Unraveling Heterogeneity in Online Shopping and Travel Behavior Through Latent Class Modeling

Transportation Research Record Journal of the Transportation Research Board, Год журнала: 2024, Номер unknown

Опубликована: Март 30, 2024

While existing literature has extensively explored the impact of online shopping on travel behavior, few studies have undertaken segmentation analysis to uncover hidden behavioral heterogeneity. This study fills this gap by addressing heterogeneity and identifying distinct shopper segments based behaviors, with a focus product types. Data collected in November December 2021 from 1,747 shoppers Florida were analyzed using Latent Class Analysis (LCA) covariates. Sociodemographic residential characteristics, COVID-19 influences, attitudes, perceptions channel-specific factors served as active inactive covariates predict class membership. Our model identified six classes shoppers, short-distance dual-channel representing largest (28.4%) exclusive smallest (6.2%). Dual-channel shopaholics, overrepresented Gen Zers, Millennials, Blacks, workers, exhibited high average monthly vehicle miles traveled (VMT) across all types strong potential for complementary behavior. Conversely, members silent generation, those who live alone, no vehicle, do not enjoy shopping, demonstrated substitutive In general, single-channel showed lower VMT than their counterparts These findings contribute deeper understanding offering insights more accurate quantification net traffic environmental impacts e-commerce. Additionally, they provide valuable considerations designing segment-specific policies aimed at minimizing maximizing shopping.

Язык: Английский

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Assessing the willingness to pay for Mobility-as-A-Service: An Agent-Based approach

Case Studies on Transport Policy, Год журнала: 2024, Номер 17, С. 101221 - 101221

Опубликована: Май 22, 2024

Язык: Английский

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Optimizing mobility resource allocation in multiple MaaS subscription frameworks: a group method of data handling-driven self-adaptive harmony search algorithm

Annals of Operations Research, Год журнала: 2024, Номер unknown

Опубликована: Авг. 23, 2024

Язык: Английский

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Segmenting the potential users of MaaS by combining latent class cluster analysis and structural equation modeling

Sustainable Cities and Society, Год журнала: 2024, Номер 114, С. 105764 - 105764

Опубликована: Авг. 23, 2024

Язык: Английский

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Investigating the unobserved heterogeneity in passenger satisfaction with Mobility-as-a-Service (MaaS) bundles

Transportation Research Part F Traffic Psychology and Behaviour, Год журнала: 2024, Номер 109, С. 50 - 63

Опубликована: Дек. 5, 2024

Язык: Английский

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From words to deeds: when digital app acceptance turns into sustainable mobility behaviours. Methodologies and insights from MaaS experiences

Urban Planning and Transport Research, Год журнала: 2024, Номер 13(1)

Опубликована: Дек. 7, 2024

Mobility-as-a-Service (MaaS) is typically framed as a tool that offers multi-modal transportation solutions through an integrated digital interface, playing pivotal role in supporting the sustainable transition within Smart Cities. However, its applications and user acceptance are often assessed from narrow, mobility-focused perspective, which tends to reduce MaaS experience purely travel-related service – thus overlooking broader potential. Users' preferences, willingness-to-adopt, willingness-to-pay commonly evaluated based on factors such performance, fare schemes, convenience. when considering deeper mindset behavioral shifts required for adoption of more modes, tools implemented must not only be functional but they also resonate with how users perceive interact them. These interactions crucial success widespread solutions. This paper reviews primary methodologies used evaluate acceptance, highlights their strengths limitations, explores platforms facilitating shift toward mobility. The main focus will represented by potential benefits successful implementation can arise optimizing users' experiences, particularly integration nudging rewarding systems designed influence individual behavior.

Язык: Английский

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Understanding Congestion Risk and Emissions of Various Travel Behavior Patterns Based on License Plate Recognition Data

Sustainability, Год журнала: 2025, Номер 17(2), С. 551 - 551

Опубликована: Янв. 13, 2025

Understanding vehicle travel behavior patterns is crucial for effectively managing urban traffic congestion and mitigating the associated risks excessive emissions. Existing research predominantly focuses on commuting patterns, with limited attention given to spatiotemporal characteristics of other behaviors, sparse investigation into emissions these patterns. To address this gap, present study examines various their emissions, using one week License Plate Recognition (LPR) data from megacity expressway network. First, we classify vehicles different modes based features extracted LPR propose a scalable mode recognition method suitable large-scale applications. We then assess each estimate resulting congestion. The findings reveal notable differences in among modes, bimodal distribution influenced by temporal rhythm flow. Furthermore, although commercial constitute only one-third total population, attributed are comparable those privately owned vehicles. This suggests that focusing exclusively may underestimate both results not deepen our understanding relationship between individual but also support optimization personal time health management, providing foundation development personalized proactive demand management strategies.

Язык: Английский

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Exploring the potential adoption of Mobility-as-a-Service in Beijing: A spatial agent-based model

Transportation Research Part A Policy and Practice, Год журнала: 2025, Номер 194, С. 104430 - 104430

Опубликована: Март 1, 2025

Язык: Английский

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Factors Influencing MaaS Uptake in the Context of Developing Countries Based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) Framework

Lecture notes in intelligent transportation and infrastructure, Год журнала: 2025, Номер unknown, С. 723 - 736

Опубликована: Янв. 1, 2025

Язык: Английский

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In-depth investigation into the hierarchical causal chain of fatal crashes between vulnerable road users and single motor vehicle

Traffic Injury Prevention, Год журнала: 2025, Номер unknown, С. 1 - 9

Опубликована: Апрель 4, 2025

Crash pattern recognition and characterization are essential for reducing the damage vulnerable road users (VRUs) suffer in motor vehicle crashes. However, traditional methods provide an incomprehensive understanding of crash causality impacts VRU-vehicle interactions. Therefore, this study aims to a reasonable various types To achieve goal, three-layer causal analysis framework was developed. The layers consist physical states (mainly environmental human factors), interactions (pre-crash behaviors drivers VRUs), First, latent class cluster sequence were used identify interactive behavior patterns pairs, respectively. Besides, oversampling algorithm proposed assist Granger test uncovering relationships between pre-crash patterns. Finally, Sankey diagrams utilized compare analyze path. results show that single consecutive crashes have nine eleven typical scenarios, respectively, excluding considering potential chains. These chains new scenarios. It found personal subjective factors primarily influence drivers, while VRUs, traffic environment plays crucial role. Noteworthily, highest risk only associated with chain where vehicles unable brake time. Clarifying interaction is essential, which can help finding critical causes fatal identified VRU violations inability time as determinants severity both Accordingly, targeted safety interventions proposed, including enhancements pedestrian crossing infrastructure improvements braking systems mitigate risk.

Язык: Английский

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