Travel Behaviour and Society最新文献_第3页

Learning nonlinearity and measuring uncertainty--a multi-task neural network and additive gaussian process based travel choice model 学习非线性和测量不确定性——基于多任务神经网络和加性高斯过程的旅行选择模型

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2026-07-01 Epub Date: 2026-01-23 DOI: 10.1016/j.tbs.2026.101247

Sha Zhang , Yao Dong , Peter J. Jin , Shichao Sun , Fei Yang

Discrete choice model (DCM) is a classical framework for modelling an individual’s travel choice. However, its oversimplified architecture of utility function may limit its performance when faced with a complex decision process. In this paper, we develop a new framework called multi-task neural network and additive gaussian process based discrete choice model (MNNAGP-DCM). Specially, the multi-task neural network (MNN) is used to learn the representation of individual characteristics, while the additive Gaussian process regression (AGP) process is utilized to enhance flexibility of utility function. In multi-task neural network, the sub-learners learn the taste parameters between individuals’ characteristic in each alternative, while the global bias term is used to learn the cross effect between alternatives. The additive GPR framework is employed to substitute the linear term in utility function with a nonparametric probability framework. Additive GPR enables the modelling of nonlinearity, threshold effects and uncertainty, thereby providing a more comprehensive perspective on the decision-making process. Moreover, when combined with DCM, the GPRs become intractable. To address this, we employ variational inference to construct a tractable lower bound, thereby transforming the original model into a tractable one. Then MNNAGP-DCM can be optimized by gradient based algorithms such as Adam. The proposed model is tested on the open-source dataset and benchmarked with standard MNL, Mix-logit, XGBoost, TasteNet-MNL, MNN-DCM and MNNSGP-DCM. Results show that MNNAGP-DCM can not only capture individuals’ heterogeneity but also can learn the nonlinearity in utility function, showing great superiority in terms of predictability. Our model can also provide interpretable result with taste parameters and the fitted GPR models, while quantifying uncertainty through GPR’s probability framework.

离散选择模型（DCM）是一个经典的个人旅行选择建模框架。然而，在面对复杂的决策过程时，其过于简化的效用函数架构可能会限制其性能。本文提出了一种基于多任务神经网络和加性高斯过程的离散选择模型（MNNAGP-DCM）。其中，利用多任务神经网络（MNN）学习个体特征的表示，利用加性高斯过程回归（AGP）过程增强效用函数的灵活性。在多任务神经网络中，子学习者学习每个选择中个体特征之间的口味参数，而全局偏差项用于学习选择之间的交叉效应。采用加性探地雷达框架将效用函数中的线性项替换为非参数概率框架。加性探地雷达可以对非线性、阈值效应和不确定性进行建模，从而为决策过程提供更全面的视角。此外，当与DCM结合使用时，gpr变得棘手。为了解决这个问题，我们采用变分推理来构造一个可处理的下界，从而将原始模型转换为可处理的模型。然后利用Adam等基于梯度的算法对MNNAGP-DCM进行优化。该模型在开源数据集上进行了测试，并与标准MNL、Mix-logit、XGBoost、TasteNet-MNL、MNN-DCM和MNNSGP-DCM进行了基准测试。结果表明，MNNAGP-DCM不仅可以捕捉个体的异质性，还可以学习效用函数的非线性，在可预测性方面表现出很大的优势。通过探地雷达的概率框架对不确定性进行量化，该模型还可以利用味觉参数和拟合的探地雷达模型提供可解释的结果。

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引用次数: 0

Navigating the gig economy: transportation labor challenges facing California’s app-based ridehailing and courier drivers 驾驭零工经济：加州基于应用程序的叫车和快递司机面临的运输劳动力挑战

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2026-07-01 Epub Date: 2026-01-23 DOI: 10.1016/j.tbs.2025.101218

Susan Shaheen , Brooke Wolfe , Adam Cohen

Given the dynamic landscape surrounding the classification of workers in California, it is important to consider how the existing legal and regulatory environment may impact app-based gig drivers, including transportation network companies (TNCs, also known as ridehailing) and courier network services (CNS). Using a multi-method approach, we conducted a literature review (n = 41 sources), expert interviews (n = 8), and case study analysis (n = 7) between October 2022 to May 2024 to better understand how California’s gig drivers are impacted by state legislation and regulation (i.e., Assembly Bill 5, Proposition 22, and Senate Bill 1014). The expert interviews found that gig drivers are concerned with fair pay, benefits, labor classification, and transparency from the app-based platforms on issues related to punitive actions (i.e., deactivations). Drivers also raised concerns about California’s Clean Miles Standard (also known as SB 1014), which requires 90 % of vehicle miles traveled be electric by 2030, due to the financial costs associated with acquiring and operating electric vehicles (EVs) and limited public charging availability. The seven case studies examine gig labor policies from other states and countries (e.g., policies that may help enhance driver working conditions, platform regulation, and facilitate the EV transition). Together, these methods explore the tension between sustaining an app-based gig driving platform and providing fair compensation and working conditions for gig drivers. The study finds that state and/or local policies establishing minimum pay for drivers and policies enhancing transparency and appeal processes for driver deactivations could help improve working conditions for gig drivers. Various state agencies, such as the California Public Utilities Commission, could support gig drivers through incentives for the purchase of EVs and installation of EV charging near their homes and driving locations.

考虑到围绕加州工人分类的动态景观，重要的是要考虑现有的法律和监管环境如何影响基于应用程序的零工司机，包括运输网络公司（TNCs，也称为乘车服务）和快递网络服务（CNS）。利用多方法方法，我们在2022年10月至2024年5月期间进行了文献综述（n = 41个来源）、专家访谈（n = 8）和案例研究分析（n = 7），以更好地了解加州的零工司机是如何受到州立法和法规（即议会法案5、提案22和参议院法案1014）的影响的。专家访谈发现，零工司机关心的是公平的薪酬、福利、劳动分类，以及基于应用程序的平台在惩罚行动（即停用）相关问题上的透明度。由于购买和运营电动汽车的财务成本以及有限的公共充电设施，司机们还对加州的“清洁里程标准”（也称为SB 1014）提出了担忧。该标准要求，到2030年，电动汽车的行驶里程必须达到90%。这七个案例研究考察了其他州和国家的零工劳工政策（例如，可能有助于改善司机工作条件、平台监管和促进电动汽车转型的政策）。总之，这些方法探讨了维持基于应用程序的零工驾驶平台与为零工司机提供公平的薪酬和工作条件之间的紧张关系。研究发现，制定司机最低工资的州和/或地方政策，以及提高司机停职透明度和申诉程序的政策，可能有助于改善零工司机的工作条件。加州公用事业委员会（California Public Utilities Commission）等多个州政府机构可以通过奖励购买电动汽车，并在他们的家和驾驶地点附近安装电动汽车充电桩，来支持零工司机。

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引用次数: 0

Extracting socio-psychological perceptions for analysis of travel behaviours 为分析旅行行为提取社会心理感知

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2026-04-01 Epub Date: 2025-12-08 DOI: 10.1016/j.tbs.2025.101197

Yanyan Xu, Panchamy Krishnakumari, Neil Yorke-Smith, Serge Hoogendoorn

This article proposes an evidence-based policy recommendation framework integrating social media data and natural language processing methods, to support inclusive and efficient transport policy-making. Given that current research underscores the crucial role of both external and psychological variables in individual travel decisions, psychological features – such as beliefs, attitudes or values – are frequently used as latent variables for travel behaviour interpretation and travel choice modelling. However, user-centric policy recommendations based on dynamic psychological variables are still limited. Most studies rely on survey data, which neglects the urgent dynamic trend of user perception change and its underlying relationship with travel behaviour. Hence there is a lack of illustration on how these psychological variables can be further used at specific temporal and spatial levels for travel behaviour interpretation. This would be valuable to identify priorities for more targeted (sustainability and other) policies and interventions. In this article, we utilize sentiment analysis and dynamic topic modelling to represent the spatial–temporal variance of psychological features. Integrating with corresponding travel behaviour, we illustrate how these dynamic psychological features can distinguish travel dissonance, identify key motivations, and reflect urgent social demands at precise spatial–temporal levels. We demonstrate these advances in a case study in New York City from 2019 to 2022 using Twitter (X) data. A comparison with existing travel-related policies in the case study validates the feasibility of our framework to support evidence-based policy recommendations. We conclude by discussing the potential of this framework to support sustainable transport promotion.

本文提出了一个基于证据的政策建议框架，整合社交媒体数据和自然语言处理方法，以支持包容性和高效的交通政策制定。鉴于目前的研究强调了外部变量和心理变量在个人旅行决策中的关键作用，心理特征——如信仰、态度或价值观——经常被用作旅行行为解释和旅行选择建模的潜在变量。然而，基于动态心理变量的以用户为中心的政策建议仍然有限。大多数研究依赖于调查数据，忽视了用户感知变化的迫切动态趋势及其与出行行为的潜在关系。因此，缺乏关于如何在特定的时间和空间水平上进一步使用这些心理变量来解释旅行行为的说明。这对于确定更有针对性的（可持续性和其他）政策和干预措施的优先事项将是有价值的。本文利用情感分析和动态主题建模来表征心理特征的时空变异。结合相应的旅行行为，我们说明了这些动态心理特征如何区分旅行失调，识别关键动机，并在精确的时空水平上反映紧迫的社会需求。我们使用Twitter (X)数据在2019年至2022年期间在纽约市进行的案例研究中展示了这些进步。案例研究中与现有旅游相关政策的比较验证了我们的框架支持循证政策建议的可行性。最后，我们讨论了该框架在支持可持续交通推广方面的潜力。

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引用次数: 0

Exploring different patterns of bike-and-ride trips and influencing factors using geographically weighted random forest 基于地理加权随机森林的自行车出行模式及其影响因素研究

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2026-04-01 Epub Date: 2025-12-11 DOI: 10.1016/j.tbs.2025.101201

Zijian Yang , Guocong Zhai , N.N. Sze , Hongliang Ding , Nikolai Bobylev , Hongtai Yang

Numerous studies have examined the effectiveness of urban transportation planning policies such as park-and-ride, transit-oriented development, and multimodal transportation hubs in promoting public transit use. In the past decades, bike sharing, both dockless and docking systems, has been increasingly popular as a green transport mode, connecting to public transit. However, the influence of socioeconomic conditions, land-use factors, transport infrastructure, and station characteristics on bike-and-ride remains underexplored, particularly across different patterns of bike-and-ride. In this study, an integrated random forest (RF) and geographically weighted regression (GWR) model is applied to capture nonlinear relationships and spatial heterogeneity between bike-and-ride usage and explanatory variables, including socioeconomic variables, land-use factors, transportation infrastructure, and metro characteristics, based on the integrated bike sharing and metro ridership data in Chengdu, China. Additionally, a novel similarity metric, Dynamic Time Warping (DTW), is applied to classify the metro stations based on the temporal pattern of bike-and-ride trips at all stations. Hence, four clusters of metro stations with a varying pattern of bike-and-ride trips are established. The results show that the importance of determinants and their association with bike-and-ride vary significantly among different clusters of metro stations. This study proposes a fine-grained analytical framework for bike-and-ride, providing theoretical and empirical support for station function classification.

许多研究已经检验了城市交通规划政策的有效性，如停车换乘、交通导向发展和多式联运枢纽，以促进公共交通的使用。在过去的几十年里，共享单车作为一种连接公共交通的绿色交通方式，无论是无桩还是有坞系统，都越来越受欢迎。然而，社会经济条件、土地利用因素、交通基础设施和车站特征对自行车骑行的影响仍未得到充分探讨，特别是在不同的自行车骑行模式中。本文基于成都市共享单车和地铁出行数据，采用随机森林（RF）和地理加权回归（GWR）模型，分析了共享单车使用与社会经济变量、土地利用因子、交通基础设施和地铁特征等解释变量之间的非线性关系和空间异质性。在此基础上，提出了一种新的相似性度量——动态时间扭曲（Dynamic Time Warping， DTW），基于各车站的骑车出行时间模式对地铁站进行分类。因此，建立了四个具有不同模式的自行车和骑行的地铁站群。结果表明，在不同的地铁车站群中，决定因素的重要性及其与骑车出行的关系存在显著差异。本研究提出了自行车骑行的细粒度分析框架，为车站功能分类提供理论和实证支持。

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引用次数: 0

The impact of perceived walking accessibility on willingness to walk: evaluating different assessment methods 步行可达性对步行意愿的影响：不同评估方法的比较

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2026-04-01 Epub Date: 2025-11-06 DOI: 10.1016/j.tbs.2025.101173

Cong Qi , Jonas De Vos , Yibang Zhang , Xiucheng Guo

Accurately assessing perceived walking accessibility is essential for analysing its impact on people’s willingness to walk and walking behaviour. However, limited research has analysed and compared different assessments of perceived walking accessibility. This paper uses survey data from Nanjing’s central area to build binary logit models and analyse the impact of perceived walking accessibility on willingness to walk. Four different assessment methods are employed: the perceived accessibility scale, perceived walkability, overall perceived walking accessibility, and perceived impedance. The results show that perceived walking time is the most effective method for assessing perceived walking accessibility to specific locations, with the highest degree of explanatory power for willingness to walk. Older people, those unfamiliar with the city centre and those who arrive there by car or bicycle are less likely to walk in the central area. Perceived walking time is the primary factor influencing both enthusiastic walkers and reluctant walkers, while actual walking time primarily influences conditional walkers. Land use type at survey point has no significant effect on willingness to walk. These findings are valuable for designing an appropriate walking environment in the city centre and for encouraging walking by improving people’s perceived walking accessibility.

准确评估感知步行可达性对于分析其对人们步行意愿和步行行为的影响至关重要。然而，有限的研究分析和比较了感知步行可达性的不同评估。本文利用南京市中心城区的调查数据，建立二元logit模型，分析感知步行可达性对步行意愿的影响。采用感知可达性量表、感知步行可达性、整体感知步行可达性和感知阻抗四种不同的评价方法。结果表明，感知步行时间是评估特定地点感知步行可达性的最有效方法，对步行意愿的解释能力最高。老年人、不熟悉市中心的人以及开车或骑自行车到达市中心的人不太可能在市中心步行。感知步行时间是影响热心步行者和不情愿步行者的主要因素，而实际步行时间主要影响有条件步行者。调查点土地利用类型对步行意愿的影响不显著。这些发现对于在城市中心设计合适的步行环境以及通过改善人们感知的步行可达性来鼓励步行具有重要价值。

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引用次数: 0

Miles with smiles: the role of e-cargo bikes in facilitating new personal and family-oriented travel and relevant beyond-utility motivations 微笑里程：电动货运自行车在促进以个人和家庭为导向的新型旅行中的作用，以及相关的超越实用性的动机

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2026-04-01 Epub Date: 2025-12-23 DOI: 10.1016/j.tbs.2025.101217

Labib Azzouz , Christian Brand , Noel Cass , Ian Philips

E-cargo bikes (ECBs) can play a crucial role in the transition to sustainable transport. Existing research primarily focuses on ECBs in sharing schemes and urban delivery, with limited attention to domestic use. Most studies emphasize mode substitution, often overlooking motivations unique to ECBs and beyond-utility travel motivations. Critically, little is known about ECBs’ role in generating new travel demand. This study explores how ECBs generate new trips, focusing on individual and household motivations that extend beyond purely utilitarian purposes. Trials were conducted with 49 households across three cities: Leeds, Oxford, and Brighton. A mixed-methods approach was employed, emphasizing qualitative data from interviews and supplemented with quantitative insights from travel diaries.

Findings indicate that ECBs enhanced accessibility, leading to increased travel distance and frequency, and enabling travelers to ‘do more.’ Their capacity to transport children and bulky items unlocked induced and latent demand, facilitating trips that otherwise would not have occurred. Beyond utility, ECBs fostered new solo and family travel shaped by a range of intrinsic motivations. They promoted well-being, offered therapeutic outdoor experiences, disrupted daily routines, and supported personal growth, freedom, and autonomy. Caregivers particularly valued ECBs for the control, spontaneity, and flexibility they provided in managing complex household schedules. Parents’ and children’s enjoyment, curiosity, and sense of adventure encouraged additional travel, transforming routine journeys into playful and memorable family experiences. New ECB travel enhanced family bonding, strengthened intra-household cohesion, and increased children’s willingness to participate in activities that might otherwise have been resisted. Households used ECBs to cultivate sustainable travel identities, model pro-environmental behaviors, and instill active mobility norms in children.

The paper reframes induced demand and advances research on travel behavior and motivations. It provides valuable insights for policymakers, researchers, and societies, positioning ECBs as a distinct mode in the transition to sustainable mobility.

电动货运自行车（ECBs）可以在向可持续交通的过渡中发挥至关重要的作用。现有的研究主要集中在共享计划和城市运输中的ECBs，对家庭使用的关注有限。大多数研究强调模式替代，往往忽略了欧洲央行独有的动机和超越效用的旅行动机。关键是，人们对欧洲央行在创造新的旅游需求方面所起的作用知之甚少。本研究探讨了ecb如何产生新的旅行，重点关注超越纯粹功利目的的个人和家庭动机。试验在三个城市的49个家庭中进行：利兹、牛津和布莱顿。采用混合方法，强调来自访谈的定性数据，并辅以来自旅行日记的定量见解。研究结果表明，ecb增强了可达性，导致旅行距离和频率增加，并使旅行者“做更多的事情”。他们运送儿童和大件物品的能力释放了潜在的需求，为原本不会发生的旅行提供了便利。除了实用性之外，欧洲央行还催生了由一系列内在动机塑造的新的个人和家庭旅行。它们促进了幸福感，提供了治疗性的户外体验，打乱了日常生活，并支持了个人成长、自由和自主。照顾者特别重视ecb，因为它们在管理复杂的家庭安排时提供了控制性、自发性和灵活性。父母和孩子的享受、好奇心和冒险感鼓励了额外的旅行，将常规旅行转变为有趣和难忘的家庭体验。欧洲央行的新旅行增强了家庭纽带，加强了家庭内部凝聚力，并提高了儿童参与活动的意愿，否则这些活动可能会受到抵制。家庭使用ecb来培养可持续的旅行身份，示范亲环境行为，并向儿童灌输积极的移动规范。本文重构了诱导需求，推进了旅游行为和动机的研究。它为政策制定者、研究人员和社会提供了有价值的见解，将ecb定位为向可持续交通过渡的独特模式。

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引用次数: 0

Rail transit and travel satisfaction: Evidence from a natural experiment in Wuhan 轨道交通与出行满意度：来自武汉自然实验的证据

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2026-04-01 Epub Date: 2025-12-20 DOI: 10.1016/j.tbs.2025.101211

Zhenhua Li , Yi Lu , Jingjing Wang , Yihao Wu

The impact of rail transit infrastructure on residents’ travel satisfaction and subjective well-being has gained increasing attention among researchers and policymakers. However, few studies have used longitudinal data to analyze the causal effects of rail transit systems on travel satisfaction and its underlying mechanisms. This study employed a natural experiment approach, using two waves of survey data (2020 & 2021) from 422 participants in Wuhan, China, to assess the effects of a newly opened subway line on travel satisfaction. Applying a mixed-effects difference-in-differences (DID) method, we found that the new subway line significantly improved residents’ travel satisfaction after accounting for socio-demographic and travel attitude covariates. Mediation analysis revealed that this improvement was primarily driven by increased perceived accessibility to downtown and transit stops or stations, as well as a reduction in the number of out-of-home activities on weekends. Heterogeneous analysis indicated that the subway’s benefits are more pronounced among females, individuals under 60 years old, and those from middle-income households. These findings provide new causal evidence on the link between rail transit infrastructure and travel satisfaction, deepening our understanding of this complex relationship and offering practical insights for formulating strategies to improve urban residents’ quality of life.

轨道交通基础设施对居民出行满意度和主观幸福感的影响越来越受到研究者和决策者的关注。然而，很少有研究利用纵向数据分析轨道交通系统对出行满意度的因果关系及其潜在机制。本研究采用自然实验方法，使用来自中国武汉422名参与者的两波调查数据（2020 & 2021）来评估新开通的地铁线路对旅行满意度的影响。运用混合效应差分法（mixed-effects difference-in-difference， DID），我们发现在考虑社会人口统计学和出行态度协变量后，新地铁线路显著提高了居民的出行满意度。中介分析显示，这种改善主要是由于到市中心和公交站点或车站的可达性增加，以及周末外出活动数量的减少。异质性分析表明，地铁的好处在女性、60岁以下的个体和中等收入家庭中更为明显。这些发现为轨道交通基础设施与出行满意度之间的联系提供了新的因果证据，加深了我们对这种复杂关系的理解，并为制定改善城市居民生活质量的策略提供了实用的见解。

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引用次数: 0

Meet me halfway – Disentangling the factors affecting leisure joint destination choice 我们各让一步——拆解影响休闲联合目的地选择的因素

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2026-04-01 Epub Date: 2025-11-12 DOI: 10.1016/j.tbs.2025.101175

Joanna Ji , Benjamin Gramsch-Calvo , Kay W. Axhausen , Rolf Moeckel , Giancarlos Parady

This study investigates the factors that influence joint-leisure activities and travel between dyads (pairs of friends, family or acquaintances). We draw on a special dataset of self-reported frequently visited leisure destinations conducted in Zurich, and estimate two discrete choice models that consider relationship attributes, such as relationship time length, strength and gender homophily. The first model analyzes home-visits, as the probability of a person hosting a social activity at their place; while the second model is an out-of-home destination choice that quantifies the impact of relationship attributes on the distance traveled for social activities. The findings show that long relationships, (relationship time length

>

7 years), have a higher probability of hosting social activities by 3.87 percentage points, and having a strong relationship (when survey respondent can draw on

\geq 3

expressive resources from the other person) results in higher probability of hosting by 10.5 percentage points. For social activities outside the home, strong ties (

\geq 3

expressive resources from the other person) travel 0.88 km farther on average, and long ties (

> 7

years) 1.54 km farther, relative to weak (

<

3 expressive resources) and short (

\leq 7

years) ties, respectively. However, dyads in a relationship that is both long and strong travel an average of 3.18 kilometers extra than those in relationships that are neither long nor strong, showing that these relationship attributes have an even higher impact when combined.

本研究探讨影响二人（朋友、家人或熟人）共同休闲活动和旅游的因素。我们利用在苏黎世进行的自我报告的经常访问的休闲目的地的特殊数据集，并估计了两个考虑关系属性的离散选择模型，如关系时间长度，强度和性别同一性。第一个模型分析家访，作为一个人在他们的地方举办社会活动的概率；而第二个模型是一个外出目的地选择，量化了关系属性对社会活动旅行距离的影响。研究结果表明，长期的关系（关系时间长度>； 7年）主办社交活动的概率高出3.87个百分点，而牢固的关系（当被调查者可以从对方那里获得≥3种表达资源）主办社交活动的概率高出10.5个百分点。在家庭以外的社会活动中，强关系（来自他人的表达资源≥3个）比弱关系（来自他人的表达资源≤3个）和短关系（来自他人的表达资源≤7年）平均多走了0.88公里，长关系（7年）平均多走了1.54公里。然而，在一段既长又牢固的关系中的二人组比那些既不长也不牢固的关系中的二人组平均多旅行3.18公里，这表明这些关系属性在结合起来时会产生更大的影响。

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引用次数: 0

Changes in travel satisfaction during the day: How pre- and post-trip activities affect travel satisfaction 白天旅行满意度的变化：旅行前后活动如何影响旅行满意度

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2026-04-01 Epub Date: 2025-11-15 DOI: 10.1016/j.tbs.2025.101193

Qi Wang , Na Ta

Travel satisfaction is a crucial factor in evaluating residents’ subjective perceptions of the transportation system and travel experience, as well as in formulating traffic policies. However, the factors that influence travel satisfaction remain controversial. In previous studies, scholars have focused only on travel behavior and neglected the effects of travel-related activity characteristics. This study aims to address this knowledge gap by exploring the influences of activities before and after trips on trip characteristics and travel satisfaction, using a GPS-facilitated activity diary survey conducted in the Shangdi-Qinghe area of Beijing in 2012. Two structural equation models were constructed to examine the different impacts of activity categories and locations. The results indicate that pre- and post-trip activity characteristics exert both direct and indirect influences on travel satisfaction, with the indirect effects mediated by travel behavior characteristics being more pronounced. Pre-trip recreation activities and post-trip activities at flexible places have direct positive effects on travel satisfaction. Public transit travel and trip duration are important mediators. This study highlights the importance of considering activity-travel interactions in travel-related research.

出行满意度是评价居民对交通系统和出行体验的主观感受以及制定交通政策的关键因素。然而，影响旅游满意度的因素仍然存在争议。在以往的研究中，学者们只关注旅行行为，而忽略了旅行相关活动特征的影响。本研究旨在通过2012年在北京上地-清河地区进行的gps辅助活动日记调查，探讨旅行前后活动对旅行特征和旅行满意度的影响，从而解决这一知识空白。构建了两个结构方程模型来考察活动类别和地点的不同影响。结果表明，旅游前、后活动特征对旅游满意度既有直接影响，也有间接影响，其中旅游行为特征介导的间接影响更为显著。出行前游憩活动和出行后灵活场所活动对旅行满意度有直接的正向影响。公共交通出行和出行时间是重要的调节因子。本研究强调了在旅行相关研究中考虑活动-旅行互动的重要性。

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引用次数: 0

Transition to electric motorcycle-based ride-hailing: User heterogeneity, perception, and pro-environmental habits 向基于电动摩托车的网约车过渡：用户异质性、感知和环保习惯

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2026-04-01 Epub Date: 2025-11-11 DOI: 10.1016/j.tbs.2025.101180

Muhammad Zudhy Irawan , Muhamad Rizki , Prawira Fajarindra Belgiawan , Tri Basuki Joewono , Hironori Kato

The adoption of electric motorcycles (EM) for ride-hailing offers a promising solution to sustainability concerns in Southeast Asia. However, a gap remains in understanding the factors that influence user preferences for electric motorcycle-based ride-hailing (e-MBRH). This study aims to fill this gap by analyzing data from 418 MBRH customers in Yogyakarta, Indonesia. Using a latent class cluster analysis (LCCA), this study first categorizes MBRH customers according to their trip purposes, frequency, daily distance, and duration of use. It then employs an ordered hybrid choice model (OHCM) to investigate how socioeconomic factors, motorcycle availability, experience with EM, perceptions of EM, and post-COVID-19 pro-environmental habits affect the adoption of e-MBRH in each category. The LCCA results reveal that three groups of MBRH users exist: those who use it for irregular support trips, those who use it regularly for mandated activities, and those who use it occasionally for discretionary or maintenance activities. Notably, the OHCM results indicate that the users categorized in the last group are the most likely to adopt e-MBRH because their decisions are significantly influenced by symbolic and performance value, convenience, and their post-COVID-19 shift toward pro-environmental habits. To further encourage adoption among that group, effective policies should foster prestige- and performance-driven marketing campaigns, positioning e-MBRH as the premier choice for innovative, environmentally conscious urban mobility.

采用电动摩托车（EM）进行网约车为东南亚的可持续性问题提供了一个有希望的解决方案。然而，在了解影响用户对基于电动摩托车的叫车服务（e-MBRH）偏好的因素方面仍然存在差距。本研究旨在通过分析来自印度尼西亚日惹市418名MBRH客户的数据来填补这一空白。本研究首先使用潜在类聚类分析（LCCA），根据出行目的、频率、每日距离和使用时间对MBRH客户进行分类。然后，采用有序混合选择模型（OHCM）来调查社会经济因素、摩托车可用性、新兴市场经验、对新兴市场的看法以及covid -19后的环保习惯如何影响每个类别中e-MBRH的采用。LCCA结果显示，MBRH用户存在三种群体：那些使用它进行不定期支持旅行的人，那些定期使用它进行强制性活动的人，以及那些偶尔使用它进行自由裁量或维护活动的人。值得注意的是，OHCM的结果表明，最后一组用户最有可能采用e-MBRH，因为他们的决策受到象征和性能价值、便利性以及他们在covid -19后向亲环境习惯转变的显著影响。为了进一步鼓励这一群体的采用，有效的政策应促进以信誉和业绩为导向的营销活动，将e-MBRH定位为创新的、具有环保意识的城市交通的首选。

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