A Multi-class Ride-hailing Service Subsidy System Utilizing Deep Causal Networks
<|reference_start|>A Multi-class Ride-hailing Service Subsidy System Utilizing Deep Causal Networks: In the ride-hailing industry, subsidies are predominantly employed to incentivize consumers to place more orders, thereby fostering market growth. Causal inference techniques are employed to estimate the consumer elasticity with different subsidy levels. However, the presence of confounding effects poses challenges in achieving an unbiased estimate of the uplift effect. We introduce a consumer subsidizing system to capture relationships between subsidy propensity and the treatment effect, which proves effective while maintaining a lightweight online environment.<|reference_end|>
@article{yu2024a,
    title={A Multi-class Ride-hailing Service Subsidy System Utilizing Deep Causal
  Networks},
    author={Zhe Yu, Chi Xia, Shaosheng Cao, Lin Zhou},
    journal={arXiv preprint arXiv:2408.02065},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.02065},
    primaryClass={cs.LG stat.ML}
}