A user-operator assignment game with heterogeneous user groups for empirical evaluation of a microtransit service in Luxembourg

TL;DR

This paper introduces a stochastic stable matching model to empirically evaluate microtransit service policies, revealing that cost reductions and travel time improvements can significantly boost ridership and profit.

Contribution

It extends the stable matching framework to account for user heterogeneity and applies it to real microtransit data for the first time.

Findings

Reducing route costs by 50% can increase ridership by 10%.

Reducing in-vehicle travel time by 20% can significantly increase profit.

Current operation is not a stable outcome under the model.

Abstract

We tackle the problem of evaluating the impact of different operation policies on the performance of a microtransit service. This study is the first empirical application using the stable matching modeling framework to evaluate different operation cost allocation and pricing mechanisms on microtransit service. We extend the deterministic stable matching model to a stochastic reliability-based one to consider user's heterogeneous perceptions of utility on the service routes. The proposed model is applied to the evaluation of Kussbus microtransit service in Luxembourg. We found that the current Kussbus operation is not a stable outcome. By reducing their route operating costs of 50%, it is expected to increase the ridership of 10%. If Kussbus can reduce in-vehicle travel time on their own by 20%, they can significantly increase profit several folds from the baseline.