Quantitative cusp catastrophe model to explore abrupt changes in collaborative regulation behavior of e-commerce platforms

Abstract

Complex interactions and changes in environments make e-commerce platform collaborative regulation (ECPCR) present nonlinear features and radical changes; however, previous research has seldom been conducted from a catastrophe perspective. Accordingly, we develop a quantitative cusp catastrophe model to explore such abrupt changes by combining stochastic evolutionary game, catastrophe theory, and resilience theory. Specifically, a stochastic evolutionary game is utilized to describe the interactions between the government and the platform with the consideration of random disturbance. Then, a cusp catastrophe model is developed to capture the mechanism of sudden changes. With the catastrophe threshold identified, a catastrophe-based resilience measurement method is proposed to quantitatively investigate the catastrophe process, and simulation experiments are conducted to explain and validate the proposed approach. The results show that ECPCR suffers catastrophe (e.g., from nonsupervision to supervision) when the combination of parameters reaches a certain threshold, and the impact of the parameters on catastrophe can be quantified by measuring the resilience of collaborative regulatory systems. In addition, increasing penalty intensity and reputation losses can effectively prevent catastrophe from supervision to nonsupervision, while supervision revenue has little impact. This integrated study provides a new perspective for supervision research and offers ideas for the quantitative analysis of catastrophe.