Measuring systemic risk of Greek banks: New approach by using the epidemic model “SEIR”

Derbali, Abdelkader; Hallara, Slaheddine

doi:10.1080/23311975.2016.1153864

Cited by 12 publications

(6 citation statements)

References 22 publications

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“…Many diffusion phenomena in human systems are analogous to the social contagion processes of infectious diseases, including word of mouth, imitation, and network externalities. From the diffusion of new products to the spread of rumors and financial panics, to the dynamics of infectious diseases and their formal models, there is a rich history in the social sciences [21][22][23][24]. In recent years, researchers have used dynamic models to study the diffusion of new products.…”

Section: Dynamic Model Of New Product Diffusionmentioning

confidence: 99%

Nonlinear Dynamic Analysis of New Product Diffusion considering Consumer Heterogeneity

Tang

Zhu

2020

Complexity

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When a new product enters the market, individual consumers’ decision-making behavior and purchase time are uncertain. Based on the dynamics of epidemic transmission theory and agent modeling technology, this study proposes a new coupling model through the combination of the improved SEIR epidemic model and the heterogeneous agent model. This model considers consumer heterogeneity resulting from three aspects in consumers’ sensitivity, network topology, and considerations of information flow received. It aims to analyze how consumer heterogeneity affects the scale and speed of new product diffusion. The proposed model showed that consumers’ characteristics and behavior combination at the microlevel lead to the diversity of nonlinear diffusion curves at the macrolevel for new products. Moreover, a pilot study is conducted to simulate this model and examine how to estimate the model’s parameters using aggregated data about film products. The pilot study results suggested that different consumer characteristics and behavior combinations affect the scale and speed of new product diffusion to varying degrees. In different scenarios, there were significant differences in the influence of the degree of consumer heterogeneity on diffusion, accompanied by the occurrence of threshold. The results of the empirical analysis in this study are in line with reality.

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Section: Dynamic Model Of New Product Diffusionmentioning

confidence: 99%

Nonlinear Dynamic Analysis of New Product Diffusion considering Consumer Heterogeneity

Tang

Zhu

2020

Complexity

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“…The current epidemic model that is based on a complex network is not only limited to the study of virus transmission but also widely used in the field of social science [35][36][37], such as technology and innovation diffusion [38], financial crisis contagion [39,40], and the spread of rumors [41,42]. The epidemic model provides the necessary technological means for solving social problems, and it also offers theoretical basis for devising coupling strategies.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Diffusion Evolution Model of Unethical Behavior among Green Food Enterprise

et al. 2022

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Under the background of low-carbon economy, the unethical behavior of green food enterprises has aggravated the uncertainty and frequency of green food safety problems and even triggered a contagion of unethical behavior among green food enterprises. In view of this, considering the characteristics of organizational behavior, external environmental intervention and social networks, we construct an infectious disease model of the nonlinear spread of unethical behavior in green food enterprises and simulated the mechanism and evolution characteristics of the spread of unethical behavior among them. The main conclusions are as follows. (1) Single adjustment of the level of enterprise moral clarity, damage degree of unethical behavior, and enterprise influence can only reduce the diffusion probability of unethical behavior to a certain extent. (2) Enterprise ethical climate plays a crucial role in the diffusion of unethical behavior among green food enterprises and exerts a “strengthening effect” on other organizational behavior and external environmental intervention factors. (3) The strength of external supervision and strength of punishment exert a “suppression effect” on the diffusion of unethical behavior among green food enterprises.

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“…Some scholars focus on common problems in life, such as alcoholism, to analyze the causes of these social phenomena through the transmission dynamics model and find solutions [7]. Such above transmission dynamics models have also been introduced into the field of economy and finance; meanwhile, the risk contagion mecha-nism of banks [8][9][10] and the rule of capital flow in the stock market are discussed [11][12]. Cao et al use the SIR model to simulate the risk contagion process of banks by combining knowledge of risk contagion process, bank risk characteristics, and complex network structure.…”

Section: Introductionmentioning

confidence: 99%

Study on the Dynamic Behavior of a Class of Heterogeneous Network Systems With Time Delay

Wang

Cui

2020

IEEE Access

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Successful treatment of COVID-19 that outbroke worldwide since the beginning of 2020 has demonstrated the importance of effective isolation, which is aimed at asymptomatic and symptomatic infected persons in the incubation period. In this paper, to further analyze the transmission dynamics behavior of epidemics with the latent state, we construct a class of health state-latent state-infectionrecovery state (SEIR) infectious disease model with heterogeneity and time delay characteristic based on considering the nonlinear incidence rate formed by psychological inhibition factors. Also, the dynamics of the epidemic, the threshold condition, and stability are studied by creating Lyapunov functions reasonably, applying LaSalle's Invariance Principle and mean-field equation theory. The research shows that, the basic reproduction number R 0 of the system depends on birth rate, death rate, recovery rate, disease transmission rate, and network topology. If R 0 < 1, the system is stable at the disease-free equilibrium point E 0 , and if R 0 > 1, the system is sound at the endemic equilibrium point E *. Moreover, it is also proved that latent delay and psychological inhibitory factors can influence the peak and rate of the infected nodes in the system before their convergence to the equilibrium point, but not the system's global stability. Meanwhile, the theoretical results are verified by numerical simulation finally.

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Measuring systemic risk of Greek banks: New approach by using the epidemic model “SEIR”

Cited by 12 publications

References 22 publications

Nonlinear Dynamic Analysis of New Product Diffusion considering Consumer Heterogeneity

Nonlinear Dynamic Analysis of New Product Diffusion considering Consumer Heterogeneity

Nonlinear Diffusion Evolution Model of Unethical Behavior among Green Food Enterprise

Study on the Dynamic Behavior of a Class of Heterogeneous Network Systems With Time Delay

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