Search

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]

Metro intelligent system produces massive passenger flow and traffic data every day, among which route, station, and operation data are important for optimizing the train operation scheme. We collect passenger flow information of Shenzhen metro, analyze the passenger flow pattern and its distribution characteristics based on the data warehouse of the Hadoop platform, and optimize the train operation scheme in this paper. Using dynamic passenger flow data, an optimization model with train departure and dwell time as decision variables and passenger waiting time, passenger ride time, train full load ratio, and train operation balance as objectives is developed. An improved parallel genetic algorithm (GA) incorporating a simulated annealing algorithm (SAA) and an optimal individual retention strategy is used to find the optimal result. To verify the usefulness of the method, simulation experiments are conducted on the optimization model and method using the real passenger flow and train operation data of Shenzhen metro, and the simulation results are compared with the original plan. [ABSTRACT FROM AUTHOR]

The construction of the Guangdong-Hong Kong-Macao Greater Bay Area requires the establishment of a comprehensive port cooperation mechanism. Coordination is key to port integration. This paper establishes a multi-group Lotka-Volterra model based on the theory of competition and cooperation to study the evolution of the relationships among Hong Kong Port, Shenzhen Port, and Guangzhou Port. The results show that the three major ports have predator-prey roles and form a symbiotic competition and cooperation ecological pattern. The extended Hotelling model is established to study the central ports' spatial differences; the results show that whether it is the central port cooperation body or the entire central port group, the gains from Shenzhen Port-Guangzhou Port cooperation are greater than between either and Hong Kong Port for Guangdong-Hong Kong-Macao Greater Bay Area's container business. The biggest competitor to Hong Kong Port in the container business is Guangzhou Port. Hong Kong Port will gain more from cooperation with Shenzhen Port and should strengthen such cooperation. The study provides quantitative support and reference for positioning the strategic development of the high-end shipping business in Hong Kong Port, the pilot free-trade port in Shenzhen Port, and the exploration of the Shenzhen-Hong Kong composite port, Guangzhou Port's comprehensive shipping hub. [ABSTRACT FROM AUTHOR]

Differential pricing of trains with different departure times caters to the taste heterogeneity of the time-dependent (departure time) demand and then improves the ticket revenue of railway enterprises. This paper studies optimal differential pricing for intercity high-speed railway services. The distribution features of the passenger demand regarding departure times are analyzed, and the time-dependent demand is formulated; a passenger assignment method considering departure periods and capacity constraints is constructed to evaluate the prices by simulating the ticket-booking process. Based on these, an optimization model is constructed with the aim of maximizing the ticket revenue and the decision variables for pricing train legs. A modified direct search simulated annealing algorithm is designed to solve the optimization model, and three random generation methods of new solutions are developed to search the solution space efficiently. Experimental analysis containing dozens of trains is performed on Wuhan-Shenzhen high-speed railway in China, and price solutions with different elastic demand coefficients (ϕ) are compared. The following results are found: (i) the optimization algorithm converges stably and efficiently and (ii) differentiation is shown in the price solutions, and the optimized ticket revenue is influenced greatly by ϕ , increasing by 7%–21%. [ABSTRACT FROM AUTHOR]

The planning and operation of urban buses depend heavily on the time-varying origin-destination (OD) matrix for bus passengers. In most cities, however, only boarding information is recorded, while the alighting information is not available. This paper proposes a novel method to predict the destination of a single bus passenger based on bus smartcard data, metro smartcard data, and global positioning system (GPS) bus data. First, the attractiveness of each bus stop in a bus line was evaluated, considering the attractiveness of nearby metro stations. Then, the exploration and preferential return (EPR) model was employed to estimate the probability of a bus stop to be the alighting stop, i.e., the destination, of a passenger. The estimation result was obtained through a simulation based on the Monte Carlo (MC) algorithm. The effectiveness of our method was proved through a case study on the bus network in Shenzhen, China. [ABSTRACT FROM AUTHOR]

Presented in this paper is a study on the lateral unloading creep tests under different excess pore water pressures. The marine sedimentary soft soil in Shenzhen, China, was selected in this study. The results show that the excess pore water pressure plays a significant role in enhancing the unloading creep of soft soil. Higher excess pore water pressure brings more obvious creep deformation of soft soil and lower ultimate failure load. Meanwhile, the viscoelastic and the viscoplastic modulus of soft soil were found to exponentially decline with creep time. A modified merchant model and a combined model of the modified merchant model and plastic elements are used to simulate the viscoelastic and the viscoplastic deformation, respectively. Therefore, a lateral unloading creep model of soft soil is developed based on the modified merchant model. The accuracy and applicability of this model were verified through identifying the parameters in the model. Research results are of particular significance to the numerical simulation of underground space excavation in soft soil areas which considers the effects of excess pore water pressure. [ABSTRACT FROM AUTHOR]

Short-term Origin-Destination (OD) flow prediction plays a major part in the realization of Smart Metro. It can help traffic managers implement dynamic control strategies to improve operation safety. Also, it can assist passengers in making reasonable travel plans to improve the passenger experience. However, there are problems that the dimension of OD short-term traffic prediction is much higher than the base number of metro stations and the OD matrix is sparse. To resolve the above two problems, a threshold-based method is proposed to extract key OD pairs first. OD passenger flow contains the attribute information of the Origin-Destination station and exhibits similar time evolution characteristics, so the spatial and temporal correlation needs to be considered in the prediction. Pearson correlation matrix is used to build a virtual graph and model the virtual connection between OD pairs. A spatiotemporal virtual graph convolutional network (ST-VGCN), which combines the advantages of a graph neural network and gated recurrent neural network, is proposed to identify spatial associations and temporal patterns simultaneously. The proposed method is evaluated on 39 days of real-world data from Shenzhen Metro, which outperforms other benchmarks. The research in this work can contribute to the development of short-term OD flow forecasts and help to provide ideas for the research on real-time operation and management of rail transit. Furthermore, it can help to establish passenger flow prediction and early warning mechanisms to quickly evacuate a large number of passengers in case of emergency. [ABSTRACT FROM AUTHOR]

Environment is the external factor that affects the durability of concrete structures. Buildings in different regions with different climates will respond to durability deterioration in different ways. For macroenvironmental regionalization, the dominant factor analysis method of the climatic zonation was applied into the environmental regionalization in this paper. Based on the environmental characteristics in China and the effect of environmental factor on the durability of concrete structure, the proper regionalization indexes are chosen, and the environmental regionalization is made. For microenvironmental regionalization, fuzzy set and rough set theories were used in date mining on discrete measured data, and the weight determination of various factors affecting durability was transformed into evaluation of the significance of attributes among rough sets. The method of durability environmental regionalization is established by analyzing the degree of influence that various factors have on the durability of concrete structures. The result of durability environmental regionalization for concrete structures in Shenzhen city shows that the proposed approach is reasonable. [ABSTRACT FROM AUTHOR]