, and annual mean value, and the changes of the two efficiencies are analyzed from the perspectives of time series, industry, and annual average values. Secondly, through the coupling coordination degree (CCD) model, the development status of the coupling coordination between the two efficiencies is innovated expounded. Finally, the Tobit regression model is used to discuss the factors influencing CCD from the whole and industry perspectives. The results show that: (1) TIE is generally lower than FE, and FE shows a downward trend while TIE shows an upward trend. (2) CCD between the two efficiencies is Near dysfunction, and TIE restricts the development of CCD between the two efficiencies to a certain extent. (3) R&D intensity, enterprise size, and government subsidy intensity have a significant positive impact on CCD between FE and TIE of ESEPEs, while the impact of other factors is not significant.

Valuating the efficiency of social security and healthcare in OECD countries from a sustainable development.

Under the goal of sustainable development, coping with the increase in social security and healthcare expenses caused by population aging is becoming increasingly important, but it is rare in the literature to evaluate the impact of social security efficiency on healthcare efficiency. This research uses the dynamic SBM two-stage model to observe the efficiencies of social security and healthcare in OECD countries. There are two findings as follows. First, the higher social security efficiency is, the better is the healthcare efficiency of countries with lower per capita GDP. Second, higher social security efficiency of National Health Service (NHS) countries denote better healthcare efficiency. When the financial source of the social security system is taxation, then it is more likely to bring higher efficiency to healthcare.

Optimizing Epoxy Molding Compound Processing: A Multi-Sensor Approach to Enhance Material Characterization and Process Reliability.

The in-line control of curing during the molding process significantly improves product quality and ensures the reliability of packaging materials with the required thermo-mechanical and adhesion properties. The choice of the morphological and thermo-mechanical properties of the molded material, and the accuracy of their determination through carefully selected thermo-analytical methods, play a crucial role in the qualitative prediction of trends in packaging product properties as process parameters are varied. This work aimed to verify the quality of the models and their validation using a highly filled molding resin with an identical chemical composition but 10 wt% difference in silica particles (SPs). Morphological and mechanical material properties were determined by dielectric analysis (DEA), differential scanning calorimetry (DSC), warpage analysis and dynamic mechanical analysis (DMA). The effects of temperature and injection speed on the morphological properties were analyzed through the design of experiments (DoE) and illustrated by response surface plots. A comprehensive approach to monitor the evolution of ionic viscosity (IV), residual enthalpy (dHrest), glass transition temperature (Tg), and storage modulus (E) as a function of the transfer-mold process parameters and post-mold-cure (PMC) conditions of the material was established. The reliability of Tg estimation was tested using two methods: warpage analysis and DMA. The noticeable deterioration in the quality of the analytical signal for highly filled materials at high cure rates is discussed. Controlling the temperature by increasing the injection speed leads to the formation of a polymer network with a lower Tg and an increased storage modulus, indicating a lower density and a more heterogeneous structure due to the high heating rate and shear heating effect.

Evaluation of healthcare efficiency in China: a three-stage data envelopment analysis of directional slacks-based measure.

Background: A consensus on the changing pattern of healthcare efficiency in China is current absent. This study tried to identify temporal fluctuations in healthcare efficiency from 2012 to 2021, and conducted a comparative analysis on the performance of 31 regions in China using region-level balanced panel data. Methods: Employing three-stage data envelopment analysis (DEA) as the analytical framework, we measured healthcare efficiency and its changes using the directional slacks-based measure and global Malmquist-luenberger (GML) indexes. We also decomposed the sources of healthcare inefficiency and extended our analysis to changes in healthcare efficiency across different primary medical service levels and regional economic development tiers. Results: The average efficiency score of medical institutions (0.956) was slightly higher than that of hospitals (0.930). We found that the average GML indexes of medical institutions in China stood at 0.990, while the average technical change (TC) index was 0.995 and the average efficiency change (EC) index was 0.998 from 2012 to 2021. The GML indexes, TC indexes, and EC indexes of hospitals were 1.002, 1.009, and 0.994, respectively. The healthcare inefficiency for both inputs and desirable outputs in medical institutions was primarily attributed to the redundant numbers of institutions, outpatient visits slacks and inpatient surgery volume slacks, accounting for 50.040, 49.644, and 28.877%, respectively. The undesirable output inefficiency values of medical institutions concerning in-hospital mortality stood at 0.012, while the figure for hospital regarding the average length of stay (LOS) was 0.002. Additionally, healthcare efficiency in both medical institutions and hospitals exhibited an upward trend from 2012 to 2021, corresponding to an increase in the volume of primary medical services, primary medical staff, and the total gross domestic product (GDP). Conclusion: Total factor productivity (TFP) of medical services declined in China from 2012 to 2021. The excessive number of medical institutions and the slack of medical service volumes were the main sources of healthcare inefficiency. Regions prioritizing primary medical services and boasting higher GDP levels exhibited superior healthcare efficiency. These findings are expected to inform policymakers' efforts in building a value-based and efficient health service system in China.

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.

Efficiency measurement and inefficiency analysis of low-carbon logistics in the Beijing-Tianjin-Hebei region, China.

Under the dual-carbon goals, enhancing the green development level of logistics industry and realizing its low-carbon transformation are important issues that need to be solved urgently. Amidst the continuous escalation in the total energy consumption of the national logistics industry, the Beijing-Tianjin-Hebei (BTH) region has exhibited a favorable descending trajectory in this respect. It is necessary to investigate the underlying reasons. Based on the panel data from 2012 to 2021, the DEA and Malmquist index are employed to analyze the low-carbon logistics efficiency of the BTH region from both static and dynamic perspectives. Furthermore, the inefficiency analysis is conducted to identify the deficiencies of low-carbon logistics industry in this region. Results show that (1) from the static perspective, the development of low-carbon logistics industry in the BTH region is relatively unbalanced. Compared to Tianjin and Hebei, Beijing's low-carbon logistics efficiency is significantly lower, becoming the focal area for attention; (2) from the dynamic perspective, technological progress is the main reason for the fluctuation of total factor productivity in the BTH region and a constraining factor for further improvements; (3) from the results of inefficiency analysis, the forthcoming emphasis on low-carbon logistics in Beijing should be on optimizing the number of logistics practitioners, transportation efficiency, and energy efficiency. Economic output and energy efficiency are relatively vulnerable aspects in Tianjin and Hebei, respectively, warranting due consideration. The research results of this paper have important practical implications for better developing low-carbon logistics in the BTH region and leveraging its leading role nationwide.

A novel synthesized Vanillin-Based Deep Eutectic Agent (V-DEA) mitigates postharvest fungal decay and improve shelf life and quality of cherry tomatoes.

Fusarium oxysporum and Botrytis cinerea are the main pathogens that cause fruit decay and reduce the postharvest shelf life of cherry tomatoes. Boosting the potency of natural products requires implementing structural modification to combat postharvest pathogens. Herein, we developed a novel Vanillin-Deep Eutectic Agent (V-DEA) from natural compounds and evaluated its effectiveness against tomato fruit rot pathogens. The results demonstrated that V-DEA suppressed mycelium growth and spore germination of F. oxysporum and B. cinerea by enhancing cell membrane permeability, increasing lipid peroxidation, and inhibiting enzyme activities. Importantly, using 8-mM V-DEA successfully prevented postharvest decay in cherry tomatoes, while 4-mM significantly extended their shelf life by reducing weight loss and shriveling, and enhancing key fruit qualities such as total soluble solids, ascorbic acid, tartaric acid, and lycopene. In conclusion, V-DEA exhibits dual properties as a potent pathogen inhibitor and antioxidant activity, thus prolonging the shelf life of cherry tomatoes.

Measuring Technical Efficiency and Productivity of Secondary Maternal and Child Health Hospitals in Hubei, China: Some Evidences from Hubei Province of China 2019 to 2021.

Environmental factors like COVID-19 can have significant impact on technical efficiency (TE) and total factor productivity (TFP) of health services provided. In this study, focusing on Maternal and Child Health (MCH) hospitals in Hubei Province of China in 2019 to 2021, we aimed to measure their TE and TFP, identify some influential environmental factors, and propose some policy recommendations. Altogether 62 secondary MCH hospitals were selected as the study sample. Four input indicators, 3 output indicators, and 4 environmental indicators were selected to analyze the panel data from 2019 to 2021. Three-stage Data Envelopment Analysis (DEA) and Malmquist Productivity Index (MPI) model were employed to estimate the TE and TFP of these hospitals. During 2019 to 2021, the inputs of the sample hospitals had increased, while the outputs had decreased. The inputs redundancy was negatively associated with birth rate, number of residents, and GDP per capita (P < .05). It was positively associated with number of COVID-19 infections (P < .05). The adjusted TE scores in 2019 to 2021 were 0.822, 0.784, and 0.803, respectively. The TFP declined in 2020 and 2021 compared to 2019, with scores being 0.845 and 0.762. The technical efficiency change (TEC) scores from 2019 to 2021 were 0.926 and 1.063. The technological change (TC) scores from 2019 to 2021 were 0.912 and 0.716. During 2019 to 2021, the operation of sample hospitals had been significantly influenced by environmental factors like COVID-19 pandemic, low birth rate, number of residents, and GDP per capita. The inputs had increased but outputs had decreased, leading to an increase in inputs redundancy and a decline in TE. The TFP showed a downward trend, with TC and SEC being the priority directions for improvement. Some recommendations are made for both hospitals and government to continuously improve the TE and TFP.