| Summary: | Disruption recovery is an imperative task for the tram system, which has caused widespread concerns in the public transport area. In this paper, how to provide replacement services for stranded passengers during short-term unplanned events has been investigated. A decision support tool for the tram company to dispatch appropriate replacement services by taxis or buses has been proposed. First, critical factors for disruption recovery decisions are identified as commuters' behaviors, recovery cost, and service level. Then, critical factors are model as replacement service selection strategies among bus, taxi, and bus-taxi hybrid. Finally, numerical analyses are conducted to shed light on key variables affecting the tram company's benefit function as well as replacement service decisions. The numerical analyses provide immediate managerial implications. The proposed method can be easily extended to real-time disruption recovery for urban public transit system by capturing passenger patterns and vehicle status through big data technologies.
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