Inequity Aversion Selection Under Revenue-Sharing in a Reservation Commuting Platform for Urban–Rural Agglomerations

The intelligent design of a transportation system management platform offers a compelling solution for optimizing traffic flow in urban–rural agglomerations. While previous studies have concentrated on the technical aspects of addressing transportation challenges in these areas, there has been a paucity of attention paid to the economic dimensions. This study explores the economic viability of such a system by examining the revenue-sharing mechanism. Moreover, it examines the principal cost elements within the construction context and develops a mathematical model based on game theory and considerations of inequity aversion. A case study of the Guangdong–Hong Kong–Macao Greater Bay Area serves to demonstrate the model’s validity. From the perspective of the service provider, it is advantageous for the provider to pursue fairness, or at the very least, to disregard any unfairness, if the owner pursues absolute fairness. In an ideal scenario, where both parties prioritize fairness, optimal or near-optimal solutions can be reached based on their fairness preferences. This approach allows for the maximization of overall benefits without incurring losses. The research findings not only offer guidance to policymakers in the realm of traffic management but also present novel ideas and methodologies for scholarly exploration in related fields.