An integrated interval-valued intuitionistic fuzzy technique for resumption risk assessment amid COVID-19 prevention.

Currently, China has achieved a remarkable achievement on the containment of COVID-19, which creates a favorable condition for the gradual resumption of normal life. However, COVID-19 infections continue to rise in many nations and some sporadic cases occur from time to time in China, which still poses some risks to the resumption. Hence, it is imperative to develop some reasonable techniques to assess the resumption risk. This paper aims to investigate an integrated interval-valued intuitionistic fuzzy (IVIF) technique to adroitly assess the resumption risk based on DEMATEL (decision making trial and evaluation laboratory), BWM (best-worst method) and SPA (set pair analysis). This integrated technique is called IVIF-DBWM-SPA, where the IVIF-DBWM (combined by the IVIF-DEMATEL and IVIF-BWM) is used to determine the global criteria weights and the IVIF-SPA is employed to generate the ranking order of the alternatives. The IVIF-DEMATEL and IVIF-BWM are used to determine the weights of dimensions and the weights of criteria under each dimension, respectively. In this IVIF-BWM, two bi-objective programming models are constructed by regarding experts' pessimistic and optimistic attitudes, respectively. Combined experts' intrapersonal and interpersonal uncertainties simultaneously, a bi-objective programming model is proposed to derive the dynamic weights of experts. Based on the determined weights of experts and criteria, an IVIF-SPA is developed to assess the risk levels of all alternatives. The validity of the proposed technique is demonstrated with a real case of college resumption risk assessment amid COVID-19. Some sensitivity and comparison analyses are provided to show the merits of the proposed technique.

A study on the evolution of economic patterns and urban network system in Guangdong-Hong Kong-Macao greater bay area.

The COVID-19 pandemic has seriously affected China's macroeconomy, industrial transformation, and high-quality development. Research on economic patterns and urban network systems can provide a reference for healthy development of the regional economic system. The evolution of the economic pattern and urban network system of Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 2010 to 2020 is investigated using methods (e.g., the gravity center model, the gravitational force model, social network analysis, and geographic information system). (1) The gravity center of gross domestic product (GDP) of the GBA is located in Nansha district, Guangzhou, with a skewing direction northwest-east-northwest and a movement rate of "large-small-large." The center of import and export and the center of consumption show a "zigzagging migration" in which the center of investment shows an "irregular (random) migration". (2) The economic connection degree of cities in the GBA exhibits a high ascending velocity, and the whole area tends to be mature, with a significant effect of spatial proximity. With the steady increase in network density, there is significant polarization of network centrality in the region. The four major cohesive subgroups have been relatively stable and consistent with the degree of geographic proximity of the cities. The center-periphery structure is more significant, in which the core area is extended to the cities on the east coast of the Pearl River Estuary, thus forming the core cluster of "Hong Kong-Shenzhen-Guangzhou-Dongguan." In this study, the evolution of economic patterns and urban network systems in the GBA over the past decade is analyzed using multiple methods (i.e., gravity model, urban network system analysis, and geographic information system) based on urban socioeconomic data by starting from various spatial elements (e.g., "points, lines, and networks") to gain insights into and optimize research on regional economic development after the COVID-19 pandemic.

Analysis of Spatio-Temporal Characteristics of Urban Economic Resilience and Influencing Factors in Guangdong-Hong Kong-Macao Greater Bay Area.

Due to the changes in the domestic and international economic situation in the post-pandemic era, the economic development of the Guangdong-Hong Kong-Macao Greater Bay Area has become unstable in many aspects. The paper adopted the Pressure-State-Response (PSR) model to build a regional economic resilience evaluation system from the perspective of public health emergencies. Then, the spatial and temporal evolution of the economic resilience of the Guangdong-Hong Kong-Macao Greater Bay Area and the influencing factors were explored by using entropy weight method, GIS and gray correlation method. The conclusions show that: (1) Temporally, the economic resilience of the Guangdong-Hong Kong-Macao Greater Bay Area has generally increased from 2010 to 2021, and is divided into three main stages: rapid development, adjustment to fluctuations and stable development. (2) Spatially, the overall pattern of economic resilience in the Guangdong-Hong Kong-Macao Greater Bay Area is high in the middle and south and low in the northwest, and shows a "stochastic-equalized-polarized" pattern of transformation. (3) In terms of influencing factors, economic status and economic response are the main dimensions affecting the resilience level of the economic system in the Guangdong-Hong Kong-Macao region. The level of scientific research and innovation, medical governance, government regulation and the rationalization of the industrial system are the key factors.