Travel Behaviour and Society最新文献

{"title":"Propagating synthetic populations with dynamic Bayesian networks: a framework for long-horizon demographic forecasting","authors":"Mohammad Mehdi Oshanreh ,&nbsp;Nazmul Arefin Khan ,&nbsp;Don MacKenzie","doi":"10.1016/j.tbs.2025.101226","DOIUrl":"10.1016/j.tbs.2025.101226","url":null,"abstract":"<div><div>This study presents a dynamic demographic microsimulator using dynamic Bayesian networks to forecast long–term changes in household and individual life events. Leveraging longitudinal Panel Study of Income Dynamics (PSID) data, two networks for individuals and households were modeled to simulate transitions in employment, income, education, marriage, childbirth, leaving the parental home, home ownership, mortality, and household formation or dissolution. Across 1,000 simulation runs spanning 24  years, household–level outcomes remain highly accurate and individual–level predictions reasonable. Although accuracy naturally declines with projection horizon, performance remains promising at both levels. This study addresses a key limitation of existing population synthesis models, which typically generate only a single static snapshot of the population. By introducing a framework that propagates cross-sectional outputs into the future, the microsimulator enables the tracking of demographic evolution over time, enhances realism in population-based simulations, and supplies credible inputs to agent-based travel demand models.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101226"},"PeriodicalIF":5.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Who waits longer to pick you up? behavioral and spatial inequities in ride-hailing pickup time based on real-world platform data","authors":"Jiayan Zhang ,&nbsp;Jiao Jiao ,&nbsp;Xiang Wang ,&nbsp;Inhi Kim ,&nbsp;Tianqi Gu","doi":"10.1016/j.tbs.2025.101224","DOIUrl":"10.1016/j.tbs.2025.101224","url":null,"abstract":"<div><div>Pickup time at the post-matching stage is a critical but often overlooked dimension of service equity in ride-hailing systems. While existing studies often rely on modeled or inferred estimates of wait time based on distance, traffic conditions, or simulation outcomes, few have access to actual pickup time records linked to real-name ride-hailing transactions. This study draws on a rare, real-world dataset comprising platform-recorded pickup durations and real-name verified driver profiles from Suzhou, China. Using a Geographically Weighted Random Forest (GWRF) model with SHAP interpretation, we examine how pickup responsiveness varies across driver characteristics (gender, age, residency), geography (central vs. peripheral zones), and time (weekday vs. holiday). Our findings show that young, local male drivers tend to achieve faster pickups due to broader geographic coverage and incentive sensitivity, while older, non-local female drivers face slower pickups, especially under uncertain or high-risk conditions. Moreover, spatial and temporal patterns reveal that conventional assumptions—such as the edge disadvantage or vehicle density effects—do not hold uniformly across groups. These findings suggest that pickup time is a socially embedded outcome rather than a purely algorithmic one. Building on this perspective, we propose behavior-aware dispatch strategies, targeted driver support programs, and regulatory design implications aimed at enhancing equity, inclusion, and responsiveness in ride-hailing governance.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101224"},"PeriodicalIF":5.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding the elements of the tourism accessibility chain","authors":"Francisco López-del-Pino ,&nbsp;José M. Grisolía ,&nbsp;Juan de Dios Ortúzar","doi":"10.1016/j.tbs.2025.101161","DOIUrl":"10.1016/j.tbs.2025.101161","url":null,"abstract":"<div><div>This study investigates how different components of the accessibility chain influence tourist destination choices, using a Hybrid Discrete Choice (HDC) model that integrates stated preferences and latent attitudinal constructs. Drawing on a sample of visitors to Gran Canaria, the results show that staff preparedness, accessible environments, and reliable information significantly affect destination choice, with staff training emerging as the most influential factor. The research is grounded in the Social Model of Disability, which views disability as a social construct, and the Capability Approach, which focuses on individuals’ freedom to live the lives they value. These frameworks reframe accessibility not as an isolated technical issue but as a systemic condition enabling or constraining effective participation. The study also adopts a Universal and Inclusive Design perspective within this framework, recognising human diversity as a central design parameter in tourism systems. The estimated model reveals substantial heterogeneity in preferences: individuals with direct or indirect experience of disability place greater importance on staff support and trustworthy information. At the same time, younger and non-disabled tourists prioritise price and location. By combining behavioural and attitudinal data, the study demonstrates the added value of HDC models for understanding how accessibility is cognitively evaluated and behaviourally enacted. The findings have practical implications for inclusive destination design. Rather than addressing accessibility through isolated improvements, tourism systems should adopt a chain-based approach, ensuring coherence across all stages of the travel experience. As societies age and accessibility becomes a strategic imperative, this model provides a transferable tool for evaluating service gaps and guiding inclusive policy design.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"42 ","pages":"Article 101161"},"PeriodicalIF":5.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145404750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel integrated machine learning and inferential modeling approach to explore non-linear effects of built environment on travel: a three-wave repeated cross-sectional study","authors":"Niaz Mahmud Zafri ,&nbsp;Ming Zhang","doi":"10.1016/j.tbs.2025.101146","DOIUrl":"10.1016/j.tbs.2025.101146","url":null,"abstract":"<div><div>This study investigates the dynamic effects of the built environment on travel in Austin, Texas, over a 20-year period. Using three waves of household travel surveys from 1997, 2006, and 2017, the research employs a repeated cross-sectional approach to address the limitations of traditional longitudinal and cross-sectional studies, and to more accurately estimate effect sizes. Methodologically, we introduce a novel integration of machine learning and inferential modeling to uncover non-linear relationships and threshold effects of the built environment characteristics on travel. Using Gradient Boosted Decision Trees (GBDT) and Partial Dependence Plots (PDPs), we first identify optimal threshold points in the relationships, which are then incorporated into piecewise multilevel models.</div><div>Findings from the study reveal that the built environment serves as a sustainable tool for managing travel in the long term, contributing 50 % or more to the total feature importance in predicting individual travel—surpassing the combined effects of personal and household characteristics. Improved transit accessibility, enhanced local and regional accessibility, higher population and employment densities, and greater diversity are all associated with significant reductions in travel—particularly within their identified thresholds—though the magnitude of their influence varies across time periods and shows diminishing marginal returns.</div><div>These findings highlight the potential of smart growth policies—such as expanding transit accessibility, promoting high-density and mixed-use development, and discouraging single-use development and peripheral sprawl—as effective strategies to reduce car dependency and manage travel demand. Moreover, the study demonstrates that the proposed integrated approach can effectively capture complex non-linear effects while enhancing flexibility and interpretability, reducing researcher bias, and enabling statistical inference—ultimately providing more robust and policy-relevant insights.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"42 ","pages":"Article 101146"},"PeriodicalIF":5.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the determinants of electric motorcycle adoption and changes in travel behavior: Insights from Indonesia","authors":"Harits Rachmat Hidayat ,&nbsp;Muhammad Zudhy Irawan ,&nbsp;Muhamad Rizki ,&nbsp;Ilma Aurarisa","doi":"10.1016/j.tbs.2025.101121","DOIUrl":"10.1016/j.tbs.2025.101121","url":null,"abstract":"<div><div>Electric motorcycles (EMs) have garnered increasing attention as a cleaner alternative to gasoline-powered vehicles, offering substantial potential for reducing air pollution. While recent research has examined factors influencing EM adoption, limited studies have linked psychological and demographic determinants to actual usage behavior and mode shifts, particularly within the Indonesian context. To bridge this gap, the study extends the UTAUT2 framework by incorporating perceived safety, environmental concern, and policy measures. It examines both EM adoption intentions and resulting changes in travel behavior. Data were gathered from 445 EM users in Jakarta, Indonesia, and analyzed using Partial Least Squares–Structural Equation Modeling. Findings indicate that performance expectancy, social influence, hedonic motivation, habits, and perceived safety significantly influence the intention to adopt EMs. This intention, in turn, increases EM usage, reduces dependence on private vehicles, and complements public transport. Demographic factors moderate key relationships: age affects how habits shape EM usage, income and education impact how performance expectancy influences intention. Education also strengthens the role of perceived safety and hedonic motivation on intention. User satisfaction further reinforces the connection between intention and actual usage. Expanding charging infrastructure, improving battery technology, and promoting stylish design and user testimonials are recommended to accelerate adoption.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"42 ","pages":"Article 101121"},"PeriodicalIF":5.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144903420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Defining the role of mobility as a service – A discrete choice framework incorporating missing data","authors":"T.M. Rahul ,&nbsp;Bh. Aaditya ,&nbsp;Nikhil","doi":"10.1016/j.tbs.2025.101110","DOIUrl":"10.1016/j.tbs.2025.101110","url":null,"abstract":"<div><div>Mobility as a Service (MaaS) is an emerging concept that integrates various sustainable and shared modes using a digital interface. Currently, it is promoted as an option that encourages shift from private vehicles. Its preference among private vehicle non-users is unexplored. The current study models the willingness of individuals to choose a Maas package consisting of Mass Rapid Transit System (MRTS), bus and shared bicycle options in the city of Chandigarh, India using an Integrated Choice and Latent Variable (ICLV) framework. It addresses the issue of missing income, in the data collected, by assuming the income variable to be latent in the ICLV model. The structural and measurement equations of the latent income variable are specified using novel error formulations having either normal or lognormal distributions. Among the models estimated, multiplicative models with lognormal error distribution in the structural and measurement equations were observed to result in a better fit than the conventional model with normal error distributions in both structural and measurement equations. Across models, income and environmental consciousness were found to significantly increase the preference for MaaS. Further, our results highlighted a need for improving the quality of existing shared modes and public transport that are included in the MaaS subscription. The preference for MaaS among low-income respondents, and females, who do not have a driving license, indicated that MaaS can be considered as an option to address the issue of transportation inequity, especially for people having low chances of owning a private vehicle.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"42 ","pages":"Article 101110"},"PeriodicalIF":5.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144842179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Social influences in the context of parking: An exploratory study using a stated choice approach","authors":"Peter van der Waerden ,&nbsp;Jaap van der Waerden","doi":"10.1016/j.tbs.2025.101109","DOIUrl":"10.1016/j.tbs.2025.101109","url":null,"abstract":"<div><div>This paper presents an exploratory study of social influences in the context of car drivers’ parking choice behavior. The influence of parking attributes and a car driver’s social network is measured using a stated choice approach. In an online questionnaire various hypothetical parking facilities are presented to respondents. Four attributes are included to describe parking facilities: parking tariff, walking distance between parking facility and final destination, type of parking facility, and security level. The social network of car drivers is represented by family, friends, colleagues, and others. The evaluations of more than 600 respondents are analyzed using a mixed logit model. The model analysis shows that when choosing a parking facility, car drivers are not only influenced by parking attributes but also by their social network.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"42 ","pages":"Article 101109"},"PeriodicalIF":5.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144826494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bus drivers’ intention to accept level 4 autonomous buses in ethical dilemmas: An extended technology acceptance model","authors":"Yu-Kai Huang ,&nbsp;Jyun-Kai Liang ,&nbsp;Chung-Cheng Lu","doi":"10.1016/j.tbs.2025.101143","DOIUrl":"10.1016/j.tbs.2025.101143","url":null,"abstract":"<div><div>As autonomous driving technology progresses in the private vehicle sector, research on autonomous buses is gaining global attention. Most studies currently focus on passenger needs and attitudes, with less attention given to the drivers who directly operate these vehicles. This study examines the attitudes and behavioral intentions of current bus drivers under different operational scenarios using Level 4 autonomous buses. By extending the Technology Acceptance Model to include trust and compatibility and integrating it with the Integrative Ethical Decision-Making Framework (IEDMF), the study analyzes drivers’ intentions to use AI systems in moral dilemmas. This theoretical integration provides a comprehensive understanding of how rational and intuitive moral reasoning influence technology acceptance in ethical contexts. Structural equation modeling indicates that perceived usefulness and ease of use are critical factors influencing drivers’ operations of autonomous buses in such contexts. The research also reveals significant differences in decision-making behaviors between urban and intercity bus drivers in moral dilemmas, with urban drivers more likely to rely on AI for ethical judgment and prioritize pedestrian safety in critical situations. These findings highlight the importance of targeted training programs: urban bus drivers should focus on urban safety and ethical considerations of pedestrian areas, whereas intercity drivers should enhance their strategies for managing long-distance driving ethics and highway dilemmas. Furthermore, this study underscores the necessity of investing in robust AI systems capable of making ethical decisions under pressure and advocates for integrating diverse ethical frameworks into these systems to better reflect societal values and norms, providing guidance for the future operation of autonomous buses.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"42 ","pages":"Article 101143"},"PeriodicalIF":5.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of sea level rise on aging population’s accessibility to essential services in Honolulu, Hawaii","authors":"Dingyi Liu,&nbsp;Suwan Shen","doi":"10.1016/j.tbs.2025.101139","DOIUrl":"10.1016/j.tbs.2025.101139","url":null,"abstract":"<div><div>With demographic shifts showing an increasing elderly population and growth in low-elevation coastal zones, this study investigates the impacts of sea level rise on elderly accessibility to essential services in Honolulu, Hawai’i, exploring the question how sea level rise will affect road accessibility to essential services for the elderly.</div><div>Using the Cohort Change Ratio (CCR), we project the elderly population in each Traffic Analysis Zone (TAZ) over the coming decades. The study identifies road segments and essential facilities at risk under various sea-level rise scenarios (1.1 feet and 2.0 feet) and analyzes network connectivity from each TAZ to essential services.</div><div>Results indicate that while infrastructure damage is moderate, accessibility to essential services in vulnerable communities will be significantly impacted, even under 1.1 feet rise. Some areas with high elderly populations could be isolated due to transportation bottlenecks. These findings underline the urgent need for transportation network planning to ensure connectivity for vulnerable elderly populations and suggest that long-term land use planning is crucial for climate change adaptation. The methodology and insights from this study are applicable to other coastal regions and can inform adaptation planning practices nationwide.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"42 ","pages":"Article 101139"},"PeriodicalIF":5.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spherical fuzzy evidential reasoning for vehicle-to-grid enabled electric vehicle adoption: A data-driven analysis of public perception","authors":"Muhammad Zahid ,&nbsp;Ezzeddin Bakhtavar ,&nbsp;Salim Khoso ,&nbsp;Syed Naveel Hussain ,&nbsp;Rehan Sadiq ,&nbsp;Kasun Hewage","doi":"10.1016/j.tbs.2025.101169","DOIUrl":"10.1016/j.tbs.2025.101169","url":null,"abstract":"<div><div>The successful adoption of Vehicle-to-Grid (V2G) technology depends on public awareness, infrastructure readiness, and policy support. This study presents a Spherical Fuzzy Set-Evidential Reasoning (SFS-ER) framework to assess public perceptions of V2G adoption, leveraging survey data from 729 respondents in Okanagan, British Columbia (BC), Canada. The study quantifies belief structures through three dimensions: True Belief (<em>m_T</em>), False Belief (<em>m_F</em>), and Uncertainty (<em>m_U</em>), and computes utility scores to evaluate adoption likelihood. K-Means clustering with the Elbow Method identifies three distinct respondent groups: Supporters (high belief and adoption potential), Skeptical (moderate false beliefs), and Resistant (high skepticism and reluctance toward adoption). The findings reveal that awareness (<em>m_T</em> = 0.78) and interest (<em>m_T</em> = 0.75) are the strongest predictors of adoption, whereas familiarity alone has a limited impact. Higher-income and university-educated respondents demonstrate greater awareness, while apartment and townhouse residents face structural barriers due to limited charging infrastructure. Moreover, sensitivity analysis confirms that awareness-driven interventions can increase utility scores by 5.4 %. Based on the results, the key policy recommendations include expanding educational initiatives, implementing financial incentives, and integrating V2G-ready infrastructure in multi-unit dwellings.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"42 ","pages":"Article 101169"},"PeriodicalIF":5.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145441894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}