The Impact of Cooperative Behavior between Social Organizations during the Covid-19 Pandemic Outbreak in Shanghai
A Simulation Approach
Bibliographic Data
| ID | 15460688 |
|---|---|
| Authors | Weipeng Fang (Tongji University), Changwei Qin (0000-0003-4919-4662, Tongji University), Dan Zhou (0000-0001-8678-8270, Tongji University), Jian Yin (0000-0003-1203-5537, Tongji University), Zhongmin Liu (0000-0002-7999-2940, Tongji University, corresponding author), Xianjun Guan (Tongji University, corresponding author) |
| Year | 2023 |
| Volume | 20 |
| Issue | 2 |
| Pages | 1409-1409 |
| Publication date | 2023-01-12 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph20021409 |
| PMID | 36674165 |
| OpenAlex | W4315701828 |
| Language | EN |
| References cited | 20 |
In 2022, a new outbreak of the COVID-19 pandemic created considerable challenges for the Shanghai public health system. However, conventional prevention and control strategies, which only rely on formal organizations, inefficiently decrease the number of infections. Thus, a multi-organization management mode is needed for pandemic prevention. In this paper, we applied a stochastic actor-oriented model (SAOM) to analyze how these social organizations cooperate with others and further identify the mechanism that drives them to create a reliable and sustainable cooperative relationship network from the perspective of social network analysis. The model allowed us to assess the effects of the actor’s attributes, the network structure, and dynamic cooperative behavior in RSiena with longitudinal data collected from 220 participants in 19 social organizations. The results indicated that the number of cooperative relationships increased during the pandemic, from 44 to 162, which means the network between social organizations became more reliable. Furthermore, all the hypotheses set in four sub-models were significant (t-ratio 2). Additionally, the estimated values showed that four factors played a positive role in forming the cooperative relationship network, i.e., all except the “same age group effect (−1.02)”. The results also indicated that the social organizations tend to build relationships with more active actors in the community in every time period. This paper is of great significance regarding the innovation of public health system management and the improvement of Chinese grassroots governance
Business · Control (management · Coronavirus disease 2019 (COVID-19 · Corporate governance · Economics · Grassroots · Management · Outbreak · Pandemic · Political science · Public health · Public relations · Set (abstract data type · Social media · Social network (sociolinguistics · Social network analysis · Structural equation modeling · Complex Network Analysis Techniques · Computer Science · COVID-19 epidemiological studies · Medicine · Mental Health Research Topics
Five Rules for the Evolution of Cooperation
The way bullying works
Introduction to stochastic actor-based models for network dynamics
Factors That Affect the Covid-19 Pandemic in Summer 2022 Compared to Summer 2021
Straining but not thriving
Network relationships and standard adoption
Modeling Diffusion through Statistical Network Analysis
The Statistical Evaluation of Social Network Dynamics
Stochastic actor-oriented models for network change
International Students' Cross-Cultural Adjustment
| Citation velocity | historical |
|---|---|
| Highly cited | No |