Search

According to the proposal of Kyoto protocol, carbon dioxide emission rights are traded as a commodity, and carbon emission trading market emerges as the times require. As the world's largest carbon emitter, China has established eight pilot markets for carbon emission trading. Selecting the closing price of eight carbon trading markets from the establishment to June 23, 2020, this paper analyzes the daily, weekly, and monthly return series data, using the first-order autoregressive process to adjust the daily income series to eliminate the weak trading market effect and then comprehensively uses the traditional variance ratio test and multiple variance ratio test to analyze the weak-form market efficiency of the eight carbon trading markets. The empirical results show that most of the carbon trading markets are non-weak-form market efficiency, and only Tianjin, Shanghai, and Hubei markets are weak-form market efficiency under the daily trading data. However, with the increase of carbon holding period, the weak-form market efficiency continues to strengthen. It shows that liquidity, quantity, and information transparency are important factors that affect the market efficiency. [ABSTRACT FROM AUTHOR]

With the development of Internet technology, multisource big data can collect and analyze information so as to provide people with a good vision. In the process of governance, local governments will have problems of incomplete information. With the development of big data, multisource and big data will have advanced nature. Therefore, based on multisource big data, this paper analyzes the multisource big data algorithm in detail and establishes a local government governance model based on multisource big data. Then, the proposed model is applied to the local government governance process of Beijing, Shanghai, Chongqing, and Tianjin, and the local governance situation of each city is compared and analyzed so as to provide some reference for the optimization of the local government governance path. The experimental results show that the local governance model based on multisource big data can optimize the local government governance path and point out the direction for the local government governance path. [ABSTRACT FROM AUTHOR]

With the quality of urbanization getting more attention, city-industry integration has increasingly become a hot topic in academia. This paper is based on the traditional quantitative research of city integration, introducing the measuring model of ternary coupling coordination degree of city-industry integration in Shanghai and highlighting the ecological environment has become an important factor in the process of integration. Through the entropy method and coupling coordination model to measure the integration of Shanghai, a reasonable conclusion was reached within data analyses. [ABSTRACT FROM AUTHOR]

In this paper, based on the existing research, the rural talent supply situation is analyzed. Rural talent relative to the existing rural labor force has a higher human capital of the labor force. We also discuss the part of moving workers who can be considered as talents. Financial dimension is mostly through literature collection and statistical data finding and computational calculation, according to the results of communicate indicators, to reflect its performance level. The performance analysis of organizational management dimension and institutional development dimension mainly focuses on qualitative analysis and comparative analysis, and then we summarize and evaluate the performance status of Shanghai basic endowment insurance system for urban and rural residents. Therefore, all countries in the world are constantly exploring and trying to improve the performance management model of their social security institutions. Through the evaluation and analysis of the above four dimensions, it can be found that the overall performance level of urban and rural residential insurance in Shanghai is relatively high, but there are still some problems in the operation process. [ABSTRACT FROM AUTHOR]

As for whether the customer risk leads to the inefficient investment of suppliers, 776 suppliers and customers of Shanghai and Shenzhen A-shares from 2007 to 2017 are chosen as the supply chain data of listed companies, the relationship between customer risk and supplier enterprise investment efficiency is studied by manual sorting, and the moderating effect of the nature of supply chain relationship on customer risk and enterprise investment efficiency is taken into account. According to the research, the customer risk will reduce the investment efficiency of supplier enterprises, which is manifested as underinvestment. Based on further research, the relationship is more significant in supplier enterprises with a higher customer concentration and state-owned enterprises that are customers and suppliers. The research of this paper enriches the relevant literature on investment efficiency and the relationship between customer and supplier, provides a new perspective for studying investment efficiency and the empirical evidence for risk prevention behavior among enterprises, and has important practical significance for supplier enterprises to choose core customers and manage customer relations. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the impact of intellectual capital (IC) and its components on financial competitiveness and green innovation performance. The data are collected from renewable energy companies listed on the Shanghai and Shenzhen stock exchanges during 2013–2018. The modified Value Added Intellectual Coefficient (MVAIC) model is applied as a proxy for IC efficiency, an index system is constructed to systematically measure financial competitiveness, and green innovation performance is measured by the total number of green patents, the number of green invention patents, and the number of green noninvention patents. The empirical results show that IC has an inverted U-shaped relationship with financial competitiveness and no impact on green innovation performance. Regarding IC components, human capital (HC), structural capital, and relational capital positively affect financial competitiveness. HC has a negative impact on green patents, while innovation capital has a positive impact on green invention patents. Physical capital is the main driving force of green innovation performance. This study will help managers to reasonably manage their IC resources to strengthen financial competitiveness and achieve green development. [ABSTRACT FROM AUTHOR]

Government intervention and financial support are two major means to promote the independent innovation performance of enterprises in strategic emerging industries, and government intervention has induced crowding-out effects on financial support, which leads to the uncertainty of the dual incentive effect of government intervention and financial support on enterprises' independent innovation. The research object of this paper is 657 strategic emerging enterprises listed in Shanghai and Shenzhen. We empirically studied the impact of government intervention and financial support on the comprehensive efficiency of independent innovation of strategic emerging enterprises. The empirical study draws the following conclusions. Firstly, the comprehensive efficiency of independent innovation of enterprises is in the trend of continuous improvement and technical efficiency and scale efficiency are also increasing, but the technical efficiency is lower than the scale efficiency, which shows that the improvement of independent innovation efficiency mainly depends on the expansion of innovation scale. Secondly, both government intervention and financial support promote the comprehensive efficiency of independent innovation of strategic emerging industry enterprises, but the incentive effect of government intervention is more obvious. Thirdly, there is an inverted U-shaped relationship between government intervention and the comprehensive efficiency of independent innovation. Fourthly, the regression coefficient of the interaction between government intervention and financial support and the comprehensive efficiency of enterprise independent innovation is negative, which indicates that government intervention has an inhibitory effect on the effect of financial support on the overall efficiency of enterprise independent innovation. Finally, we put forward countermeasures and suggestions. [ABSTRACT FROM AUTHOR]

In Beijing, Shanghai, Hangzhou, and other cities in China, traffic congestion caused by traffic incidents also accounts for 50% to 75% of the total traffic congestion on expressways. Therefore, it is of great significance to study an accurate and timely automatic traffic incident detection algorithm for ensuring the operation efficiency of expressways and improving the level of road safety. At present, many effective automatic event detection algorithms have been proposed, but the existing algorithms usually take the original traffic flow parameters as input variables, ignoring the construction of feature variable sets and the screening of important feature variables. This paper presents an automatic event detection algorithm based on deep cycle limit learning machine. The traffic flow, speed, and occupancy of downstream urban expressway are extracted as input values of the deep-loop neural network. The initial connection weights and output thresholds of the deep-loop neural network are optimized by using the improved particle swarm optimization (PSO) algorithm for global search. The higher classification accuracy of the extreme learning machine is trained, and the generalization performance of the extreme learning machine is improved. In addition, the extreme learning machine is used as a learning unit for unsupervised learning layer by layer. Finally, the microwave detector data of Tangqiao viaduct in Hangzhou are used to verify the experiment and compared with LSTM, CNN, gradient-enhanced regression tree, SVM, BPNN, and other methods. The results show that the algorithm can transfer low-level features layer by layer to form a more complete feature representation, retaining more original input information. It can save expensive computing resources and reduce the complexity of the model. Moreover, the detection accuracy of the algorithm is high, the detection rate is higher than 98%, and the false alarm rate is lower than 3%. It is better than LSTM, CNN, gradient-enhanced regression tree, and other algorithms. It is suitable for urban expressway traffic incident detection. [ABSTRACT FROM AUTHOR]

In recent years, the condition of urban traffic congestion in China has become more and more aggravated. Thus, from the social and environmental perspective, this paper has proposed a traffic congestion charging fee (TCCF) management model based on the system dynamics approach, taking Shanghai as a case study. The system dynamics approach applied in this paper focuses on the dynamic interrelations among some major variables in the TCCF management model. Hence, through a detailed discussion on these major variables, which are amount of car trips (ACT), growth of cars (GC), amount of NOx generation (ANG), attraction degree of car trips (ADCT), per vehicle area of roads (PVAR), and degree of traffic congestion (DTC), it is discovered that, when TCCF equals 45 yuan/day ⁎ vehicle, the DTC has declined by 67.84% and the ANG by 33.09%, which is a relatively satisfying solution to the traffic congestion problem. [ABSTRACT FROM AUTHOR]

Portfolio selection problem introduced by Markowitz has been one of the most important research fields in modern finance. In this paper, we propose a model (least squares support vector machines (LSSVM)-mean-variance) for the portfolio management based on LSSVM. To verify the reliability of LSSVM-mean-variance model, we conduct an empirical research and design an algorithm to illustrate the performance of the model by using the historical data from Shanghai stock exchange. The numerical results show that the proposed model is useful when compared with the traditional Markowitz model. Comparing the efficient frontier and total wealth of both models, our model can provide a more measurable standard of judgment when investors do their investment. [ABSTRACT FROM AUTHOR]

With the development of society, public resources for healthcare are increasingly inadequate to meet the demands for the services. Therefore, it is extremely important for policymakers to provide citizens with the most effective healthcare services within the limited available resources. In order to achieve positive effect rescue operations in the Emergency Medical Services (EMS) system, the problems including where to locate the ambulance facilities and how many ambulance vehicles should be allocated to the stations have become the focus of attention. In this paper, we study the problem based on the demand for EMS in Songjiang District, Shanghai, China, followed by the joint planning of Emergency Medical Services management, which typically consists of ambulance facility locations planning and patient’s assignment to hospitals. We proposed a modified Double Standard Model (DSM) to maximize the demand points covered at least two times within the minimum coverage criteria. The problem is solved by integer linear programming technique with the CPLEX software and we make a comparison between the solutions and the locations which exist in the emergency system used by the Songjiang emergency center. Our results show that the demand coverage rate and response time can be efficiently improved through relocating the current facilities without additional vehicle resources. [ABSTRACT FROM AUTHOR]