Transport Policy最新文献_第8页

Accounting for the uncertainty in an analysis of travel choice experiments using a hybrid choice model 利用混合选择模型分析旅行选择实验中的不确定性

IF 6.3 2区工程技术 Q1 ECONOMICS

Transport Policy

Pub Date : 2025-12-27 DOI: 10.1016/j.tranpol.2025.103981

Amin Moeinaddini , Meeghat Habibian

To evaluate the impacts of Transportation Demand Management (TDM) policies on traffic congestion and air pollution, citizens' travel behavior should be investigated accurately. The Choice Experiment (CE) approach could be adopted to investigate the behavior of citizens who may be affected by TDM policies. However, respondents might not be sure about their choices, and this uncertainty can be intensified when CEs are used to assess combinations of TDM policies. The choice uncertainty is a degree (or index) that indicates how uncertain a respondent is about their choice, which could result in inaccuracy in predicting transportation behavior. This study focuses on the mode choice uncertainty when there are three TDM policies, including transit development, cordon, and parking pricing, in an analysis of CEs. In this regard, using a face-to-face survey, the car commuters who traveled to a region in the central part of Tehran, Iran, at peak hours for work purposes were questioned about the reduction of car usage as well as the level of certainty about their decision. Afterward, using a hybrid choice model, respondents' choices and their certainty are addressed by considering panel correlations. According to the results, choice certainty depends on the cordon entrance fee, the number of urban trips per day, the value of the cars owned by the individual's household, age, and gender. The results also indicated that increasing the cordon entrance fee and parking cost reduce the choice certainty.

为了评估交通需求管理（TDM）政策对交通拥堵和空气污染的影响，需要对市民的出行行为进行准确调查。选择实验（CE）方法可用于调查受TDM政策影响的公民的行为。然而，受访者可能不确定他们的选择，当使用ce来评估TDM政策组合时，这种不确定性可能会加剧。选择不确定性是一个程度（或指数），表明受访者对他们的选择有多不确定，这可能导致预测交通行为的不准确性。本文主要研究了交通发展、封锁线和停车收费三种TDM政策下的模式选择不确定性。在这方面，通过面对面的调查，对在工作高峰时间前往伊朗德黑兰中部地区的汽车通勤者进行了关于减少汽车使用量以及他们决定的确定程度的询问。之后，使用混合选择模型，受访者的选择和他们的确定性是通过考虑面板相关性来解决的。根据结果，选择的确定性取决于警戒线入场费、每天的城市出行次数、个人家庭拥有的汽车价值、年龄和性别。研究结果还表明，停车费和停车费的增加降低了选择的确定性。

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引用次数: 0

The impact of transport network improvements in inter-provincial border counties on county centrality under local protectionism: Breaking barriers or reinforcing the siphon effect? 地方保护主义下省际边境县域交通网络改善对县域中心度的影响：打破壁垒还是强化虹吸效应？

IF 6.3 2区工程技术 Q1 ECONOMICS

Transport Policy

Pub Date : 2025-12-26 DOI: 10.1016/j.tranpol.2025.103980

Xuechen Meng , Qinyin Meng , Xiaoying Zhou , Xiaoshu Xu

Interprovincial border regions have long been constrained by administrative boundaries, giving rise to “administrative regional economies” in which local protectionism plays a central role. This study examines whether improvements in transport infrastructure enhance county-level economic centrality by mitigating these administrative barriers. Using panel data for 587 interprovincial border counties from 2000 to 2021, we construct an index of county centrality to capture factor agglomeration capacity and estimate multi-period difference-in-differences models, complemented by instrumental-variable and robustness checks. The results show that: (1) on average, highway openings are associated with a decline in border-county centrality. (2) Transportation integration raises centrality in more open eastern border counties, especially those within roughly 150–200 km of core cities, while effects are muted or negative in western regions and in more remote eastern counties. (3) Mechanism tests show that highway openings are followed by increases in the local SOE share and reduced non-SOE entry where centrality does not improve, consistent with reinforced administrative barriers that impede factor mobility and diminish regional centrality. We hence theoretically capture and provide robust empirical evidence for an “institutional transport paradox”: under specific institutional conditions, reductions in transport costs can become a catalyst for market segmentation rather than an unambiguous force for integration. The findings highlight that dismantling administrative barriers is a precondition for transport-enabled regional coordination and provide guidance for the differentiated design of cross-provincial transport and reform policies.

省际边境地区长期受到行政边界的制约，形成了以地方保护主义为核心的“行政区域经济”。本研究考察了交通基础设施的改善是否通过减轻这些行政障碍来增强县级经济中心性。利用2000年至2021年587个省际边境县的面板数据，我们构建了一个县中心性指数来捕捉要素集聚能力，并估计了多期差异中的差异模型，并通过工具变量和稳健性检验进行了补充。结果表明：(1)平均而言，高速公路开通与边界县中心度下降相关。(2)交通一体化提高了较开放的东部边境县域的中心性，尤其是距离核心城市约150-200公里的县域，而对西部地区和较偏远的东部县域的中心性影响不大或为负。(3)机制检验表明，高速公路开通后，地方国有企业份额增加，非国有企业进入减少，而中心性没有提高，这与阻碍要素流动和降低区域中心性的行政壁垒加强相一致。因此，我们从理论上捕捉并提供了“制度运输悖论”的有力经验证据：在特定的制度条件下，运输成本的降低可以成为市场细分的催化剂，而不是一体化的明确力量。研究结果强调，消除行政障碍是实现交通区域协调的前提条件，并为跨省交通的差别化设计和改革政策提供了指导。

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引用次数: 0

Identification and dynamic simulation of electric-vehicle charging demand drivers: a high-order hybrid method 电动汽车充电需求驱动因素识别与动态仿真：一种高阶混合动力方法

IF 6.3 2区工程技术 Q1 ECONOMICS

Transport Policy

Pub Date : 2025-12-25 DOI: 10.1016/j.tranpol.2025.103978

Jing Liu , Wei Gao , Xuewen Zhang , Jie Zhang

Rapid expansion of electric vehicles has made charging demand highly variable in space and time, yet its coupled drivers are poorly understood. We develop a three-stage embedded hybrid method to close this gap. Sixteen spatial, facility, pricing, and weather variables are first identified. Their causal weights are quantified through a Pearson correlation–transfer entropy–DEMATEL sequence. Finally, the weighted relations are embedded in a complex-network framework to perform node-failure, centrality, edge-weight sensitivity, and threshold-based dynamic-pricing simulations. A Shenzhen charger dataset validates the model. Results reveal that charging demand is jointly governed by spatial layout, economic regulation, and environmental conditions. Traffic adjacency, charger count, and occupancy dominate demand, whereas real-time price and inter-station distance, despite weak causality, hold the highest centrality and sensitivity. Dynamic pricing cuts peaks by ∼20 % in stable periods but fails under extreme shocks. We recommend mixed stations and coordinated pricing, demand-response, and storage strategies to enhance network resilience.

电动汽车的快速扩张使得充电需求在空间和时间上具有高度的可变性，但人们对其耦合驱动因素的理解却很少。我们开发了一种三阶段嵌入式混合方法来缩小这一差距。首先确定16个空间、设施、价格和天气变量。它们的因果权重通过皮尔逊相关-转移熵- dematel序列量化。最后，将加权关系嵌入到复杂网络框架中，以执行节点故障、中心性、边权敏感性和基于阈值的动态定价模拟。深圳充电器数据集验证了该模型。结果表明，城市充电需求受空间布局、经济调控和环境条件的共同制约。交通邻接性、充电器数量和占用率主导需求，而实时价格和站间距离尽管因果关系较弱，但具有最高的中心性和敏感性。在稳定时期，动态定价削减的峰值为20%，但在极端冲击下则失效。我们建议采用混合站和协调定价、需求响应和存储策略来增强网络弹性。

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引用次数: 0

Toward lower-emission freight: Grid infrastructure tradeoffs of battery-electric vs fuel cell trucks in New Zealand 迈向低排放货运：新西兰的电池电动卡车与燃料电池卡车的电网基础设施权衡

IF 6.3 2区工程技术 Q1 ECONOMICS

Transport Policy

Pub Date : 2025-12-25 DOI: 10.1016/j.tranpol.2025.103974

Wilson McNeil , Rafaella Canessa , Corinne D. Scown , Jannik Haas , Rebecca Peer

Trucking is critical for New Zealand's economy as it is responsible for most of the country's freight movement. However, the reliance on diesel-powered trucks disproportionately contributes to carbon dioxide (CO₂) and air pollutant emissions. Two different technologies have the potential to electrify heavy freight: battery-electric and fuel cell electric trucks; however, it remains unclear which technology will be used to reach New Zealand's goal of net-zero freight transportation emissions by 2050. In this study, we develop an integrated assessment framework that quantifies present-day heavy truck emissions in New Zealand and compares the energy requirement of decarbonization through battery-electric versus fuel cell trucks in 2035 and 2050. This framework includes freight demand, vehicle powertrain, truck operation and charging, and diesel emission models. Further, we quantify the electricity grid infrastructure requirements of the shift to battery-electric and fuel cell truck fleets using the REMix-NZ capacity expansion model. Results show that the current fleet of heavy diesel trucks in New Zealand emits 2.4 million tonnes of CO₂ eq. annually, which could be fully mitigated by 2050 through battery-electric or fuel cell fleets. A full fleet of battery-electric trucks in 2050 would consume 7.2 % of New Zealand's current electricity generation compared to 13.5 % for fuel cell trucks. A sensitivity analysis shows that improved truck design and efficiency can reduce this electricity requirement. Up to 3.6 GW additional capacity would need to be built by 2050, primarily through solar power, to satisfy the energy demand of a battery-electric truck fleet compared to 5.3 GW for a fuel cell fleet.

卡车运输对新西兰的经济至关重要，因为它负责该国大部分的货运活动。然而，对柴油动力卡车的依赖不成比例地增加了二氧化碳和空气污染物的排放。两种不同的技术有可能实现重型货运的电气化：电池电动和燃料电池电动卡车；然而，目前尚不清楚哪种技术将用于实现新西兰到2050年货运净零排放的目标。在本研究中，我们开发了一个综合评估框架，量化了新西兰目前重型卡车的排放，并比较了2035年和2050年通过电池电动卡车和燃料电池卡车实现脱碳的能源需求。该框架包括货运需求、车辆动力系统、卡车运行和充电以及柴油排放模型。此外，我们使用REMix-NZ容量扩展模型量化了向电池电动和燃料电池卡车车队转变的电网基础设施需求。结果显示，新西兰目前的重型柴油卡车每年排放240万吨二氧化碳当量，到2050年，通过电池电动或燃料电池车队可以完全缓解这一问题。到2050年，一个完整的电池电动卡车车队将消耗新西兰当前发电量的7.2%，而燃料电池卡车的发电量为13.5%。敏感性分析表明，改进卡车设计和效率可以减少这种电力需求。到2050年，要满足电池电动卡车车队的能源需求，需要增加3.6吉瓦的额外容量，主要是通过太阳能发电，而燃料电池车队的能源需求为5.3吉瓦。

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引用次数: 0

AI deployment for heterogeneous ports: Strategic choices between independent R&D and outsourcing 异构端口的AI部署：自主研发与外包的战略选择

IF 6.3 2区工程技术 Q1 ECONOMICS

Transport Policy

Pub Date : 2025-12-24 DOI: 10.1016/j.tranpol.2025.103977

Bo Lu, Guixian Zhang, Yonggang Li

Artificial intelligence (AI) technology is the key support for the intelligent transformation of ports. This study examines optimal AI technology deployment strategies for heterogeneous ports operating within co-opetition networks. We consider the ecological synergy characteristics, deployment effect uncertainty and port heterogeneity, construct a dual-market game-theoretic model to analyze the strategic choice between independent R&D and outsourcing. The results reveal that deployment decisions of port are shaped not only by cost-benefit considerations but also by the interplay of co-opetition structures, technological ecosystems, and AI technology risks. A cooperation paradox is identified, expansion of the cooperative market may reduce AI technology level when both ports pursue independent R&D, particularly under the expected effect of deployment is low. This outcome that underscores the technology investment motivational barriers in loosely coupled alliances. Conversely, when ports form a unified technology ecosystem, cooperative market growth positively correlates with the AI technology deployment level, driven by ecological synergy effects. If one port opts for independent R&D while the other outsources third-party AI technology, competitive advantage hinges on whether the former's AI deployment effect exceeds a critical threshold. The study delineates a multidimensional strategic space defined by cooperative market scale, competition intensity, AI technology deployment effect uncertainties and R&D costs, provide theoretical support for ports in choosing AI technology deployment strategy.

人工智能技术是港口智能化改造的关键支撑。本研究探讨了在合作竞争网络中运行的异构端口的最佳人工智能技术部署策略。考虑生态协同特征、部署效果的不确定性和端口异质性，构建双市场博弈论模型，分析自主研发与外包的战略选择。结果表明，港口的部署决策不仅受到成本效益考虑的影响，还受到合作竞争结构、技术生态系统和人工智能技术风险的相互作用的影响。发现了一个合作悖论，当双方都追求自主研发时，特别是在部署预期效果较低的情况下，合作市场的扩大可能会降低人工智能技术水平。这一结果强调了松散耦合联盟中的技术投资动机障碍。相反，当港口形成统一的技术生态系统时，在生态协同效应的驱动下，协同市场增长与人工智能技术部署水平呈正相关。如果一个港口选择自主研发，而另一个港口将人工智能技术外包给第三方，那么竞争优势取决于前者的人工智能部署效果是否超过一个临界阈值。研究勾勒出由合作市场规模、竞争强度、人工智能技术部署效果不确定性和研发成本所定义的多维战略空间，为港口选择人工智能技术部署策略提供理论支持。

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引用次数: 0

Policy-mix complexity and carbon emissions: evidence from China's EV industry 政策组合复杂性与碳排放：来自中国电动汽车行业的证据

IF 6.3 2区工程技术 Q1 ECONOMICS

Transport Policy

Pub Date : 2025-12-24 DOI: 10.1016/j.tranpol.2025.103976

Xiaolei Zhao , Xuemei Li , Lingrun Yang

China's electric vehicle (EV) policies, designed to address the energy crisis and improve urban air quality, exhibit significant policy-mix complexity (PC). This study examines the effect of PC on carbon emissions using panel data from 280 cities in China. Findings reveal a U-shaped relationship between PC and carbon emissions, with moderately complex policies most effective in reducing emissions. This causal U-shaped relationship is robustly identified using a two-stage least squares (2SLS) strategy with institutional and political instruments. Mechanism analysis reveals that this U-shape is driven by an underlying inverted U-shaped relationship between PC and key pathways: market uptake, infrastructure investment and technological innovation. Among PC dimensions, the number of policy instruments (PIs) and policy scope (PS) significantly reduce emissions, while policy types (PTs) and departments involved (DI) show no significant impact. Heterogeneity analysis indicates the U-shaped relationship holds in less developed areas and during 2003–2011. PIs are most effective in developed regions, while PS excels in the 2003–2011 period. This study improves theoretical insights in PC and provides practical guidance for designing EV policies to mitigate carbon emissions.

中国的电动汽车（EV）政策旨在解决能源危机和改善城市空气质量，表现出显著的政策组合复杂性（PC）。本研究利用中国280个城市的面板数据考察了PC对碳排放的影响。研究结果表明，PC与碳排放呈u型关系，适度复杂的政策对减排最有效。使用两阶段最小二乘法（2SLS）策略以及制度和政治工具，可以强有力地确定这种因果u型关系。机制分析表明，这一u型是由PC与关键路径（市场吸收、基础设施投资和技术创新）之间潜在的倒u型关系驱动的。在PC维度中，政策工具数量（pi）和政策范围（PS）显著减少排放，而政策类型（PTs）和参与部门（DI）没有显著影响。异质性分析表明，经济欠发达地区和2003-2011年之间存在u型关系。在发达地区，pi最有效，而PS在2003-2011年期间表现优异。本研究提高了PC的理论认识，并为电动汽车减排政策的设计提供了实践指导。

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引用次数: 0

Ownership, regulation, and ESG in transport and logistics: Insights for policy from explainable machine learning 运输和物流中的所有权、监管和ESG：来自可解释机器学习的政策见解

IF 6.3 2区工程技术 Q1 ECONOMICS

Transport Policy

Pub Date : 2025-12-23 DOI: 10.1016/j.tranpol.2025.103967

Xiaowen Sha , Miao Su

This study employs an explainable machine learning framework to examine the key factors associated with environmental, social, and governance (ESG) performance in China's transportation and logistics industry. Using panel data of 1912 firm-year observations from A-share listed companies (2009–2023), the CatBoost model is combined with SHapley Additive exPlanations (SHAP) for accurate and interpretable predictions. Among 11 mainstream ML algorithms, CatBoost achieves the lowest mean absolute error. Results show that management expense ratio, executive compensation, fixed asset ratio, and capital intensity positively correlated with ESG performance, while firm size, independent director ratio, and ownership concentration of top ten shareholders have negatively associated with it. SHAP reveals nonlinear relationships and complex interactions. Heterogeneity tests indicate notable differences between state-owned and private enterprises and between regulated and non-regulated industries. These findings provide evidence and guidance for stakeholders, supporting targeted ESG strategies and demonstrating the value of explainable AI in promoting sustainable development.

本研究采用可解释的机器学习框架来考察与中国运输和物流业环境、社会和治理（ESG）绩效相关的关键因素。利用a股上市公司1912年的面板数据（2009-2023），CatBoost模型与SHapley加性解释（SHAP）相结合，以获得准确和可解释的预测。在11种主流ML算法中，CatBoost的平均绝对误差最小。结果表明，管理费用率、高管薪酬、固定资产比率、资本密集度与ESG绩效呈正相关，公司规模、独立董事比例、前十大股东股权集中度与ESG绩效呈负相关。SHAP揭示了非线性关系和复杂的相互作用。异质性检验表明，国有企业与民营企业、受管制行业与非管制行业之间存在显著差异。这些发现为利益相关者提供了证据和指导，支持有针对性的ESG战略，并展示了可解释的人工智能在促进可持续发展方面的价值。

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引用次数: 0

Electricity demand assessment and charging infrastructure planning for long-haul electric vehicle operations in Ontario, Canada 加拿大安大略省长途电动汽车的电力需求评估和充电基础设施规划

IF 6.3 2区工程技术 Q1 ECONOMICS

Transport Policy

Pub Date : 2025-12-22 DOI: 10.1016/j.tranpol.2025.103970

Terence Dimatulac, Hanna Maoh, Rupp Carriveau

As Canada advances toward its target of zero-emission heavy commercial vehicle sales by 2040, the success of long-haul electric vehicle (LHEV) adoption will depend on the availability of well-placed, high-capacity public charging infrastructure. This study evaluates how two critical real-world constraints, namely daily utilization time and site space capacity, affect the optimal design of Ontario's future on-route charging network by simulating a total of 63 scenarios. The results show that modest utilization thresholds (e.g., 8 h per day) can reduce the number of required stations by up to 20 % with minimal impact on service coverage. In contrast, restricted space capacity leads to steep declines in the number of supported trips unless more locations are added. When both constraints are applied together, their impacts are largely additive, increasing the need for infrastructure expansion while shifting grid demand across space and time. The study highlights the need to align transportation and electricity infrastructure planning, prioritize high-demand freight corridors, and support regulatory frameworks that promote efficient, high-utilization, and grid-resilient charging solutions.

随着加拿大向2040年重型商用车零排放销售目标迈进，长途电动汽车（LHEV）的成功采用将取决于位置良好、容量大的公共充电基础设施的可用性。本研究通过模拟共63个场景，评估了两个关键的现实世界约束，即每日使用时间和站点空间容量，如何影响安大略省未来路由充电网络的优化设计。结果表明，适度的利用率阈值（例如，每天8小时）可以将所需的站点数量减少20%，而对服务覆盖的影响最小。相反，除非增加更多的地点，否则有限的空间容量导致支持的旅行次数急剧下降。当这两种约束条件一起应用时，它们的影响在很大程度上是叠加的，增加了对基础设施扩张的需求，同时使电网需求跨越空间和时间。该研究强调，需要协调交通和电力基础设施规划，优先考虑高需求货运走廊，并支持促进高效、高利用率和电网弹性充电解决方案的监管框架。

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引用次数: 0

Slower roads, cleaner skies? causal effects of speed limit reduction on urban air quality using propensity score matching and spatial difference-in-differences regression 更慢的道路，更干净的天空？基于倾向得分匹配和空间差中差回归的限速降低对城市空气质量的因果影响

IF 6.3 2区工程技术 Q1 ECONOMICS

Transport Policy

Pub Date : 2025-12-22 DOI: 10.1016/j.tranpol.2025.103969

Wookjae Yang, Byunguk Kang

Vehicle speed limit reduction policies have been widely studied for their impact on traffic safety outcomes, such as reducing crash frequency and severity. However, little attention has been paid to the effects on air quality that may have resulted from traffic volume changes induced by speed reductions. This study aims to assess the causal impact of the speed limit reduction policy in the Republic of Korea, “5030 Speed Limit Reduction"- urban roads from 60 to 80 km/h to 50–60 km/h and on local roads from 40 to 60 km/h to 30 km/h, on air quality, explicitly targeting particulate matter (PM₁₀), carbon monoxide (CO), carbon dioxide (CO₂), nitrogen oxides (NO_x), and volatile organic compounds (VOCs). By employing a quasi-experimental study design that combines propensity score matching (PSM) and spatial difference-in-differences (SDID) regression, this research addresses gaps in existing studies by investigating the causal impact of speed limit reductions on air quality and spatial dependence, while controlling for confounding variables, such as built environment and socioeconomic status. The PSM result indicates that after matching, the mean differences between the treatment and control groups were substantially reduced, indicating that matching effectively balanced covariates. The results of three different difference-in-difference models (linear regression DID, spatial error DID, and spatial lag DID) were applied to five air pollutants: CO₂, CO, NO_x, VOCs, and PM₁₀. The treatment effect is positive and statistically significant across all pollutants, except NO_x. This confirms that the speed limit reduction policy increased traffic volume and, consequently, increased emissions, thereby worsening air quality. Although the policy successfully contributes to the United Nations' Sustainable Development Goals (SDGs) by significantly reducing crashes and enhancing road safety, it falls short of achieving another key aspect of sustainability, improving air quality. Therefore, comprehensive strategies are required to achieve sustainable urban environments.

车辆限速政策对交通安全结果的影响，如降低碰撞频率和严重程度，已被广泛研究。然而，很少有人注意到减速引起的交通量变化可能对空气质量造成的影响。本研究旨在评估韩国“5030限速降低”政策对空气质量的因果影响，即城市道路从60至80公里/小时降至50至60公里/小时，地方道路从40至60公里/小时降至30公里/小时，明确针对颗粒物（PM10）、一氧化碳（CO）、二氧化碳（CO2）、氮氧化物（NOx）和挥发性有机化合物（VOCs）。本研究采用结合倾向得分匹配（PSM）和空间差中差回归（SDID）的准实验研究设计，通过调查限速降低对空气质量和空间依赖性的因果影响，同时控制混杂变量，如建筑环境和社会经济地位，解决了现有研究的空白。PSM结果表明，匹配后，处理组和对照组之间的平均差异显著减小，表明匹配有效地平衡了协变量。将三种不同的差分模型（线性回归DID、空间误差DID和空间滞后DID）的结果应用于五种空气污染物：CO2、CO、NOx、VOCs和PM10。除氮氧化物外，对所有污染物的处理效果均为正的，具有统计学意义。这证实了降低速度限制政策增加了交通量，从而增加了排放量，从而恶化了空气质量。尽管该政策通过大幅减少交通事故和加强道路安全，成功地为联合国的可持续发展目标做出了贡献，但它未能实现可持续性的另一个关键方面，即改善空气质量。因此，需要综合战略来实现可持续的城市环境。

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引用次数: 0

Comparing fare evasion severity by econometric and artificial intelligence models: An Italian case study 用计量经济学和人工智能模型比较逃票严重程度：一个意大利案例研究

IF 6.3 2区工程技术 Q1 ECONOMICS

Transport Policy

Pub Date : 2025-12-22 DOI: 10.1016/j.tranpol.2025.103971

Benedetto Barabino, Roberto Ventura

Fare evasion is a pressing issue in public transport networks, impacting the financial sustainability of Transit Agencies (TAs) and Public Transport Companies (PTCs). While prior studies have largely focused on the probability of fare evasion (or frequency), research on severity— e.g., the financial and operational impact of detected fare evasion cases—remains limited. This study addresses this gap by specifying, calibrating, and validating two prediction models for fare evasion severity using real-world survey data on passengers from a mid-sized Italian PTC. Two approaches are employed: an Econometric Approach (EA) that uses Logistic Regression Models (LRMs) and a Machine Learning Approach (MLA) leveraging an Artificial Neural Network Model (ANNM). Model performance is evaluated and compared using Confusion Matrices, Metrics robust to class imbalance (e.g., Area Under the Precision-Recall Curve, Balanced Accuracy), and Probability Calibration tools (e.g., reliability curves, Brier score). Probability thresholds (cut-offs) are enhanced to improve predictive performance under imbalanced conditions. Finally, each predictor effect is assessed for both models. Results indicate that the ANNM slightly outperforms the LRM in this case study, demonstrating higher predictive accuracy and a stronger ability to detect high-severity fare evasion cases. However, this gain entails a minor rise in false positives, reflecting the trade-off between predictive accuracy and calibration stability. The LRM remains valuable for policy analysis, offering consistent and interpretable probability estimates to help TAs/PTCs understand key factors influencing fare evasion severity. These findings provide critical insights for enhancing fare inspection policies and enforcement resource allocation.

逃票是公共交通网络中的一个紧迫问题，它影响着公共交通机构（TAs）和公共交通公司（ptc）的财务可持续性。虽然先前的研究主要集中在逃票的概率（或频率）上，但对严重程度的研究——例如，被发现的逃票案件的财务和运营影响——仍然有限。本研究通过指定、校准和验证两种逃票严重程度的预测模型来解决这一差距，该模型使用了意大利一家中型PTC的真实乘客调查数据。采用了两种方法：使用逻辑回归模型（lrm）的计量经济学方法（EA）和利用人工神经网络模型（ANNM）的机器学习方法（MLA）。使用混淆矩阵、对类别不平衡稳健的度量（例如，精确召回曲线下的面积，平衡精度）和概率校准工具（例如，可靠性曲线，Brier分数）来评估和比较模型性能。增强概率阈值（截止值）以提高不平衡条件下的预测性能。最后，对两种模型的预测效应进行了评估。结果表明，在本案例研究中，ANNM略优于LRM，表现出更高的预测准确性和更强的检测高严重性逃票案件的能力。然而，这种增益导致误报的小幅上升，反映了预测精度和校准稳定性之间的权衡。LRM对于政策分析仍然有价值，它提供了一致且可解释的概率估计，以帮助TAs/ ptc了解影响逃票严重程度的关键因素。这些发现为加强票价检查政策和执法资源分配提供了重要见解。

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引用次数: 0