Evolutionary Game of Social Network for Emergency Mobilization (SNEM) of Magnitude Emergencies: Evidence from China

Abstract

As a common social network, the SNEM plays an important role in emergency management. Magnitude emergencies are characterized by high complexity and uncertainty, and it is impossible to rely on the government for emergency management alone. We should absorb multiple subjects to build the SNEM and carry out extensive emergency mobilization in the whole society. The SNEM can integrate resources, gather consensus, promote participation, and reduce risks. The analysis of the types, generation mechanism, subject behavior, and strategy selection of the SNEM aid in adopting appropriate mobilization strategy based on magnitude emergencies, achieving the adaptation of the SNEM and emergency scenarios. By constructing the evolutionary game model of the SNEM for magnitude emergencies, taking China as an empirical sample, this paper explores the behavior evolution law and stable strategy of the government, social organizations, and the public. The results showed that the symbiotic SNEM with a positive response of social organizations and the public under the path of high-intensity mobilization by the government is the best strategy combination, and it is conducive to maximizing the emergency joint force.

Asymmetric evolutionary game analysis of emergency cooperative social networks for magnitude emergencies: Evidence from the Beijing-Tianjin-Hebei region in China

“…The ECSNs is a dynamic structure formed by formal and informal cooperation between organizations of different types and scales in the context of crisis management [4,5] having a positive role in promoting the sharing of information, financial resources and human capital, which is conducive to the improvement of emergency management efficiency [6].…”

“…This asymmetry is manifested in resource endowment, administrative level, geographical proximity, degree of disaster impact and other aspects [9][10][11][12][13][14][15]. If there is a serious asymmetry between network actors, the stronger party will take the initiative, and occupy the central position of the network and control network resources, while the weaker party will find it is difficult to participate effectively, leading to a crisis of confidence or void contract [6]. Moreover, the actors in the ECSNs are interconnected, which makes them vulnerable to each other's strategic behaviors [16].…”

“…Therefore, vertical control by higher levels of governments helps to build trust and respect among local government entities at all levels and foster cooperative networks [19]. Second, in the theoretical framework proposed by Ansell and Gash (2007) [6], they point out that when the distribution of power is asymmetric or the motivation to participate is weak, the success of cooperative governance requires leadership control. This proposition implies that vertical control is critical to social networks.…”

Evolutionary game analysis of multiple subjects in the management of major public health emergencies

“…Other scholars focused on the relationships between governments, enterprises, and consumers, creating three-way evolutionary game models to determine whether the penalty mechanism is more effective than the subsidy mechanism in achieving the COVID-19 joint prevention goal [ 29 ]. Some researchers have explored the links between government, social organisations and the public to explore the evolutionary game of the emergency social mobilisation network for major emergencies [ 30 ].…”

Emergency Decision‐making Method of Unconventional Emergencies in Higher Education Based on Intensive Learning

“…Because non-quantitative management is highly subjective, random, and unreliable, managers often evaluate, make decisions and manage through experience, which easily leads to decision-making mistakes and hidden problems [ 2 ]. Compared with non-quantitative management, quantitative management can more effectively digitize the resources required by the emergency response capability, mine the information through mathematical tools, and obtain more objective quantitative results, which can be applied to the planning, organization, coordination, and control of the emergency response process of unconventional emergencies in higher education [ 3 ].…”