Han Sun

From the executive risk preference–policy uncertainty interaction perspective, this paper constructs a CA-SHIRD model by leveraging complex network theory and cellular automata, and further analyzes the liquidity risk contagion mechanism and dynamic evolutionary characteristics in the high-carbon manufacturing industry. In summary, this paper yields several key findings: (1) An increase in infection probability intensifies liquidity risk contagion, while a higher transition probability mainly accelerates short-term risk exposure. A higher recovery probability mitigates the contagion process and increases the proportion of recovered enterprises, whereas a higher default probability also weakens contagion but leads to a larger proportion of defaulted enterprises. (2) The liquidity risk contagion threshold in the high-carbon manufacturing industry is positively correlated with policy sensitivity, policy target ambiguity, and policy change frequency; negatively correlated with green preference, long-term orientation, and policy coordination; and exhibits a U-shaped relationship with risk perception and an inverted U-shaped relationship with policy instrument predictability. (3) When policy sensitivity interacts with policy change frequency, it exerts a risk resonance effect; when policy target ambiguity interacts with green preference and long-term orientation, a risk hedging effect is generated; when policy change frequency interacts with green preference and long-term orientation, the risk amplification effect of policy change frequency dominates the risk mitigation effect of green preference and long-term orientation.

Employing a space–time perspective, this study develops a CA-SHIRS model of corporate resonance diffusion of food safety risk, drawing on complex network theory and cellular automata theory. The study then examines the mechanisms and spatial–temporal evolution characteristics of this diffusion, considering the interplay among food firm heterogeneity, media communication strategy, and government regulatory strategy. The study reaches the following conclusions: (1) Higher probabilities of infection, conversion, and immune failure speed up risk transmission within the spatial–temporal association network of food firms. By contrast, raising the immune probability and direct immune probability helps contain the scale of risk spread. (2) The intensity of corporate resonance diffusion is positively correlated with corporate influence and media influence, and negatively correlated with corporate social responsibility, media information disclosure intensity, government penalty intensity, and government regulatory information transparency. It exhibits an inverted U-shaped relationship with corporate risk preference and a positive U-shaped relationship with media reporting preference. (3) Both corporate influence and media influence reinforce corporate resonance diffusion, while government regulation effectively mitigates it. Firms with moderate risk preference are most significantly affected by extreme media coverage; corporate social responsibility and media information disclosure intensity can jointly suppress diffusion at these nodes. Government regulation exerts a stronger inhibitory effect on corporate resonance diffusion than the amplifying effect exerted by media communication.

From a space-time perspective, this paper constructs a CA-SHIRS model to study the psychosocial resonance diffusion of food safety risk, using complex network and cellular automata theory. The CA-SHIRS model is a framework that combines cellular automata with SHIRS (Susceptible–Hidden–Infected–Recovered–Susceptible) epidemic modeling. This methodological integration can effectively reflect local interactions and spatial distribution among consumers. Furthermore, this paper analyzes the diffusion mechanism and spatial–temporal evolution of the psychosocial resonance of food safety risk, considering the interaction between consumer heterogeneity and media communication strategies. The primary conclusions are outlined as follows: (1) An increase in infection probability, conversion probability, and immune failure probability causes the psychosocial resonance of food safety risk to spread rapidly across different regions and populations. In contrast, an increase in immune probability helps control the psychosocial resonance of food safety risk. (2) The diffusion threshold of the psychosocial resonance of food safety risk is negatively related to the consumer risk perception level, consumer risk attention, media freedom, and media report authenticity. However, it is positively correlated with consumer sentiment, market noise, and media report tendency. (3) The consumer risk perception level, consumer risk attention, media freedom, and media report authenticity can effectively inhibit the spatial–temporal diffusion of the psychosocial resonance of food safety risk. On the other hand, increases in market noise, consumer sentiment, and media report tendency accelerate the spread of the psychosocial resonance of food safety risk across different regions.