Cancellation penalties for ride-sourcing orders considering passengers'rational inattention
Analyzing passengers'order cancellation behavior and formulating appropriate penalty strategies are crucial issues in optimizing the operations of ride-sourcing companies.This study in-vestigates the order cancellation behavior of passengers and the penalty strategies employed by com-panies in the coexisting market of ride-sourcing and taxi servicesbased on the theory of rational inat-tention.In contrast to existing assumptions of perfect information or complete lack of information,this study considers passengers'autonomous selection of information strategies and decisionmaking based on the acquired information,thereby establishing a two-level optimization model.At the upper level of the model,the optimization objectives of maximizing company profits and social welfare are separately pursued to determine the penalty amount for order cancellations.At the lower level,a user decision-making model based on the theory of rational inattention is constructed,and the characteris-tics of three penalty strategies,namely the fixed fee,segmented,and time-based penalties,are com-pared.The model is solved using a combination of the particle swarm optimization algorithm and the method of successive averages.The research findings indicate that reducing the cost of information acquisition can potentially lead to a maximum reduction of 8%in individual travelers'costs and a maximum increase of 40%in the probability of making the right decision.Furthermore,as the cost of information acquisition increases,optimal company profits and social welfare decrease by 16.8%and 5.1%,respectively.Under the objective of optimizing company profits and social welfare,the three penalty strategies exhibit negligible differences.However,when maximizing company profits,the penalty amount is significantly higher than that under the objective of optimizing social welfare,resulting in a lower order cancellation rate.The study provides valuable insights and practical impli-cations for ride-sourcing companies in formulating penalty strategies.