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The impact of COVID-19 is global, and uncertain information will affect product quality and worker efficiency in the complex supply chain network, thus bringing risks. Aiming at individual heterogeneity, a partial mapping double-layer hypernetwork model is constructed to study the supply chain risk diffusion under uncertain information. Here, we explore the risk diffusion dynamics, drawing on epidemiology, and establish an SPIR (Susceptible-Potential-Infected-Recovered) model to simulate the risk diffusion process. The node represents the enterprise, and hyperedge represents the cooperation among enterprises. The microscopic Markov chain approach (MMCA) is used to prove the theory. Network dynamic evolution includes two removal strategies: (i) removing aging nodes; (ii) removing key nodes. Using Matlab to simulate the model, we found that it is more conducive to market stability to eliminate outdated enterprises than to control key enterprises during risk diffusion. The risk diffusion scale is related to interlayer mapping. Increasing the upper layer mapping rate to strengthen the efforts of official media to issue authoritative information will reduce the infected enterprise number. Reducing the lower layer mapping rate will reduce the misled enterprise number, thereby weakening the efficiency of risk infection. The model is helpful for understanding the risk diffusion characteristics and the importance of online information, and it has guiding significance for supply chain management.
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People's health is a necessary condition for the country's prosperity. Under the background of the COVID-19 pandemic and frequent natural disasters, exploring the spatial and temporal distribution, regional differences and convergence of China's provincial public health level is of great significance to promoting the coordinated development of China's regional public health and achieving the strategic goal of a "healthy China". Based on China's provincial panel data from 2009 to 2020, this paper constructs an evaluation index system for China's public health level from five dimensions: the popularization of a healthy life, optimization of health services, improvement of health insurance, construction of a healthy environment, and development of a health industry. In this paper, the entropy method, Dagum Gini coefficient, Kernel density function and spatial econometric model are used to analyze the spatiotemporal distribution, regional differences, dynamic evolution and convergence of China's public health level since the new medical reform. The study found that, first, China's public health level is generally low, structural contradictions are prominent and the construction of a healthy environment has become a shortcoming hindering the improvement of China's public health level since the new medical reform. The public health level of the four major regions showed a spatial distribution pattern of "high in the eastern, low in the northeastern, central and western" areas. Second, the overall Gini coefficient of China's public health level showed a "V-shaped" trend of first decreasing and then rising, but the overall decrease was greater than the increase, among which the regional difference was the main source of regional differences in China's public health level, but its contribution rate showed a downward trend. Third, except for the basic maintenance of a healthy environment, the Kernel density curves of China's public health level and its sub-dimensions have shifted to the right to a certain extent, and there is no polarization phenomenon. Finally, the level of public health in China has a significant spatial correlation. Except for the northeast region, the growth rate of low-level public health provinces in China and the other three major regions is higher than that of high-level public health provinces, showing a certain convergence trend. In addition, the impact of economic development, financial pressure, and urbanization on the convergence of public health levels in the four major regions is significantly heterogeneous.
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COVID-19 pandemic has paused many ongoing research projects and unified researchers' attention to focus on COVID-19 related issues. Our project traces 712,294 scientists' publications related to COVID-19 for two years, from January 2020 to December 2021, in order to detect the dynamic evolution patterns of COVID-19 collaboration network over time. By studying the collaboration network of COVID-19 scientists, we observe how a new scientific community has been built in preparation for a sudden shock. The number of newcomers grows incrementally, and the connectivity of the collaboration network shifts from loose to tight promptly. Even though every scientist has an equal opportunity to start a study, collaboration disparity still exists. Following the scale-free distribution, only a few top authors are highly connected with other authors. These top authors are more likely to attract newcomers and work with each other. As the collaboration network evolves, the increase rate in the probability of attracting newcomers for authors with higher degree increases, whereas the increase rates in the probability of forming new links among authors with higher degree decreases. This highlights the interesting trend that COVID pandemic alters the research collaboration trends that star scientists are starting to collaborate more with newcomers, but less with existing collaborators, which, in certain way, reduces the collaboration disparity. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
COVID-19 pandemic has paused many ongoing research projects and unified researchers' attention to focus on COVID-19 related issues. Our project traces 712,294 scientists' publications related to COVID-19 for two years, from January 2020 to December 2021, in order to detect the dynamic evolution patterns of COVID-19 collaboration network over time. By studying the collaboration network of COVID-19 scientists, we observe how a new scientific community has been built in preparation for a sudden shock. The number of newcomers grows incrementally, and the connectivity of the collaboration network shifts from loose to tight promptly. Even though every scientist has an equal opportunity to start a study, collaboration disparity still exists. Following the scale-free distribution, only a few top authors are highly connected with other authors. These top authors are more likely to attract newcomers and work with each other. As the collaboration network evolves, the increase rate in the probability of attracting newcomers for authors with higher degree increases, whereas the increase rates in the probability of forming new links among authors with higher degree decreases. This highlights the interesting trend that COVID pandemic alters the research collaboration trends that star scientists are starting to collaborate more with newcomers, but less with existing collaborators, which, in certain way, reduces the collaboration disparity. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
In this paper, an analysis of changes in dynamic process models described by variables that represent social behavior from the point of view of people's mobility and of economic indices in the framework of the COVID19 pandemic is presented. Here, the mobility described by Google and Apple is used as a proxy for the social behavior to correlate it with the dynamic evolution of daily COVID19 infections. In addition, indices related from the global economy are used as a proxy of the socio-economic process, where two of ascending evolution (MSFT Microsoft and NASDAQ, Inc.) and another with smooth evolution (WTI oil gallon price) are analyzed. The evolution of such proxies are related to the daily COVID19 cases. In the latter case, it is difficult to detect a territorial region of influence given the number of origins of influences that the selected indices have, but the impact of the first peak in China and the subsequent evolution in the world can be studied, especially in our country and in the Netherlands. The main findings include that the underlying model for social behavior has changed in different stages, depending on the months of the year and that after mid-2021 an unstable equilibrium is on the track, with the addition of the new possibilities provided by the vaccination process and the rules of social coexistence. It is concluded that it is necessary to analyze which decision should be taken at the social level of public policy and which personal decisions for each individual. © 2021 IEEE.
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The emergence of digital technologies has profoundly affected and transformed almost every aspect of societal relations. These impacts have also reached public administration, including its governance. Digital technologies’ rise has paved the way for the surfacing of a new public governance model called the Digital Era Governance (DEG) model (often referred to as e-government, digital government, e-governance, or digital governance) in which digital technologies play a central role. Therefore, the main aim of this paper is to provide a comprehensive and in-depth examination of DEG research over the past two decades. Bibliometric analysis is based on the Scopus database that contains 9175 documents published between 2001 and 2020. In this context, several established and innovative bibliometric approaches are applied. The results reveal the growth of DEG research over the last two decades, especially in recent years, as accelerated by several of the most relevant documents published in reputable journals such as Government Information Quarterly. Most DEG research has been conducted in Anglo-Saxon countries, as confirmed while examining the most relevant authors’ affiliations and collaborations. The results also indicate that DEG has advanced from conventional public services to citizen-oriented e-services by including citizens’ participation and, most recently, even to smart services by facilitating emerging and disruptive technologies. The findings add to the stock of scientific knowledge and support the evidence-based policymaking needed to successfully pursue a sustainable future.
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Purpose This study aims to investigate the basic public service level in the Beijing-Tianjin-Hebei region under the impact of COVID-19. Design/methodology/approach This study constructed a basic public service-level evaluation system from the five dimensions of education, culture, health, social security and infrastructure and environment, and measures the basic public service level in 13 cities in Beijing, Tianjin and Hebei using the entropy method. The spatial pattern and dynamic evolution of the public service level are analysed from the perspective of dynamic trends in time series and spatial distribution, along with the reasons for the evolution of spatial distribution. Findings (1) The basic public service level in the 13 cities is generally on the rise, but the trend is unstable. (2) The basic public service level in space shows a general trend of attenuation from northeast to southwest, with significant spatial imbalance and orientation. (3) The regional differences first increase and then decrease. (4) The inter-group mobility of different basic public service levels is low, and cities with lower initial levels find it difficult to achieve leapfrog development. Moreover, the health service level of the region is still at a low stage, which is not conducive to effectively preventing and controlling the epidemic. Originality/value From the perspective of this research, the spatial pattern and dynamic evolution of basic public service were adopted to analyse the coordinated development of the Beijing-Tianjin-Hebei region. Furthermore, this study discusses how to improve the basic public service level to ensure sustainable operation in the region under the impact of COVID-19.
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This work constructs an evaluation index system and quantitatively explores the coupling coordination relationship between the tourism development system and the medical services system in China. Results show that the degree of coupling coordination between the tourism development system and the medical services system showed a good upward trend in China during the period 2012-2019. However, the relationship was barely balanced, with tourism development lagging. The overall layout shows a spatial pattern of "high in the north and low in the south, high in the east and low in the west." The degree of coupling coordination tends to be randomly distributed from clustered distribution, and the cold-hot spots show a spatial development pattern of "cold in the northwest and hot in the southeast" as time passes. The power of government to regulate has always been an important mechanism affecting the degree of coupling coordination. The study aims to provide reference for the rationalization of medical tourism layout and sustainable development.
Subject(s)
Economic Development , China , Government , Humans , TourismABSTRACT
Compound disasters are highly complex and can involve different types of disasters. Since the beginning of the COVID-19 pandemic, compound disasters of public health emergencies, accident disasters, and natural hazards have occurred frequently all over the world; therefore, it is important to establish effective compound disaster emergency collaboration networks. Thus, this study examined the 7 March building collapse in Quanzhou City as a case study. This case was a typical compound disaster involving a public health emergency and an accident disaster during COVID-19. Based on the network analysis, the overall response and dynamic characteristics of the emergency collaboration for compound disasters were examined in this study. A compound disaster emergency collaboration network (ECN) was constructed by identifying the interactional relationships between emergency organizations. After applying time slices, the dynamic evolution of network structure, organizational-functional relations, organizational attributes, and cross-organizational relationships were discussed. The research results showed the following: (1) The density and connectivity of the compound disaster ECN first decreased before increasing. Meanwhile, the evolution of the network structure followed a path from decentralized to concentrated and from being uneven to an equilibrium. (2) The characteristics and practices of compound disasters during different periods indicated varied emergency needs for emergency organizations. We found that the formation of emergency tasks not only involved the passive adaptation to match the practice for compound disasters, but also the active choices of emergency organizations when facing compound disasters according to their collective experiences and decisions. (3) The national emergency management departments, the government emergency rescue organizations, and the local governments were the core organizations of the ECN. Public health management departments and social organizations were also required to participate in the ECN to improve the diverse and heterogeneous distribution of resources. (4) With increased demands during a compound disaster emergency, the number of cross-organizational collaborative relationships gradually increased. This study explored compound disaster emergencies from the perspective of network analysis to improve our understanding of the current and developing organizational relationships and practices during a compound disaster event. The dynamic characteristics of compound disasters require efficient adaptation and improvements of the collaborative mechanisms involved during emergencies.
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Public health emergencies, especially major infectious diseases, may cause global crises. Timely and effective communication is essential for response to such incidents. However, the emergency response to such incidents usually lasts longer and break out repeatedly, and the existing static emergency communication network (ECN) analysis cannot fully reflect the dynamic information interaction between organizations during the emergency process. Therefore, this article takes the recent COVID-19 epidemic in Hubei, China as a case, and uses social network analysis to reveal the dynamic evolution of communication networks, positions, roles, and tasks of organizations from the time dimension. The results show that: (1) the ECN has changed from concentrated to decentralized over time; (2) the positions and roles of participating organizations in the ECN has changed, but there are still a few key organizations that at the central position in all phases of emergency communication; (3) the core tasks have changed due to emergency needs at each stage; (4) under the concentrated management system, the core organization of the ECN mainly comes from government organizations. The research results reveal the dynamic evolution of communication networks between different types of emergency organizations, which is beneficial to guide emergency management of public health emergencies. In actual emergency, the emergency communication mode should be dynamically adjusted based on the characteristics of the emergency situation at different stages, comprehensively using the advantages of the concentrated and decentralized emergency network. In addition, communication between different types of organizations such as governments, research institutions, and enterprises should be strengthened, and channels for diversified organizations to participate in emergency communication should be set up. The research helps to improve communication between emergency response organizations and is of great significance to controlling and reducing the harm caused by public health emergencies.