Print Email Facebook Twitter Behavioral modeling of on-demand mobility services Title Behavioral modeling of on-demand mobility services: general framework and application to sustainable travel incentives Author Xie, Yifei (Massachusetts Institute of Technology) Danaf, Mazen (Massachusetts Institute of Technology) Azevedo, Carlos Lima (Technical University of Denmark) Akkinepally, Arun Prakash (Massachusetts Institute of Technology) Atasoy, B. (TU Delft Transport Engineering and Logistics) Jeong, Kyungsoo (National Renewable Energy Laboratory) Seshadri, Ravi (Singapore-MIT Alliance) Ben-Akiva, Moshe E. (Massachusetts Institute of Technology) Date 2019 Abstract This paper presents a systematic way of understanding and modeling traveler behavior in response to on-demand mobility services. We explicitly consider the sequential and yet inter-connected decision-making stages specific to on-demand service usage. The framework includes a hybrid choice model for service subscription, and three logit mixture models with inter-consumer heterogeneity for the service access, menu product choice and opt-out choice. Different models are connected by feeding logsums. The proposed modeling framework is essential for accounting the impacts of real-time on-demand system’s dynamics on traveler behaviors and capturing consumer heterogeneity, thus being greatly relevant for integrations in multi-modal dynamic simulators. The methodology is applied to a case study of an innovative personalized on-demand real-time system which incentivizes travelers to select more sustainable travel options. The data for model estimation is collected through a smartphone-based context-aware stated preference survey. Through model estimation, lower values of time are observed when the respondents opt to use the reward system. The perception of incentives and schedule delay by different population segments are quantified. These results are fundamental in setting the ground for different behavioral scenarios of such a new on-demand system. The proposed methodology is flexible to be applied to model other on-demand mobility services such as ride-hailing services and the emerging mobility as a service. Subject Smart mobilityOn-demandIncentivesTravel behaviorStated preferenceSustainability To reference this document use: http://resolver.tudelft.nl/uuid:61b9a8f5-45ee-421f-b216-e8ce4c27a6f3 DOI https://doi.org/10.1007/s11116-019-10011-z Embargo date 2019-12-03 ISSN 0049-4488 Source Transportation, 46 (6), 2017-2039 Bibliographical note Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Part of collection Institutional Repository Document type journal article Rights © 2019 Yifei Xie, Mazen Danaf, Carlos Lima Azevedo, Arun Prakash Akkinepally, B. Atasoy, Kyungsoo Jeong, Ravi Seshadri, Moshe E. Ben-Akiva Files PDF Xie2019_Article_Behaviora ... emandM.pdf 2.2 MB Close viewer /islandora/object/uuid:61b9a8f5-45ee-421f-b216-e8ce4c27a6f3/datastream/OBJ/view