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[Submitted] Predicting Consumer Travel Behavior in the MaaS Era

Published:  at  09:00 AM
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๐Ÿ† Research Status & Connection

This manuscript is currently under review in a top-tier SSCI-indexed journal. It represents a significantly matured version of the initial research presented at an academic conference.


๐Ÿ“Œ Research Overview

To simulate the future of mobility markets, this study focuses on the demand-side response to Mobility as a Service (MaaS). By decoding how human choices adapt to integrated transportation paradigms, the research provides the behavioral intelligence necessary to forecast market dynamics.

โš™๏ธ Methodology

To analyze these behavioral shifts, the study employs a robust data-driven methodology:

  1. Consensus Clustering: Segments the mobility market based on actual daily travel frequencies, providing a more stable classification than traditional single-algorithm methods.
  2. Behavioral Inference: Predicts the probability of mode shifts (e.g., from private cars to shared mobility) using discrete choice modeling and statistical verification.

For the foundational model and initial presentation details, please refer to the Conference Presentation Archive.


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