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What is Causal Modelling for Transport Incentives about?

This paper presents a data-driven causal behaviour modelling approach to analyze passenger responses to fare incentives in public transport, specifically using smart card data from the Hong Kong Mass Transit Railway. The methodology includes causal discovery and inference phases to identify causal relationships and quantify the effects of interventions, revealing that approximately 3% of the population altered their travel behavior due to the incentive. The findings emphasize the importance of understanding

Author

malikhakim

Language

EN