scholarly journals The Impact of TBT and SPS Measures on Japanese and Korean Exports to China

2019 ◽  
Vol 11 (21) ◽  
pp. 6141 ◽  
Author(s):  
Jacob Wood ◽  
Jie Wu ◽  
Yilin Li ◽  
Jungsuk Kim
Keyword(s):  
Industrial Sector ◽  
Likelihood Method ◽  
Chinese Government ◽  
Coverage Ratio ◽  
Agricultural Exports ◽  
Dummy Variable ◽  
Frequency Index ◽  
Phytosanitary Measures ◽  
Made In China ◽  
The Impact

(1) Background: As countries with troubled histories, China, Japan, and Korea have, in recent times, attempted to overcome political and economic differences in a bid to forge strong trade relationships. However, Non-Tariff Measures (NTMs) have emerged in recent times, which has the potential to complicate matters. (2) Method: Our study analyzes the impact that two forms of NTM, technical barriers to trade (TBT) and sanitary and phytosanitary measures (SPS), have on Japanese and Korean exports to China. In order to effectively measure their impact, we utilize a modified version of the Gravity model and the Poisson Pseudo Maximum Likelihood method (PPML). Using three measures (coverage ratio, frequency index, and the dummy variable) to determine their impact, our study displayed a range of findings. (3) Results: The key results from our study showed that from a coverage ratio perspective, our research clearly demonstrates that Chinese TBT measures, reduce Japan and Korea’s manufacturing and total exports as a whole, while Chinese SPS measures encourage Korean agricultural exports. Moreover, the frequency index results and dummy variable estimations in the main also supported the coverage ratio findings with SPS measures promoting Korean agricultural goods exports. (4) Conclusions: Our research highlights the important role the TBT measures have played to shelter China’s emerging industrial sector from the rigors of highly competitive Korean and Japanese exporters. In doing so, the Chinese government is able to actively pursue some of its key sustainable development strategies such as “Made in China 2025” and “Industrial 4.0”.

scholarly journals Made In China 2025 and New Trends of Entrepreneurship Education of China: A Socio-Economic-Educational Perspective

2016 ◽  
Vol 2 (1) ◽  
pp. 10 ◽  
Author(s):  
Hongyun Wu ◽  
Spencer A. Benson
Keyword(s):  
Entrepreneurship Education ◽  
Government Policies ◽  
Chinese Government ◽  
Emerging Trends ◽  
Study Results ◽  
Educational Perspective ◽  
Made In China ◽  
Future Economic Development ◽  
The Impact ◽  
Made In

The importance of entrepreneurship for economic growth and job creation has gained wide acceptance around the world. The Chinese government is dedicated to innovation and entrepreneurship, realizing the critical importance in meeting this dual purpose lies in entrepreneurship education (EE) and its integration across the government, academic and business sectors. This paper outlines the emergence of entrepreneurship and the emerging trends in EE of China by looking at the past and present of China’s economy, education and government policies through a socio-economic-educational perspective. It focuses on Made In China 2025, an important 10-year national plan, that outlines China’s objectives in future economic development, and the future directions for China’s EE. By looking at past and emerging trends this study presents a historical and current picture of EE within China. The socio-economic-educational perspective of this study results in the following observations: the change from government programmed economy to a more open briskness driven economy, the close relationship between China’s reform in economy and education, the impact of government policies and mandates on China’s entrepreneurship education, EE in China, a new facet of China’s education reform, which has moved from education for the elite to the masses, and lastly, Made In China 2025’s call for innovation and reform in educational practices of EE in China. The application of a socio-economic-educational perspective provides for broader and deeper insights into the direction for the further development of EE in China.

The Supply-Demand Research of Cultural and Tourism Industries Policies in China with the Impact of COVID-19

2020 ◽  
Vol 11 (1) ◽  
pp. 24-24
Author(s):  
Dr. Jianfei Yang
Keyword(s):  
Tourism Industry ◽  
Chinese Government ◽  
Cultural Industries ◽  
Real Situation ◽  
The Real ◽  
The World ◽  
The Impact ◽  
Near Future ◽  
Post Period

COVID-19 has made a bad influence on economic and society including cultural and tourism industry in China，2020.The industry has received a huge loss in the first quarter of the year and the situation is getting worse in the near future. It is believed that there will be a long impact for the country even the world. In order to recover the industry, Chinese government has published series of policies to support the enterprises and clusters to reduce the bad influence of COVID-19. This paper mainly uses filed survey and documentary research to map the real situation of the industry. It tries to find the policy demand of the industries and then analyze the policies published by government to conquer COVID-19. Meanwhile it will focus on whether the supply meet the demand and give suggestions on how to promote the policy efficiency in the post period of COVID-19 in China. Keywords: Evaluation; Cultural Industries; Policy; Park; Pandemic

Examining the Impact and Influencing Channels of Emission Trading Pilot Markets in China

2020 ◽  
Vol 11 (1) ◽  
pp. 136-136
Author(s):  
Qiong Wu ◽  
Kanittha Tambunlertchai ◽  
Pongsa Pornchaiwiseskul
Keyword(s):  
Total Factor Productivity ◽  
Co2 Emission ◽  
Carbon Emission ◽  
Emission Trading ◽  
Chinese Government ◽  
Synergy Effect ◽  
Factor Productivity ◽  
Plan Period ◽  
Carbon Emission Trading ◽  
The Impact

The global warming has become a serious issue in the world since the 1980s. The targets for the first commitment period of the Kyoto Protocol cover emissions of the six main greenhouse gasses (GHGs). China is the world's largest CO2 emitter and coal consumer and was responsible for 27.3 percent of the global total CO2 emission and 50.6 percent of the global total coal consumption in 2016 (BP, 2017). As China plays an important role in the global climate change, China has set goals to improve its environmental efficiency and performance. In 2011, the Chinese government for the first time announced an intent to establish carbon emission trading market in China. Eight regional emission trading schemes have been operating since 2013 (seven pilot markets during the 12th Five Year Plan period and one pilot market during the 13th Five Year Plan period) including provinces of Guangdong, Hubei, and Fujian, and cities of Beijing, Tianjin, Shanghai, Shenzhen, and Chongqing. The goal of these regional emission trading pilot markets is to help the government establish an efficient carbon emission trading scheme at national level. Some researchers have been focused on examining the impact of emission trading schemes in China using CGE model by constructing different scenarios and ex-ante analysis using data prior to emission trading pilot markets implementation. While this paper tries to conduct an ex-post analysis with data of 2005-2017 to evaluate the impact of emission trading pilot markets in China at provincial level using difference-in-difference (DID) model. By including both CO2 and SO2 as undesirable outputs to calculate Malmquist-Luenberger (ML) Index to measure green total factor productivity, this paper plans to evaluate the impact of carbon emission trading pilot markets in China via emission reduction, regional green development, synergy effect and influencing channels. This paper tries to answer the following research questions: (1) Do emission trading pilot markets reduce CO2 emission and increase regional green total factor productivity? (2) Is there any synergy effect from emission trading pilot markets? (3) What are the influencing channels of emission trading pilot markets? Keywords: Emission trading, CO2 emissions, Different-in-difference

Hospital Informatization in China During the COVID-19 Pandemic: A Cross-Sectional Internet-Based Survey Study (Preprint)

2020 ◽  
Author(s):  
Ke Zeng ◽  
Weiguo Zhu ◽  
Caiyou Wang ◽  
Liyan Zhu
Keyword(s):  
Information Technology ◽  
Information Security ◽  
Medical Information ◽  
Survey Study ◽  
Chinese Government ◽  
Qr Code ◽  
Cross Sectional ◽  
Network Information ◽  
Tertiary Hospitals ◽  
The Impact

BACKGROUND The rapid spread of COVID-19 has created a severe challenge to China’s healthcare system. Hospitals across the country reacted quickly under the leadership of the Chinese government and implemented a range of informatization measures to effectively respond to the COVID-19. OBJECTIVE To understand the impact of the pandemic on the medical business of Chinese hospitals and the difficulties faced by hospital informatization construction. To discuss the application of hospital informatization measures during the COVID-19 pandemic. To summarize the practical experience of hospitals using information technology to fight the pandemic. METHODS Performing a cross-sectional on-line questionnaire survey in Chinese hospitals, of which the participants are invited including hospital information staff, hospital administrators, medical staff, etc. Statistical analyzing the collected data by using SPSS version 24. RESULTS A total of 804 valid questionnaires (88.45%) are collected in this study from 30 provinces in mainland China, of which 731 (90.92%) were filled out by hospital information staff. 473 (58.83%) hospitals are tertiary hospitals while the remaining 331 (41.17%) are secondary hospitals. The majority hospitals (82.46%) had a drop in their business volume during the pandemic and a more substantial drop is found in tertiary hospitals. 70.40% (n=566) of hospitals have upgraded or modified their information systems in response to the epidemic. The proportion of tertiary hospitals that upgraded or modified systems is significantly higher than that of secondary hospitals. Internet hospital consultation (70.52%), pre-check and triage (62.56%), telemedicine (60.32%), health QR code (57.71%), and telecommuting (50.87%) are the most used informatization anti-pandemic measures. There are obvious differences in the application of information measures between tertiary hospitals and secondary hospitals. Among these measures, most of them (41.17%) are aiming at serving patients and most of them (62.38%) are universal which continue to be used after pandemic. The informatization measures are mostly used to control the source of infection (48.19%), such as health QR Code, etc. During the pandemic, the main difficulties faced by the hospital information department are “information construction projects are hindered” (58.96%) and “increased difficulty in ensuring network information security” (58.58%). There are significant differences in this issue between tertiary hospitals and secondary hospitals. The shortcomings of hospital informatization that should be made up for are “shorten patient consultation time and optimize consultation process” (72.51%), “Ensure network information security” (72.14%) and “build internet hospital consultations platform” (59.95%). CONCLUSIONS A significant number of innovative medical information technology have been used and played a significant role in all phases of COVID-19 prevention and control in China. Since the COVID-19 brought many challenges and difficulties for informatization work, hospitals need to constantly improve their own information technology skills to respond to public health emergencies that arise at any moment.

scholarly journals Formation of an Export-Oriented Agricultural Economy and Regional Open Innovations

2021 ◽  
Vol 7 (1) ◽  
pp. 32
Author(s):  
Victor L. Shabanov ◽  
Marianna Ya Vasilchenko ◽  
Elena A. Derunova ◽  
Andrey P. Potapov
Keyword(s):  
Agricultural Economy ◽  
Institutional Management ◽  
Agricultural Exports ◽  
Modeling Methodology ◽  
Fixed Assets ◽  
Analysis Application ◽  
The Impact ◽  
The Relationship

The aim of the work is to find relevant indicators for assessing the relationship between investments in fixed assets in agriculture, gross output of the industry, and agricultural exports using tools for modeling the impact of innovation and investment development on increasing production and export potential in the context of the formation of an export-oriented agricultural economy. The modeling methodology and the proposed estimating and forecasting tools for diagnosing and monitoring the state of sectoral and regional innovative agricultural systems are used to analyze the relationship between investments in fixed assets in agriculture, gross output of the industry, and agricultural exports based on the construction of the classification of Russian regions by factors that aggregate these features to diagnose incongruence problems and to improve institutional management in regional innovative export-oriented agrosystems. Based on the results of the factor analysis application, an underestimated role of indicators of investment in agriculture, the intensity and efficiency of agricultural production, were established. Based on the results of the cluster analysis, the established five groups of regions were identified, with significant differences in the level of investment in agriculture, the volume of production of the main types of agricultural products, and the export and exported food. The research results are of practical value for use in improving institutional management when planning reforms and transformations of regional innovative agrosystems.

scholarly journals Integrated IEW-TOPSIS and Fire Dynamics Simulation for Agent-Based Evacuation Modeling in Industrial Safety

Safety ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. 47
Author(s):  
Wattana Chanthakhot ◽  
Kasin Ransikarbum
Keyword(s):  
Emergency Evacuation ◽  
Industrial Sector ◽  
Industrial Safety ◽  
Dynamics Simulation ◽  
Entropy Weight ◽  
Fire Dynamics ◽  
Evacuation Simulation ◽  
Evacuation Modeling ◽  
Agent Based ◽  
The Impact

Emergency events in the industrial sector have been increasingly reported during the past decade. However, studies that focus on emergency evacuation to improve industrial safety are still scarce. Existing evacuation-related studies also lack a perspective of fire assembly point’s analysis. In this research, location of assembly points is analyzed using the multi-criteria decision analysis (MCDA) technique based on the integrated information entropy weight (IEW) and techniques for order preference by similarity to ideal solution (TOPSIS) to support the fire evacuation plan. Next, we propose a novel simulation model that integrates fire dynamics simulation coupled with agent-based evacuation simulation to evaluate the impact of smoke and visibility from fire on evacuee behavior. Factors related to agent and building characteristics are examined for fire perception of evacuees, evacuees with physical disabilities, escape door width, fire location, and occupancy density. Then, the proposed model is applied to a case study of a home appliance factory in Chachoengsao, Thailand. Finally, results for the total evacuation time and the number of remaining occupants are statistically examined to suggest proper evacuation planning.

scholarly journals Statistical Analysis and Machine Learning Prediction of Fog-Caused Low-Visibility Events at A-8 Motor-Road in Spain

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 679
Author(s):  
Sara Cornejo-Bueno ◽  
David Casillas-Pérez ◽  
Laura Cornejo-Bueno ◽  
Mihaela I. Chidean ◽  
Antonio J. Caamaño ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Probability Distributions ◽  
Pearson Correlation ◽  
Likelihood Method ◽  
Neural Network Approach ◽  
Event Duration ◽  
Full Characterization ◽  
Low Visibility ◽  
Learning Machine ◽  
The Impact

This work presents a full statistical analysis and accurate prediction of low-visibility events due to fog, at the A-8 motor-road in Mondoñedo (Galicia, Spain). The present analysis covers two years of study, considering visibility time series and exogenous variables collected in the zone affected the most by extreme low-visibility events. This paper has then a two-fold objective: first, we carry out a statistical analysis for estimating the fittest probability distributions to the fog event duration, using the Maximum Likelihood method and an alternative method known as the L-moments method. This statistical study allows association of the low-visibility depth with the event duration, showing a clear relationship, which can be modeled with distributions for extremes such as Generalized Extreme Value and Generalized Pareto distributions. Second, we apply a neural network approach, trained by means of the ELM (Extreme Learning Machine) algorithm, to predict the occurrence of low-visibility events due to fog, from atmospheric predictive variables. This study provides a full characterization of fog events at this motor-road, in which orographic fog is predominant, causing important traffic problems during all year. We also show how the ELM approach is able to obtain highly accurate low-visibility events predictions, with a Pearson correlation coefficient of 0.8, within a half-hour time horizon, enough to initialize some protocols aiming at reducing the impact of these extreme events in the traffic of the A-8 motor road.

scholarly journals Nitrate-dominated PM<sub>2.5</sub> and elevation of particle pH observed in urban Beijing during the winter of 2017

2020 ◽  
Vol 20 (8) ◽  
pp. 5019-5033 ◽  
Author(s):  
Yuning Xie ◽  
Gehui Wang ◽  
Xinpei Wang ◽  
Jianmin Chen ◽  
Yubao Chen ◽  
...  
Keyword(s):  
Atmospheric Aerosols ◽  
Ammonia Concentration ◽  
Historical Record ◽  
Molar Ratio ◽  
Effective Control ◽  
Nitrate Content ◽  
Chinese Government ◽  
Low Level ◽  
The Impact ◽  
Pollution Episodes

Abstract. The Chinese government has exerted strict emission controls to mitigate air pollution since 2013, which has resulted in significant decreases in the concentrations of air pollutants such as SO2. Strict pollution control actions also reduced the average PM2.5 concentration to the low level of 39.7 µg m−3 in urban Beijing during the winter of 2017. To investigate the impact of such changes on the physiochemical properties of atmospheric aerosols in China, we conducted a comprehensive observation focusing on PM2.5 in Beijing during the winter of 2017. Compared with the historical record (2014–2017), SO2 decreased to the low level of 3.2 ppbv in the winter of 2017, but the NO2 level was still high (21.4 ppbv in the winter of 2017). Accordingly, the contribution of nitrate (23.0 µg m−3) to PM2.5 far exceeded that of sulfate (13.1 µg m−3) during the pollution episodes, resulting in a significant increase in the nitrate-to-sulfate molar ratio. The thermodynamic model (ISORROPIA II) calculation results showed that during the PM2.5 pollution episodes particle pH increased from 4.4 (moderate acidic) to 5.4 (more neutralized) when the molar ratio of nitrate to sulfate increased from 1 to 5, indicating that aerosols were more neutralized as the nitrate content elevated. Controlled variable tests showed that the pH elevation should be attributed to nitrate fraction increase other than crustal ion and ammonia concentration increases. Based on the results of sensitivity tests, future prediction for the particle acidity change was discussed. We found that nitrate-rich particles in Beijing at low and moderate humid conditions (RH: 20 %–50 %) can absorb twice the amount of water that sulfate-rich particles can, and the nitrate and ammonia with higher levels have synergetic effects, rapidly elevating particle pH to merely neutral (above 5.6). As moderate haze events might occur more frequently under abundant ammonia and nitrate-dominated PM2.5 conditions, the major chemical processes during haze events and the control target should be re-evaluated to obtain the most effective control strategy.

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