Built environment impacts on zonal shared e-scooter expenses: A Bayesian learning approach

IF 7.7 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment Pub Date : 2025-10-06 DOI:10.1016/j.trd.2025.105020

Guocong Zhai , Ruigan Wang , Xiang Liu , Miloš N. Mladenović , Yandong Tang , Huaqiao Mu , Xiaobo Liu , Hongtai Yang

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引用次数: 0

Abstract

Shared e-scooters are reshaping urban mobility, yet trip expense patterns, a key to operator viability, remain unexplored. This study examines how built environment factors affect zonal-level shared e-scooter trip expenses in Chicago, using a novel lognormal regression model enhanced by Bayesian Additive Regression Trees (LN + BART). The model outperforms traditional methods by accommodating the right-skewed distribution and capturing the nonlinear effects on the trip expenses. Results reveal threshold effects: areas with higher median income level, higher POI (Point of Interest) density, and closer distance to CBD (Central Business District) yield disproportionately higher revenues. However, zones with higher percentages of car-free households show lower e-scooter usage, highlighting affordability barriers despite clear mobility needs. This research advances transport economics by combining distribution-aware modeling with Bayesian machine learning, enhancing prediction and interpretability. It also offers important insights for operators to optimize deployment.

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建筑环境对区域共享电动滑板车费用的影响：贝叶斯学习方法

共享电动滑板车正在重塑城市交通，但出行费用模式（这是运营商生存的关键）仍未得到探索。本研究采用贝叶斯加性回归树（LN + BART）增强的对数正态回归模型，研究了芝加哥建筑环境因素对区域级共享电动滑板车出行费用的影响。该模型通过适应右偏态分布和捕捉出行费用的非线性影响，优于传统方法。结果显示了阈值效应：收入中位数水平较高、POI（兴趣点）密度较高、距离中央商务区较近的地区，其收入不成比例地高。然而，无车家庭比例较高的地区，电动滑板车的使用率较低，这突显了尽管有明确的出行需求，但仍存在负担能力障碍。本研究将分布感知模型与贝叶斯机器学习相结合，提高了预测和可解释性，从而促进了运输经济学的发展。它还为运营商优化部署提供了重要的见解。

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来源期刊

Transportation Research Part D-transport and Environment 工程技术-运输科技

CiteScore

14.40

自引率

9.20%

发文量

314

审稿时长

39 days

期刊介绍： Transportation Research Part D: Transport and Environment focuses on original research exploring the environmental impacts of transportation, policy responses to these impacts, and their implications for transportation system design, planning, and management. The journal comprehensively covers the interaction between transportation and the environment, ranging from local effects on specific geographical areas to global implications such as natural resource depletion and atmospheric pollution. We welcome research papers across all transportation modes, including maritime, air, and land transportation, assessing their environmental impacts broadly. Papers addressing both mobile aspects and transportation infrastructure are considered. The journal prioritizes empirical findings and policy responses of regulatory, planning, technical, or fiscal nature. Articles are policy-driven, accessible, and applicable to readers from diverse disciplines, emphasizing relevance and practicality. We encourage interdisciplinary submissions and welcome contributions from economically developing and advanced countries alike, reflecting our international orientation.