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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]

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]

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]

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]

Whether capital market opening improves the price discovery efficiency of stock market is an important issue. Shanghai-Hong Kong Stock Connect (hereafter, SHKSC) is a milestone event in the opening up of China's capital market. Based on SHKSC, using the method of PSM + DID, we study the impact of capital market opening on the price discovery efficiency from two dimensions-stock price information content and price reaction speed to information. Our research shows that capital market opening did not increase stock price information content, but speed up the reaction of price to information. Therefore, capital market opening improves capital market's price discovery efficiency in terms of response speed of stock price to information. Further analysis shows that capital market opening affects stock price reaction speed through improving market information environment and reducing insider trading, but it has not yet had a substantial impact on listed companies' earnings quality, which is the main participant in the capital market, and therefore has failed to influence the stock price information content. In order to maximize the effectiveness of capital market opening, it is necessary to introduce more effective policies to improve the information disclosure quality of listed firms and reduce the level of insider trading. [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]

Risk preference has constantly been one of the vital issues in economics and finance. In this study, the time series and term structure of Chinese investors' implicit risk aversion are investigated using the implicit risk aversion extraction method, and the dynamic term structure of Chinese investors' implicit risk aversion is modeled using the Vasicek model. In the empirical process, the SSE 50 ETF option data from March 2015 to July 2018 are adopted to extract model-free risk-neutral skewness. The standard deviation, skewness, and kurtosis of reality measure are extracted using the Shanghai 50 ETF data, and then the monthly implied risk aversion time series and term structure of Chinese investors are obtained. As indicated by the results of this study, the risk preference of Chinese investors exhibits significant time series characteristics, and it will show risk-loving and risk-averse phenomena at certain times. Moreover, for different periods in the future, differences are generated in investors' risk preferences, suggesting an aversion to short-term risk and a certain tolerance for long-term risk, i.e., there are significant characteristics of the term structure. Besides, the term structure of implied risk aversion of Chinese investors is dynamically modeled using the Vasicek model. To be specific, its first principal component can account for 90% of the change in the term structure. The "level factor" refers to the critical factor load, and the level of long-term implied risk aversion reaches 0.658. Furthermore, the term structure of implied risk aversion exhibits the characteristics of mean regression. Next, more effective research results on investors' risk preference are achieved, and the time-varying characteristics and term structure characteristics of investors' risk preference are investigated. The result suggests that the long-term risk preference of Chinese investors approaches 1, and there is a significant feature of "mean regression," i.e., a vital finding of this study. [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]

Microgrids allow energy exchange among multiple interconnected microgrids for greater energy efficiency and collective economic interest. However, in some cases, the benefit of some microgrids within the network may not be uncertain. In view of the increasing development of electric vehicles (EVs), a multiobjective model is proposed to improve the performance of microgrids by integrating electric vehicles-to-grid (V2G) and vehicles-to-building (V2B) based on global and individual benefit balance. Two reference models are built to verify the validity of the proposed method, and models are formulated as mixed integer linear programming formats solved by the weighting method. A set of parameters of microgrids are adopted to model the driver behaviors (e.g., available hours of EV), energy transactions (e.g., electricity), performance factor (e.g., emission factor), distributed energy (e.g., solar panel), and energy load of five commercial buildings (e.g., hotel) located in Shanghai. Simulation results demonstrate the effectiveness of the operation decision models in the energy management of microgrids under neutral, proeconomic, proenvironmental, and proenergy weighting scenarios. The case study results specify that the proposed method can achieve operational cost, CO2 emission, and primary energy consumption reductions for each microgrid, with total benefits declining slightly. [ABSTRACT FROM AUTHOR]

Due to the long design cycle of watercolor cultural and creative products, a design method based on style transfer algorithm is proposed. Here, the design of Shanghai style watercolor painting cultural and creative products is taken as the research object, VGG-19 network is used as the style transfer model, and the loss function of style transfer algorithm is designed. The simulation results show that the proposed method can effectively extract and reconstruct the color, texture, brushstroke, and other styles of Shanghai style watercolor painting. The generated new images are added as design elements, which makes the cultural and creative products have both appearance and personalization. In addition, the newly generated cultural and creative products have also obtained high satisfaction from experts and users, which meet the aesthetic changes. It can be seen that proposed method provides a new idea for the design of watercolor cultural and creative products, which shortens the product design cycle, reduces the design cost, and has a certain practicality. [ABSTRACT FROM AUTHOR]

Since the society enters the information age, science and technology have changed with each passing day. Electronic information has deeply affected social development and people's life. Based on the statistical correlation algorithm, this study analyzes the establishment model of statistical correlation algorithm. Then, the feature extraction technology of electronic information is obtained according to the statistical correlation algorithm, which promotes the development of electronic information., Afterwards, the feature extraction methods of electronic information among four cities of Beijing, Shanghai, Chongqing and Tianjin are compared and analyzed in detail. The experimental results show that the electronic information feature extraction method based on statistical correlation can be well applied in four municipalities directly under the central government, which provides some theoretical and experimental support for the electronic information feature extraction method in our country. [ABSTRACT FROM AUTHOR]

Using the Shanghai Interbank Offered Rate data of overnight, 1 week, 2 week and 1 month, this paper provides a comparative analysis of some popular one-factor short rate models, including the Merton model, the geometric Brownian model, the Vasicek model, the Cox-Ingersoll-Ross model, and the mean-reversion jump-diffusion model. The parameter estimation and the model selection of these single-factor short interest rate models are investigated. We document that the most successful model in capturing the Shanghai Interbank Offered Rate is the mean-reversion jump-diffusion model. [ABSTRACT FROM AUTHOR]

In the overall planning of a city, it is important to formulate the reasonable structure of urban space which needs lots of research studies as strong supports. One of these supports is the relationship between the urban built environment and human behavior, and this has been of interest to the field of urban transportation planning. The essential element in this research field is the development of appropriate measures for individual's activity space based on the collected data. This study introduced a new dataset, the cellular signaling data (CSD), and corresponding measures to analyze the relationship between the urban built environment and individual's activity space. The CSD have more detailed time-space stamps of individual's activities compared with traditional surveys, questionnaires, and even call detailed record (CDR) data. The individual's activity space is defined based on the anchor point theory. The convex polygon approach was used to describe the geometrical shape of individual's activity space. The proposed methodology was verified with the CSD collected in Shanghai. The results show that the total number of the cellphone users investigated in this study can be categorized into three different groups with specific characteristics of activity spaces. The results may benefit for related urban agencies to implement customized policy for the purpose of transportation demand management. [ABSTRACT FROM AUTHOR]

Carbon emissions cost is a potential effective measure to restrict hydrocarbon pollution in the international shipping trade. The minimization of the total cost is pursued by ship operators, whereas voyage cost is increasingly involving the replacement of clean fuel and changing the cost of the shipping route. A flexible optimization method focusing on maximizing the total profit is developed in terms of sailing speed optimization and single port skips integrate carbon emission influence. An actual ocean shipping route from Shanghai to Rotterdam is applied to validate the effectiveness of the proposed models. The results have shown that the shipping route profit is volatile along with the sailing speed and the number of port calls. However, the profit will be maximized when applying the single port skip and will slow down the sailing speed at the same time. The demand of planned skip port can be supported by a short line container. A system composed of ocean container liner and short line container can improve the profit by 4.05% and reduce the carbon emission by 19.70%. Furthermore, sensitive results show that the profit is less affected by the changing of the carbon emission cost. A small size container has enough ability to solve the short transportation demand in adjacent ports and convert extraberthing cost into profit. These findings can provide reliable support for the shipping route decision process considering future carbon emission costs. [ABSTRACT FROM AUTHOR]

With the technological advancement, China's high-speed rail (HSR) has achieved a higher running speed than ever before, which at the same time leads to the intensive competition between air and high-speed rail with trips within 500–1000 km, as well as to the significant changes of travelers' air-to-HSR choice. In order to explore the dynamic adaptation of travelers' choice of high-speed rail (HSR) and air in the case of HSR speed-up, a logit dynamics model of travelers' choice based on evolutionary game was constructed to describe the evolution of travelers' choice. With HSR-air travel time and the ticket price of origin-destination (OD) points of Beijing-Shanghai as the benchmark, the study set up two scenarios of HSR speed-up and compared and analyzed their payoffs in value. On the basis of mathematical simulation, the travelers' "air-to-HSR choice" and the change of competition range under the background of HSR speed-up were both discussed. The result indicated that the HSR speed-up would attract more travelers, and its share rate would rise to 58.31% and 72.73%, respectively, with HSR running speed increasing to 400 and 600 km/h; the marginal utility of HSR speed-up is more obvious, and in the meantime, the increase of HSR running speed extends the intense HSR-air competition range to longer-distance travels. In the case of HSR speed-up, travelers' choice changes as well. The HSR operators themselves should formulate reasonable ticket prices and improve their management. At the same time, the air operators should adjust their operation plan in time. [ABSTRACT FROM AUTHOR]

In view of the problem of competitive facility location in urban planning, the response of competitors to the new facility is considered. We use Huff's probability model to describe the market share of all facilities which depends on its service quality and its distance from customers. To maximize the market share of facilities, a two-stage method (quality decision stage and location decision stage) is adopted, which takes into account the responses of competitors. In the stage of quality decision, the competitive decision-making process is simulated as a game process and solved by Nash equilibrium. The solution of the quality decision process can be expressed as a function of the new facility's location which can be obtained by polynomial approximation. In the location decision stage, we apply the interval analysis based on branch and bound algorithm to determine the optimal location of new facility. Then, we use the randomly generated numerical experiment to verify the effectiveness of the model and algorithm. Finally, we apply this model and algorithm to the location of a new shopping mall in Putuo district, Shanghai. [ABSTRACT FROM AUTHOR]

Due to its capability to reduce fuel consumption and increase energy efficiency, the combined cooling, heating, and power (CCHP) system has obtained great concern during the last decade. A large number of deterministic and stochastic optimization models were proposed for supporting the operation management of the CCHP system, but few studies noticed that users' demands in the real world may be subjected to twofold randomness with incomplete or uncertain information. In this study, a birandom chance-constrained linear programming (BCCLP) model is developed for identifying optimal operation strategies under random uncertainties. Compared with traditional stochastic programming models, the BCCLP model made the improvement through describing the energy demands as the birandom variables firstly, instead of traditional random variables. This way effectively avoided potential imbalance between energy supply and demand caused by oversimplified expression of uncertain parameters. A gas-fired CCHP system of a hotel in Shanghai, China, was used as a study case for demonstration. A variety of operation strategies are obtained under specific constraints-satisfaction conditions. It is concluded that the BCCLP model was capable of generating the cost-effective operation strategies and evaluating the tradeoffs between system economy and reliability. The influence imposed by some critical parameters on the system performance was examined through the sensitivity analysis, which provided the important guidance to the design and operational management of other similar CCHP systems in the future. [ABSTRACT FROM AUTHOR]

This study investigates the pavement network maintenance and rehabilitation (M&R) programming problem, over a certain planning horizon and in the context of limited funding. We designed an integer programming model to fulfill three purposes, namely, optimize the road conditions, minimize user disturbance costs, and minimize agency costs. We present a case study in which this model is applied to the pavement network of Shanghai. We investigate the results through the use of five M&R strategies, to identify the Pareto-optimal trade-offs inherent in developing pavement network M&R planning. The results demonstrate that there is a positive relationship between PCI improvement and user disturbance costs and between PCI improvement and agency costs. Additionally, we conduct a comparative analysis between agency and government-oriented strategies to evaluate the effectiveness and equity consideration. The findings suggest that the government-oriented strategy improves the pavement condition effectively with low user disturbance costs, and the agency-oriented strategy accounts for more equity consideration. Finally, we formulate an extension model that considers multiple road types, for application to pavement network M&R programming. The results show that light rehabilitation and preventive maintenance are the most frequently implemented treatments on arterial roads and secondary trunk roads from the case network implementation. This study helps decision-makers identify the trade-offs made when developing a pavement network M&R program. [ABSTRACT FROM AUTHOR]

By analyzing the background of land leasing in Shanghai, the hypotheses of the mathematical models of industrial land leasing in Shanghai are proposed, and then, the mathematical models of the land price and land area are presented for analyzing the factors of industrial land leasing. Based on the mathematical models and the district data of Shanghai from 2007 to 2015, the factors influencing industrial land leasing by the district government are studied. It is shown that the influencing factors, such as the land area, GDP, tenure of district mayor, and the distance between the land and the nearest subway station, affect the government behavior on industrial land leasing. [ABSTRACT FROM AUTHOR]

Grouting reinforcement technology gradually has been widely used to repair the subgrade settlement diseases, but the current single application of discrete element software or finite element software cannot effectively simulate the grouting process. Therefore, one new method is put forward in the research of grouting based on the CFD-DEM coupling principle. And then, one typical subgrade section in the Shanghai–Nanjing intercity railway is used to simulate the grouting process and diffusion mechanism of slurry from microlevel. Based on the results of site survey, some findings are shown as follows: First, the new method is feasible which integrates the favorable aspects of discrete elements, finite elements, and boundary elements. Second, the greater the grouting pressure, the greater the influence range of grouting, and it shows six petals shape. When the grouting pressure is small, the grouting generally shows penetration or extrusion grouting, and its influence range is small. When the grouting pressure is large enough, it is characterized by splitting grouting, and the influence range of grouting is getting larger and larger. Third, the growth rates of influence range gradually increase with the increasement of grouting pressures, and the reasonable selection of grouting pressures is very important. [ABSTRACT FROM AUTHOR]