Resilience-oriented passenger subsidy design for taxi travel under pandemic control - Lei Xia; Zhengfeng Huang; Gao Gao; Pengjun Zheng (EPJ Data Science)
Abstract Summarizing historical pandemic control experience can help the government better cope with the impact of uncertain public health events on taxi industry. This paper presents a summary of the relationship between various pandemic control measures and taxi system from the perspective of travel resilience. Additionally, we investigate the effectiveness of passenger subsidy schemes in improving the taxi travel resilience. To achieve these objectives, our research follows these steps: Firstly, we analyze the impact of different pandemic control measures on the performance variation curves of the taxi travel system. Secondly, using the travel resilience calculation formula, we evaluate the taxi travel resilience levels under different pandemic control measures and analyze other factors (such as virus characteristics) on taxi travel resilience through regression models. Finally, we construct a taxi travel resilience improvement model. Aiming at maximizing the social benefits which consider taxi travel resilience, we search for the optimal passenger subsidy result. And then make a comparison for two distinct subsidy types: fixed-amount and fare subsidy rate. Taking Ningbo city, China as a case study, the research findings demonstrate: (1) The ranking order of each pandemic control measure based on taxi travel resilience performance from low to high are as follows: city-wide lockdown control measure, district-wide lockdown control measure, targeted epidemic control measure, and fully lifted control measure. These findings suggest that a reduction in the scope and duration of pandemic control measures can maintain a high level of taxi travel resilience. (2) In addition to pandemic control measures, the virus’s incubation period and infectivity have a significant impact on travel resilience. (3) Model results show that increasing passenger subsidies can quickly improve taxi travel resilience, but it cannot guarantee a consistent increase in social benefits. When the weight of travel resilience in the objective function is small, social benefits will initially increase and then decrease with higher passenger subsidy amounts. In such cases, the extreme value method can help determine the optimal passenger subsidy amount. (4) When decision-makers focus on improving taxi travel resilience, they can adopt the fixed amount subsidy scheme. When the focus is on maximizing social benefits, the fare subsidy rate scheme should be chosen.