IEIS 2023

The problem of difficult and expensive financing for small and medium-sized enterprises is not only a problem for enterprise operations, but also a difficult point for scholars to study. Based on the Stackelberg game and prospect theory, this paper constructs a supply chain model composed of a retailer, characterized by loss aversion and financial constraints, a risk-neutral manufacturer, which is a core enterprise with strong capital in the supply chain, and a investor, using reverse induction method to solve the optimal order quantity and optimal wholesale price under the mixed model of delayed payment and equity financing, and also studies the influence of parameters.

This paper combines the background of carbon peaking, takes the panel data of manufacturing subdivision industries in the Beijing-Tianjin-Hebei region from 2016 to 2020 as the sample, calculates the industrial gradient coefficient and carbon emissions, and also analyzes the current status of transferring manufacturing industries and carbon emissions in the Beijing-Tianjin-Hebei Urban Agglomeration to reveal the relationship between the transfer of manufacturing industries and carbon emissions transfer. Based on the current status of carbon peak, the paths of manufacturing industry transfer in the Beijing-Tianjin-Hebei Urban Agglomeration are proposed in terms of the choice of transferring industries and the selection of undertaking places, respectively.

Due to external adverse shocks such as COVID-19 and the Russia-Ukraine war, bank resilience is a vital measure used to defend against risk-taking. Using annual data from 42 listed commercial banks in China over the period 2013 to 2022, the study employs the Z-score as a dependent variable to measure risk-taking and the bank resilience index as an independent variable to measure capability to defend against bank risk-taking. In addition, the study adds bank-specific factors of bank size, net income margin, inefficiency, ratio of loans to deposits, cash flow, and diversification as control variables into the regression model. The empirical results of the study show that bank resilience could lower risk-taking, and bank size has a promoting effect on the relationship between bank resilience and risk-taking. As for heterogeneity analysis, banks with high-BRI have greater capability to defend against risk-taking than banks with low-BRI. Furthermore, the bank resilience of non-state-owned banks could reduce risk-taking, while state-owned banks have no impact of bank resilience on risk- taking.

This paper investigates the causality between bitcoin market and WTI crude oil market through multi-scale analysis and causality testing. The complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method is employed to decompose the two price series at different time-scales. In causality testing, a nonlinear Granger causality test is formulated to investigate the relationship among each pair of matched components. And we also divide the information components of different series into high-frequency components, low-frequency components and long-term trend according to the Fine-to-coarse reconstruction. In the end, a set of hypothetical scenarios are created and a statistical test for causality is performed.

In the context of digital China, the digital economy has become an important engine of China’s economic growth. In combination with the rural revitalization policy proposed in the No. 1 central document of the Central Committee, it is imperative to use the digital economy to drive rural development. This paper theoretically combs the relationship between digital inclusive finance, farmers’ credit and farmers’ income increase. On this basis, based on the provincial panel data from 2011 to 2020, constructs a mediating effect model, the impact of the development of digital inclusive finance in the digital economy on farmers’ income and the basic transmission mechanism are empirically analyzed. The results show that: (1) The development of digital economy can promote the increase of farmers’ income (2) In terms of impact mechanism, digital inclusive finance can increase farmers’ income by alleviating farmers’ credit constraints. After various robustness tests and elimination of two-way causality, the conclusion of this paper still holds.

5G, as a new communication technology, has the characteristics of large bandwidth, large connection, and low delay. In railway application scenarios, such as the car integration test scenario, 5G support is needed for multi-time, multi-terminal, and multi-dimensional access. Car integration data needs to maintain space-time synchronization and carry terminal location information. 5G must ensure network security, reliable data transmission, and meet low delay requirements.

In this paper, we explore the vehicle integration test multi-source data fusion scheme. We design the monitoring system and positioning synchronization system connection scheme using linear reference and dynamic segmentation technology. Based on space-time database technology support, we use the Lagrange linear interpolation method for linear reference detection data. We reuse dynamic segmentation based on events to establish a railway space-time data model. This study enhances the timeliness of data analysis and mining. The proposed technological solution enables the rapid transmission and efficient interaction of detection data between the train and the ground, providing a basis for accurate diagnosis of railway infrastructure operation, maintenance, and repair conditions.

The decision-making research of industrial organization monopoly is the interdisciplinary research direction of economy and law. The study of such decisions not only helps to prevent the emergence of monopolistic behavior. It can also divide the responsibilities of the enterprises participating in the collusion from the level of legal application. Through theoretical modeling, this paper explains the generation mode and problem of collusion decision from the perspectives of economy, law and management.

Since the 21st century, three typical world cities, London, New York and Tokyo, have conducted high-density development in the central city, which is the redistribution of urban spatial resources promoted by the market mechanism in the process of the new industrial revolution. The new industrial revolution is an industrial revolution represented by information and intelligent technology to liberate and strengthen human intelligence with machines. The matching, sharing and knowledge spillover mechanism of agglomeration economy can explain why knowledge-intensive enterprises and producer service enterprises are more inclined to gather in big cities. However, China’s urban development concept and policies have not realized the significance of high-density population agglomeration to the new industrial revolution. The current policy of strictly restricting the population of megacities has suppressed the development space of knowledge-intensive enterprises and the tertiary industry. Only by solving the misunderstanding of urban planning concept can we grasp the opportunity of the new industrial revolution. Taking Beijing as an example, this article proposes that the integrated development of stations should be carried out in the rail transit hub station of Line 10 to build the urban dynamic central area.

China's economic development has shifted from high-speed and steady growth to a new stage of maintaining high-quality development. In fact, financial development can effectively promote industrial upgrading, specifically, financial development can improve industrial efficiency by promoting the support of modern service industry to manufacturing, and financial development is the foundation and core of building a modern market economy.“ Based on this, this paper selects 30 China from 2010 to 2019 The macroeconomic indicators of provinces (municipalities and regions) are used to construct a panel model, and the financial development indicators are decomposed into three indicators, such as financial scale, financial efficiency and financial structure, and the upgrading of industrial structure is decomposed into two sub-indicators of advanced and rationalization of regional industrial structure, and the direct impact mechanism of financial development on industrial structure upgrading is systematically studied. The following is the conclusion: for a very long time, the development of finance have had a significant impact on industrial structure, with the impact of financial efficiency and financial structure being greater. From this, it is proposed to reasonably control the scale of the financial market and guide the flow of bank credit; Build a diversified financial service system for the corporate sector and improve financial efficiency; Accelerate the construction and development of the financial service system, increase the level of industrial structure simplification in the region and support the high-quality growth of the local economy.

This paper investigates multi-attribute group decision-making (MAGDM) model to solve the selection of the natural detection system in High-speed railways. In this model, the attribute values provided by decision makers (DMs) are in the form of cubic intuitionistic fuzzy numbers (CIFNs). When aggregating CIFNs, cubic intuitionistic fuzzy aggregation operators (AOs) are needed. However, existing AOs of CIFNs fail to consider the interrelationship among multiple input variables, and they cannot effectively deal with DMs’ extreme evaluation values, either. Hence, this paper proposes novel cubic intuitionistic fuzzy AOs based on power average operator and Muirhead mean, i.e., cubic intuitionistic fuzzy power weighted average operator and cubic intuitionistic fuzzy power Muirhead mean operator. In addition, the weight of the DMs can be calculate based on the social trust network and a novel method is proposed to obtain the weights of the attribute when it is unknown. Finally, a numerical example was performed to illustrate the application of the proposed method.

In recent years, rainstorm disasters occurred frequently, affecting the normal operation of the urban rail transit system, causing substantial economic and property losses, and even endangering people's lives and health. Based on this, this paper will simultaneously consider the urban rail transit stations and networks in the context of rainstorm disasters and build a network resilience assessment system from the three perspectives of the station's resistance capacity, absorption capacity, and recovery capacity. Based on the resilience theory and resilience analysis system, and considering the network topology and network efficiency, this paper will build a network performance function, and use this function to construct the recovery model and study the recovery sequence of failed sites.

The electrification of transportation has become an inevitable trend for sustainable urban development. However, the rapid population of electric vehicles and the improvement of charging infrastructure are in a state of imbalance, urgently requiring solutions for the imperfect charging infrastructure, charging path decision-making, and charging time selection. Existing charging recommendations mostly rely on distances and charging prices, without considering the users’ travel demands. In this paper, aimed to maximize the utility of users’ travel, with charging as a constraint, we propose a user activity-based Markov decision Process (MDP). Besides, the availability of charging stations is a critical factor influencing the sustainable development of electric vehicles, we also consider the availability of charging station into this model and apply reinforcement learning algorithm to get the optimal charging recommendations. Finally, we provides a charging plan for electric vehicle users by extending user activity to a week.

High-speed railway data assets provide basic support for analyzing railway safety management and discovering accident rules. Based on the analysis of the current data management situation in China’s railway industry, combined with the characteristics of a complex network and large linkage of railway global data, this paper studies the integration theoretical model of railway global risk prevention and control. It analyzes the big data requirements of railway global data management from three aspects of the “human-machine-environment” and finally realizes the real-time accuracy of railway global risk prevention and control. To minimize the overall operation risk, improve the intelligent level of railway safety prevention and control.

With the increasing importance of environmental protection and the introduction of the dual carbon strategy, green supply chains aim to achieve sustainable development of enterprises and increase the audit of green content of enterprises, thus facilitating financing for SMEs. However, compared with supply chain finance, the structure and process of green supply chain finance are more complex and involve many factors, so the probability of risk occurrence is increased and risk contagion is very easy to occur. The existing studies on risk contagion in green supply chain finance have mostly evaluated the risks under static time nodes and lacked the concept of “green” or separate dynamic evolution of risks, which failed to show the overall evolution of risk contagion better. To this end, this paper first uses literature analysis to build a green supply chain financial risk contagion measurement index system to determine the current risk status of enterprises from a static time perspective, and then combines the characteristics of risk contagion based on the SEIRE contagion dynamics model, and uses python programming language to input the enterprise risk status to simulate the green supply chain financial risk contagion path from a dynamic perspective, so as to complete the risk measurement. The results found that the risk contagion rate of green supply chain finance is the key factor to determine the current supply chain risk, i.e., the increase of contagion rate accelerates the enterprise’s bankruptcy; the risk repeated infection rate is the key factor to determine the supply chain recovery from risk, i.e., the increase of repeated contagion rate will weaken the enterprise’s recovery ability.

In order to solve the problems of low search efficiency and easy to fall into local optimal solution when using traditional ant colony algorithm for path planning of mobile robots, an improved immune ant colony hybrid algorithm is proposed. Firstly, the optimal solution is obtained by using the fast global convergence of the immune algorithm, which is used as the initial pheromone distribution of the ant colony algorithm. On this basis, the improved ant colony algorithm is used for global path planning, which effectively solves the problem that the search efficiency is low due to the lack of pheromone in the early stage. By comparing the experimental results of the two algorithms, the advantages of hybrid algorithm are illustrated. The experimental results show that the improved Immune Ant Colony Algorithm can better solve the path planning problem of mobile robots in complex environments.

In recent years, many scholars have advocated the development of public transportation in China’s cities in response to increasing traffic congestion and environmental pollution. However, the fixed departure time, peak hour congestion, and “last mile” problems have forced city managers to focus on the development of the taxi industry at the same time, and with the improvement of Internet technology, ride-hailing have become mainstream. At the city scale, a study based on ride-hailing mode can take full advantage of big data technology to reduce uncertainty and provide suggestions for controlling fleet size and improving system efficiency. Based on Occam’s razor theorem, this paper gives a research framework for a minimalist model, including the construction of urban road networks, the generation of passengers, the matching between passengers and vehicles, and the movement of vehicles. By carrying out a simple analysis, the results prove that the model constructed in this paper can reflect the universal characteristics of the system although it ignores many details, which can provide a reference for studying many problems in the ride-hailing system in reality.