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Metrics details. The progress of microtransit services across the world has been slower than expected due to institutional, operational, and financial barriers. However, how users' ride experiences and system attributes affects their future ride decisions remain an important issue for successful deployment. The results indicate that the proposed Bayesian network approach could reveal a plausible causal relationship between different dependent factors compared to the classical multinomial logit modeling approach.
By examining public transport coverage in the study area, we find that Kussbus complements the existing public transport and provides an effective alternative to personal car use. In past decades, an increasing number of transport network companies and public transport authorities have offered a spectrum of on-demand mobility services [ 1 ]. Despite numerous pilot studies, recent years have seen mixed results.
Some operations such as Kutsusplus in Helsinki and Bridj in Boston failed to achieve financial sustainability [ 2 , 3 ]. There is a need to learn from past experiences to improve business models [ 3 ]. Existing studies mainly focus on the evaluation of the impacts of microtransit services on transport systems, based on either simulation [ 4 , 5 ] or post-evaluation [ 6 , 7 ].
An empirical study is conducted based on a recent microtransit service, Kussbus, operating in the cross-border areas of Luxembourg in The contributions of this study are threefold. First, we present the system characteristics of Kussbus and analyze its system performance.
To understand how competitive the Kussbus service is, we compare it with alternative transport modes and illustrate the inconvenience of using public transport for commuters. While Kussbus ridership increased during the study period, the service was discontinued in early The considered features include spatial-effect factors i. Finally, we draw insights and discuss the findings of this study. The remainder of this study is organized as follows.