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In the past 70 years since the founding of the People’s Republic of China, China’s economic studies have been constantly centered on major issues such as national modernization, social economic development and the establishment, reform and improvement of socialist economic system. The paper aims to discuss this issue.

It has experienced a process of transition from the establishment of traditional Soviet’s paradigm of political economics to that of modern economics, during which drastic changes have been observed in various aspects of China’s economics, including research content, scope and methods.

Based on that, a discipline system of economics in line with international economics has been initially established. Currently, under the guidance of Marxism, scholars in China’s economics actively draw on the beneficial knowledge system and analytical methods from modern economics, emancipate their minds, seek truth from facts and constantly fortify confidence in the socialist path, theory, system and culture, continuously enhance the discourse power of China’s economics in global economic governance system, so as to push forward to the building of a theoretical system of socialist economics with Chinese Characteristics in the new era.

Economics is a discipline that studies resource allocation and human’s behavior of making a choice based on rationality. Emerged in the industrial revolution and developed in the exploration of a large-scale socialized mode of production and resource allocation system, this discipline has gradually become a broadly explanatory force in social sciences which profoundly affects the economic decision-making behaviors of the government and various economic entities.

Based on the context of the Internet of Things (IoT), the territorial public emergency supplies will be networked, platform-based management, unified emergency dispatch. The problem of supplies dispatching in the “last kilometer” of emergency is solved, and the supplies needed in the disaster area are promptly delivered to the hands of the victims so that they can quickly be rescued after the disaster and to save valuable time for rapid rescue, which can greatly decrease casualties and property losses. This paper aims to discuss these issues.

By analyzing the shortage of existing emergency supplies dispatching research and taking all factors such as disaster area demand, social reserve, road conditions, mode of transport, loading limit, disaster area satisfaction rate and road capacity into consideration under the background of IoT, a variety of the territorial emergency supplies dispatching model with more rescue points, more affected areas are constructed. The objective function of the model is to aim in finding the shortest rescue time, giving the solution algorithm, and finally simulating the simulation case.

Based on the context of the IoT, the territorial public emergency supplies will be networked, platform-based management, unified emergency dispatch. Considering factors such as road conditions, modes of transport and road capacity, the authors construct a number of emergency rescue plans, multiple disaster scenarios and various emergency supplies dispatching models. The authors simulate the situation through simulation cases with the shortest time being the ultimate goal. The problem of supplies dispatching in the “last kilometer” of emergency is solved, and the supplies needed in the disaster area are promptly delivered to the hands of the victims so that they can quickly be rescued after the disaster and to save valuable time for rapid rescue, which can greatly decrease casualties and property losses.

This paper provides little research on the dispatch of emergency supplies. The problems of direct dispatch from the rescue point to the affected area and dispatch of supplies without relying on the arrival of emergency supplies at the rear are addressed. Therefore, this study does not focus on the arrival of emergency supplies at the rear but on direct dispatching issues during territorial public emergency supplies from the rescue point to the disaster point.

The construction industry is an industry with a high incidence of safety accidents, and the interactions of unsafe behaviors of construction workers are the main cause of accidents. The neglect of the interactions may lead to serious underestimation of safety risks. This research aims to analyze the cascading vulnerability of unsafe behaviors of construction workers from the perspective of network modeling.

An unsafe behavior network of construction workers and a cascading vulnerability analysis model were established based on 296 actual accident cases. The cascading vulnerability of each unsafe behavior was analyzed based on the degree attack strategy.

Complex network with 85 unsafe behavior nodes is established based on the collected accidents in total. The results showed that storing in improper location, does not wear a safety helmet, working with illness and working after drinking are unsafe behaviors with high cascading vulnerability. Coupling analysis revealed that differentiated management strategies of unsafe behaviors should be applied. Besides, more focus should be put on high cascading vulnerability behaviors.

This research proposed a method to construct the cascading failure model of unsafe behavior for individual construction workers. The key parameters of the cascading failure model of unsafe behaviors of construction workers were determined, which could provide a reference for the research of cascading failure of unsafe behaviors. Additionally, a dynamic vulnerability research framework based on complex network theory was proposed to analyze the cascading vulnerability of unsafe behaviors. The research synthesized the results of dynamic and static analysis and found the key control nodes to systematically control unsafe construction behaviors.

Effective construction safety training has been considered to play a significant role in reducing the incidence of accidents. However, the current safety training methods pay less attention to the relationship between workers' personalized characteristics and their learning needs, which results in workers' low learning participation and poor training effect. The purpose of this paper is to improve the participation and effect of safety training for construction workers with a persona-based approach.

This paper presents a persona-based approach to safety tag generation and training material recommendation. By extracting the demographic characteristics and behavior patterns tags of construction workers, a neural network algorithm is introduced to calculate the learning needs tags of workers, and the collaborative filtering recommendation method is integrated to enrich the innovation of recommendation results. Offline experiments and online experiments are designed to verify the rationality of the proposed method.

The results show that the learning needs of workers are closely related to their background. The proposed method can effectively improve workers' interest in materials and the training effect compared with conventional safety training methods. The research provides a theoretical and practical reference for promoting active safety management and achieving worker-centered safety management.

First, a persona-based approach is introduced to establish a novel framework for solving the problem of personalized construction safety management. Second, an artificial intelligence algorithm is used to automatically extract the learning needs tag values and design a hybrid recommendation method for construction workers' personalized safety training. The collaborative filtering method is integrated to enrich the innovation of recommendation results.