Analysis of a tripartite evolutionary game model of food delivery platform supervision and strategy selection

The advances of technological development prompted the formation of new business models, and the changes in people's lifestyles and eating habits have driven the rapid emergence of online food delivery platforms. Food delivery orders have been increasing along with consumer disputes. To reduce these disputes and enable relevant participants to actively supervise, report, and comply with rules to maintain the operation of the delivery platforms, this study constructs a tripartite evolutionary game model consisting of platforms, restaurants, and consumers, based on the assumption of participants' bounded rationality and their expected benefits, and analyzes the main factors that determine the best strategy. Concurrently, the evolutionary paths and equilibrium states among the three groups are explored through numerical simulation analysis, and attempts are made to reduce the possibility of delivery platform issues through mutual restraint and cooperation. The results of the study demonstrate that platforms should impose severe penalties on restaurants that violate the regulations; the reduction of incentive value will make platforms more inclined to choose a supervision strategy. The platforms should adopt a supervision strategy if their supervision costs plus incentive expenses minus penalty revenues are lower than the negative social evaluations caused by lack of supervision by platforms.

Automated summary

This study constructs a tripartite evolutionary game model to analyze how online food delivery platforms can reduce consumer disputes and improve the interaction between platforms, restaurants, and consumers. The study suggests that platforms should impose severe penalties on violating restaurants and can reduce platform issues through mutual restraint and cooperation.