Bus_DCE_DIB_Data

This dataset comprises stated-preference data from a face-to-face Discrete Choice Experiment (DCE) conducted to quantify passenger willingness to pay (WTP) for public bus service improvements in Hanoi, Vietnam. The study evaluates trade-offs across six key attributes: access time, schedule punctuality, ride quality, app usability, emission reductions, and fare increments.

Structured as an encoded long-format panel, the dataset integrates respondent socio-demographics and environmental attitudes with binary choice tasks. It is optimized for discrete choice modeling (e.g., Conditional or Mixed Logit) to analyze preference heterogeneity and price sensitivity. This resource supports methodological benchmarking and policy analysis for sustainable urban transport planning.

本数据集包含来自面对面离散选择实验（Discrete Choice Experiment, DCE）的陈述偏好数据，该实验旨在量化越南河内市公共巴士服务提升场景下乘客的支付意愿（Willingness to Pay, WTP）。本研究围绕六项核心属性开展权衡分析：接驳时间、准点率、乘车品质、应用程序易用性、减排量及票价涨幅。
本数据集采用编码长格式面板结构，整合了受访者的社会人口统计学特征、环境态度与二元选择任务数据。该数据集专为离散选择模型（如条件Logit模型或混合Logit模型）优化，可用于分析偏好异质性与价格敏感性。本数据集可为可持续城市交通规划领域的方法学基准测试与政策分析提供支撑。