Metro service disruptions: how do people choose to travel?

While metro disruptions can have a significant impact to the travel patterns and behavior of users, research on that topic has been limited. Using Athens, Greece, as a study case, this paper combines information on traveler experiences and perceptions and attempts to model mode choice during a long-run metro service disruption. A Nested Logit (NL) approach for jointly analyzing RP/SP data is applied and compared to individual RP and SP based MNL models. Findings suggest that the propensity to shift to buses or cars in such cases depends—to a large extent—on the travelers’ available income. Also, the possibility of a flexible work schedule is negatively correlated with the choice of using a car during metro closures. Finally, the overall performance of the joint RP/SP Nested Logit model has been found to be superior to that of the joint RP/SP MNL model.

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