Case Studies on Transport Policy最新文献_第3页

Demystifying complexities in the adoption of hydraulic-powered personal rapid transit systems: a multi-stakeholder perspective 揭开采用液压动力个人快速交通系统的复杂性：多方利益相关者的视角

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-12-08 DOI: 10.1016/j.cstp.2025.101683

Muhammad Usman Ghani , Zheng Yonglai , Ahsan Waqas , Omrane Benjeddou , Hamad R. Almujibah

The emergence of Personal Rapid Transit (PRT) systems has provided a highly appealing solution to the challenges linked to urban mobility, including pollution, congestion, and access. Nevertheless, the global implementation of PRT systems is extremely limited, indicating a significant research void that must be elucidated by examining numerous factors and obstacles that influence the adopting such systems in urban environments. This study fills this void by employing a comprehensive multi-stakeholder approach—including a literature review and quantitative analysis to comprehend the complexities associated with PRT adoption. According to the findings, critical technological, environmental, economic, societal, and regulatory obstacles impede the implementation of PRT systems. Given the technological obstacles, integration with municipal infrastructure appeared to be the most critical factor, as indicated by the path coefficient value of 0.454, which significantly impacts adoption decisions. Additional important factors that fall within the purview of the path coefficient are economic and environmental considerations, which have respective path coefficients of 0.208 and 0.343. This is associated with a significant and tangible influence on the feasibility and reception of PRT systems. Stakeholders deemed the development of multifaceted planning and adaptive policy frameworks to emphasize the significance of regulatory support and public acceptability with path coefficients of 0.307 and 0.276, respectively. The study’s practical implications encompass urban planners, policymakers, and investors, particularly regarding utilizing collaborative strategies to surmount obstacles to adoption.

个人快速交通（PRT）系统的出现为城市交通带来的挑战提供了一个极具吸引力的解决方案，包括污染、拥堵和通道问题。然而，PRT系统的全球实施极为有限，这表明一个重大的研究空白，必须通过审查影响在城市环境中采用这种系统的众多因素和障碍来阐明。本研究通过采用全面的多利益相关者方法填补了这一空白，包括文献综述和定量分析，以理解与采用PRT相关的复杂性。根据调查结果，关键的技术、环境、经济、社会和监管障碍阻碍了PRT系统的实施。考虑到技术障碍，与市政基础设施的整合似乎是最关键的因素，路径系数值为0.454，显著影响采用决策。路径系数范围内的其他重要因素是经济和环境因素，其路径系数分别为0.208和0.343。这对PRT系统的可行性和接收产生了重大而切实的影响。利益相关者认为制定多方面的规划和适应性政策框架，以强调监管支持和公众可接受性的重要性，路径系数分别为0.307和0.276。该研究的实际意义包括城市规划者、政策制定者和投资者，特别是在利用合作战略克服采用障碍方面。

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引用次数: 0

How will electric, autonomous, and shared vehicles impact sustainable urban mobility? Professionals’ insights from Brazil 电动汽车、自动驾驶汽车和共享汽车将如何影响可持续的城市交通？巴西专业人士的见解

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-12-08 DOI: 10.1016/j.cstp.2025.101680

Anna Luíza Nobre Bezerra , Antônio Nélson Rodrigues da Silva

It was anticipated that the so-called “Mobility 4.0″ would introduce modifications to transport systems that could potentially influence mobility conditions provided by existing modes of transport. Nevertheless, it remains unclear how these changes will impact mobility in terms of its sustainability. This gap is particularly evident in countries such as Brazil, where this research was conducted. This study evaluated the prospective implications of selected mobility 4.0 developments (in particular, electric and autonomous vehicle technologies, and shared mobility) by examining 18 themes related to sustainable urban mobility. An online questionnaire was designed and distributed to professionals in the field. The questionnaire sought to categorize the most significant impacts within each theme using a 5-level Likert scale, ranging from very positive to very negative. Data analysis extracted from 320 valid responses provides empirical evidence that helps identify these technologies’ potential impacts on urban mobility’s sustainability. Depending on the theme, these impacts may be positive, negative, or neutral/undefined. It is noteworthy, for example, that electric vehicles and shared mobility have been evaluated very positively in relation to the theme Control of impacts on environment, which falls within the Environmental aspects domain. Overall, the level of knowledge demonstrated by the respondents did not significantly impact the results. However, when observed, this characteristic was notably marked among the respondents with advanced practical knowledge. Finally, in terms of policy recommendations, the outcomes suggest that policymakers must be prepared to constantly adapt policies based on changing technology, user behavior, and urban dynamics. Moreover, potential discrepancies in access to distinct socioeconomic groups are also a concern that must be addressed by policies, as these groups may have differing needs and expectations.

预计所谓的“机动性4.0″”将对运输系统进行修改，可能会影响现有运输方式提供的机动性条件。然而，目前尚不清楚这些变化将如何影响交通的可持续性。这一差距在巴西等国家尤其明显，巴西是进行这项研究的国家。本研究通过考察与可持续城市交通相关的18个主题，评估了选定的交通4.0发展（特别是电动和自动驾驶汽车技术，以及共享交通）的潜在影响。设计了一份在线问卷，并分发给该领域的专业人士。调查问卷试图使用5级李克特量表对每个主题中最重要的影响进行分类，范围从非常积极到非常消极。从320个有效回复中提取的数据分析提供了经验证据，有助于确定这些技术对城市交通可持续性的潜在影响。根据主题的不同，这些影响可能是积极的、消极的或中性的/未定义的。值得注意的是，例如，电动汽车和共享出行在环境影响控制主题方面得到了非常积极的评价，这属于环境方面的领域。总体而言，被调查者所展示的知识水平对结果没有显著影响。然而，当观察时，这一特征在具有高级实践知识的受访者中尤为明显。最后，在政策建议方面，研究结果表明，政策制定者必须做好准备，根据不断变化的技术、用户行为和城市动态不断调整政策。此外，在接触不同社会经济群体方面的潜在差异也是一个必须通过政策加以解决的问题，因为这些群体可能有不同的需求和期望。

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引用次数: 0

The rising vehicle counts and deteriorating air quality in Islamabad, Pakistan 巴基斯坦首都伊斯兰堡的机动车数量不断增加，空气质量不断恶化

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-12-07 DOI: 10.1016/j.cstp.2025.101684

Asif Hayat , Hifza Irfan , Hassan Shehzad , Sadia Haider , Muhammad Zaman

Rapid motorization in Pakistan has intensified air quality challenges, yet limited research has examined how vehicular growth contributes to environmental degradation and what institutional responses have emerged. This study investigates the linkages between rising vehicle numbers, weak regulatory enforcement and deteriorating air quality in Islamabad, Pakistan. Qualitative in-depth interviews were conducted with officials from the Capital Development Authority, Environmental Protection Agency and Islamabad Transport Authority to explores institutional capacities, policy implementation gaps and emerging strategies such as public transport expansion and electric vehicle promotion. Twelve participants were selected through purposive sampling, and the collected data were analysed thematically using MAXQDA software. The findings reveal that rapid growth in private vehicle ownership, combined with poorly maintained fleets and the absence of systematic inspection regimes, has accelerated atmospheric emissions in the capital. Institutional inertia, resource scarcity and socio-economic justifications for tolerating old vehicles further exacerbate the problem. While initiatives such as the Bus Rapid Transit system and planned electric vehicle policies signal potential, their scale remains insufficient. The current study contributes to debates on urban air quality governance in the Global South by highlighting how weak institutional frameworks and competing development priorities undermine environmental sustainability. It calls for integrated policy reforms, investment in sustainable public transport and robust enforcement mechanisms to mitigate transport-related emissions.

巴基斯坦的快速机动化加剧了空气质量挑战，然而，关于车辆增长如何导致环境退化以及出现了哪些制度性应对措施的研究有限。本研究调查了巴基斯坦伊斯兰堡车辆数量增加、监管执法不力和空气质量恶化之间的联系。对首都发展局、环境保护局和伊斯兰堡交通管理局的官员进行了定性深入访谈，以探讨机构能力、政策实施差距和新兴战略，如公共交通扩张和电动汽车推广。通过有目的抽样，选取12名参与者，利用MAXQDA软件对收集到的数据进行专题分析。调查结果显示，私人汽车保有量的快速增长，加上保养不善的车队和缺乏系统的检查制度，加速了首都的大气排放。体制惰性、资源匮乏和容忍旧车的社会经济理由进一步加剧了这一问题。虽然快速公交系统和计划中的电动汽车政策等举措显示出潜力，但它们的规模仍然不够。目前的研究通过强调薄弱的制度框架和相互竞争的发展优先事项如何破坏环境的可持续性，为全球南方城市空气质量治理的辩论做出了贡献。它呼吁进行综合政策改革，投资可持续公共交通，并建立强有力的执法机制，以减少与交通相关的排放。

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引用次数: 0

Territorial classification for mitigating socio-spatial inequalities in Fortaleza, Brazil: Advancing strategic LUTI planning towards a problem-oriented approach 缓解巴西福塔莱萨社会空间不平等的领土分类：以问题为导向的方法推进战略性城市道路交通规划

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-12-07 DOI: 10.1016/j.cstp.2025.101681

Francelino Franco Leite de Matos Sousa , Carlos Felipe Grangeiro Loureiro

Strategically assessing accessibility inequalities in urban contexts is pivotal for the sustainable land use and transportation integrated (LUTI) planning paradigm. This work introduces an innovative territorial classification methodology, focusing on problems of socio-spatial accessibility inequalities, essential for informing strategic objectives in urban planning and defining areas where policies should be prioritized to mitigate such inequalities. Applied to the city of Fortaleza, Brazil, the proposed methodology measures accessibility levels using a utility-based logsum-type indicator calculated with socioeconomic/land-use data and travel impedances from the TRANUS model simulations for past, present, and future scenarios. The findings highlight a chronic imbalance in the spatial distribution of economic activities and low-income households, alongside an increasing reliance on motorized modes for commuting. Through the hierarchization of urban space, we identify areas with potential to accommodate vulnerable populations, zones where low-income residential occupation should be discouraged due to unacceptable job accessibility conditions, and areas requiring integrated land-use and transport policies to improve access to work activities. This approach not only underscores the importance of addressing socio-spatial inequalities in LUTI planning but also provides a methodological basis for negotiating planning objectives and prioritizing critical areas across the urban territory, promoting more equitable access to opportunities.

战略性地评估城市环境中的可达性不平等对于可持续土地利用和交通一体化（LUTI）规划范式至关重要。这项工作引入了一种创新的地域分类方法，重点关注社会空间可达性不平等问题，这对于为城市规划中的战略目标提供信息和确定应优先考虑政策以减轻这种不平等的地区至关重要。该方法应用于巴西福塔莱萨市，使用基于效用的对数型指标来衡量可达性水平，该指标是根据过去、现在和未来情景的TRANUS模型模拟的社会经济/土地利用数据和旅行阻抗计算得出的。研究结果强调了经济活动和低收入家庭空间分布的长期不平衡，以及对机动交通方式的日益依赖。通过城市空间的分层，我们确定了有潜力容纳弱势群体的区域，由于不可接受的工作可达性条件而不鼓励低收入住宅占用的区域，以及需要综合土地利用和交通政策以改善工作活动的区域。这种方法不仅强调了在城市道路规划中解决社会空间不平等问题的重要性，而且还为协商规划目标和确定城市范围内关键领域的优先次序提供了方法基础，促进了更公平的机会获得。

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引用次数: 0

Flight delay prediction using machine learning and explainable AI: a case study on Hazrat Shahjalal International Airport, Dhaka 利用机器学习和可解释的人工智能进行航班延误预测：以达卡Hazrat Shahjalal国际机场为例

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-12-04 DOI: 10.1016/j.cstp.2025.101663

Fariha Tasnim Chowdhury , Sayeed Ziarat Mahmud , Syed Mohtasib Mashruk , Ahanaf Tajwar Basunia , Khan Md Hasib , Mohammad Shafiul Alam

Continuous delay in flight is a major problem for the aviation community. It results in losses, schedule adjustments, and passengers dissatisfaction. While machine learning has been used to predict delays, most earlier research focuses only on accuracy and does not explain why delays happen. This study fills that gap by combining prediction models with explainable AI (XAI) at Hazrat Shahjalal International Airport (HSIA), Dhaka. We used flight and weather data from 2022 to create a complete dataset by cleaning data, creating new features, and combining information. We tested several models including KNN, Support Vector Machine, Decision Tree, Random Forest, AdaBoost, XGBoost and CatBoost. The results show that ensemble models did the best, with CatBoost and XGBoost reaching 95% accuracy. To make these models more understandable, we used the LIME method, which showed that weather and scheduling were the main factors influencing delays. This study uniquely applies explainable machine learning to predict flight delays in a developing country context, specifically at Hazrat Shahjalal International Airport in Bangladesh. Most previous studies focused on countries like the UK, USA, Saudi Arabia, or China etc. By providing accurate predictions along with clear explanations, the results show how airlines and airport authorities can improve scheduling, better use resources, and meet international delay standards. This can help enhance passenger satisfaction and strengthen airport resilience.

航班持续延误是航空界的一个大问题。这导致了损失、时刻表调整和乘客不满。虽然机器学习已被用于预测延迟，但大多数早期研究只关注准确性，并没有解释延迟发生的原因。这项研究通过将达卡Hazrat Shahjalal国际机场（HSIA）的预测模型与可解释的人工智能（XAI）相结合，填补了这一空白。我们使用2022年以来的航班和天气数据，通过清理数据、创建新特征和组合信息，创建了一个完整的数据集。我们测试了几种模型，包括KNN、支持向量机、决策树、随机森林、AdaBoost、XGBoost和CatBoost。结果表明，集成模型表现最好，CatBoost和XGBoost的准确率达到95%。为了使这些模型更容易理解，我们使用了LIME方法，结果表明天气和调度是影响延误的主要因素。这项研究独特地应用了可解释的机器学习来预测发展中国家的航班延误，特别是在孟加拉国的Hazrat Shahjalal国际机场。以前的研究大多集中在英国、美国、沙特阿拉伯或中国等国家。通过提供准确的预测和明确的解释，结果显示航空公司和机场当局如何改进调度，更好地利用资源，并达到国际延误标准。这有助于提高乘客满意度和增强机场的应变能力。

{"title":"Flight delay prediction using machine learning and explainable AI: a case study on Hazrat Shahjalal International Airport, Dhaka","authors":"Fariha Tasnim Chowdhury , Sayeed Ziarat Mahmud , Syed Mohtasib Mashruk , Ahanaf Tajwar Basunia , Khan Md Hasib , Mohammad Shafiul Alam","doi":"10.1016/j.cstp.2025.101663","DOIUrl":"10.1016/j.cstp.2025.101663","url":null,"abstract":"<div><div>Continuous delay in flight is a major problem for the aviation community. It results in losses, schedule adjustments, and passengers dissatisfaction. While machine learning has been used to predict delays, most earlier research focuses only on accuracy and does not explain why delays happen. This study fills that gap by combining prediction models with explainable AI (XAI) at Hazrat Shahjalal International Airport (HSIA), Dhaka. We used flight and weather data from 2022 to create a complete dataset by cleaning data, creating new features, and combining information. We tested several models including KNN, Support Vector Machine, Decision Tree, Random Forest, AdaBoost, XGBoost and CatBoost. The results show that ensemble models did the best, with CatBoost and XGBoost reaching 95% accuracy. To make these models more understandable, we used the LIME method, which showed that weather and scheduling were the main factors influencing delays. This study uniquely applies explainable machine learning to predict flight delays in a developing country context, specifically at Hazrat Shahjalal International Airport in Bangladesh. Most previous studies focused on countries like the UK, USA, Saudi Arabia, or China etc. By providing accurate predictions along with clear explanations, the results show how airlines and airport authorities can improve scheduling, better use resources, and meet international delay standards. This can help enhance passenger satisfaction and strengthen airport resilience.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":"23 ","pages":"Article 101663"},"PeriodicalIF":3.3,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145736350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Environmental awareness and infrastructure – A path to sustainable transport in Central and Eastern European Countries 环境意识和基础设施——中欧和东欧国家通往可持续交通的道路

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-12-04 DOI: 10.1016/j.cstp.2025.101675

Agata Kliber , Blanka Łęt , Pavel Řezáč , Barbara Będowska-Sójka , Jindřich Frič

Reducing the use of combustion cars is one of the crucial aspects of the current environmental policy of the European Union. This article analyses how environmental awareness and the perceived quality of public transport and cycling infrastructure influence daily mobility mode choice in the Visegrad Group economies. We collected the data through surveys run in these countries from December 2023 to January 2024. We estimated a multilogit model with latent attitudinal variables. We demonstrate that ecological awareness is one of the key factors influencing consumers’ decisions about choosing transport modes other than a car. However, commuting remains predominantly car-based in all countries studied. Our results suggest that, when planning infrastructure that will encourage residents to use sustainable transport, decision-makers should prioritise creating good public transport connections with shopping centres, while cycling infrastructure should be linked to workplace and school locations.

减少内燃机汽车的使用是欧盟当前环境政策的关键方面之一。本文分析了环境意识、公共交通和自行车基础设施的感知质量如何影响维谢格拉德集团经济体的日常出行方式选择。我们通过从2023年12月到2024年1月在这些国家进行的调查收集数据。我们估计了一个具有潜在态度变量的多重logit模型。研究表明，生态意识是影响消费者选择汽车以外交通方式的关键因素之一。然而，在所研究的所有国家中，通勤仍然以汽车为主。我们的研究结果表明，在规划鼓励居民使用可持续交通的基础设施时，决策者应优先考虑与购物中心建立良好的公共交通连接，而自行车基础设施应与工作场所和学校地点联系起来。

引用次数: 0

What drives workers to be heavily reliant on cars in commuting to workplaces? Investigations of commute behaviour in Melbourne 是什么驱使工人们严重依赖汽车上下班？墨尔本通勤行为调查

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-12-02 DOI: 10.1016/j.cstp.2025.101679

Fadhlullah Apriandy , Sugiarto Sugiarto , Yusria Darma , Irsan Bahrumy

As the largest proportion of weekdays trips in Melbourne, Australia, work commutes, even in short distance, are predominantly attributed to cars. This study aims to investigate as to why Melbourne residents are heavily reliant on cars in commuting to workplaces. To better understand variations of car dependencies across different parts of the city and commute distances, this study divides Melbourne into three regions namely inner, middle, and outer Melbourne and set boundaries of commute distances to walkable (≤ 2.5 km), bikeable (2.5 to 15 km), and long (≥ 15 km). Multinomial Logistic models were utilized to explore the Victorian Integrated Survey of Travel and Activity (VISTA) data that contains travel, socio-demographic, and built environment factors. Variables were found to exhibit varying impacts on work commute behaviours across regions and distances. Overall, possessing a car license is associated with car uses across all distances. In walkable distance commutes, a km increase in commute distance significantly increases the likelihood of using cars. Inner Melbourne residents exhibit the tendency of using car in bikeable and long-distance commutes with the increasing number of cars owned. The findings of this study could help stakeholders in developing interventions to mitigate car dependency in work commutes.

作为澳大利亚墨尔本工作日出行比例最大的城市，即使距离很近，上班通勤也以汽车为主。这项研究的目的是调查为什么墨尔本居民严重依赖汽车通勤到工作场所。为了更好地了解城市不同地区和通勤距离的汽车依赖变化，本研究将墨尔本分为内、中、外三个区域，并将通勤距离划分为步行（≤2.5公里）、骑自行车（2.5至15公里）和长途（≥15公里）。使用多项Logistic模型来探索维多利亚旅行和活动综合调查（VISTA）数据，其中包含旅行，社会人口统计和建筑环境因素。研究发现，不同地区和距离的变量对工作通勤行为的影响是不同的。总的来说，拥有汽车执照与所有距离的汽车使用有关。在步行距离通勤中，通勤距离每增加一公里，使用汽车的可能性就会显著增加。随着汽车拥有量的增加，内墨尔本居民在骑自行车和长途通勤中表现出使用汽车的趋势。这项研究的发现可以帮助利益相关者制定干预措施，以减轻工作通勤中的汽车依赖。

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引用次数: 0

Machine learning for predicting the public adoption of partial and fully automated vehicle in Indonesia 机器学习预测印尼公众对部分和完全自动驾驶汽车的采用

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-12-02 DOI: 10.1016/j.cstp.2025.101678

Achmad Pratama Rifai , Fitri Trapsilawati , Erlangga Satrio Agung , Ari Widyanti , Roger Woodman , Auditya Purwandini Sutarto , Nachnul Ansori

This study investigates the public adoption of Partially Autonomous Vehicles (PAV) and Fully Autonomous Vehicles (FAV) in Indonesia, utilizing machine learning algorithms to predict willingness to use (WTU) and willingness to buy (WTB). Data were collected through an online survey of 1,251 Indonesian respondents, considering 38 socio-demographic, psychological, and mobility factors. Using Artificial Neural Networks (ANN) and Support Vector Machines (SVM), predictive models were developed and evaluated. The results highlight that ANN models exhibit higher accuracy for FAV predictions (MAPE = 11.246 %), while SVM models demonstrate efficiency with shorter training times. The results show that trust, perceived safety, and social influence strongly shape adoption intentions, with behavioural complexity increasing from PAV to FAV. These findings provide evidence-based guidance for policymakers and industry stakeholders preparing for autonomous mobility in Indonesia. The study acknowledges limitations related to online sampling and the absence of longitudinal behavioral data.

本研究调查了印度尼西亚公众对部分自动驾驶汽车（PAV）和完全自动驾驶汽车（FAV）的采用情况，利用机器学习算法预测使用意愿（WTU）和购买意愿（WTB）。数据是通过对1251名印尼受访者的在线调查收集的，考虑了38个社会人口、心理和流动性因素。利用人工神经网络（ANN）和支持向量机（SVM）建立预测模型并进行评估。结果表明，人工神经网络模型对FAV的预测具有更高的准确性（MAPE = 11.246%），而支持向量机模型在更短的训练时间内表现出更高的效率。结果表明，信任、感知安全性和社会影响强烈地影响着收养意愿，行为复杂性从PAV到FAV逐渐增加。这些发现为印尼的政策制定者和行业利益相关者准备自主出行提供了基于证据的指导。该研究承认在线抽样和缺乏纵向行为数据的局限性。

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引用次数: 0

Inference of parking search and location choice behavior using trip trajectories and Bayesian statistics 基于出行轨迹和贝叶斯统计的停车搜索和位置选择行为推断

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-11-29 DOI: 10.1016/j.cstp.2025.101671

Prakash Ranjan , Fatemeh Fakhrmoosavi , Krishna M. Gurumurthy , Abdelrahman Ismael , Nazmul A. Khan

Effectively designed parking solutions play a crucial role in mitigating urban challenges such as traffic congestion, excessive fuel consumption, and reduced safety. This study integrates GPS data with traveler survey data to model parking choice behavior, including preferences for parking type and choice for specific garage. Given the hierarchical nature of the choices, a nested logit model was estimated within a Bayesian framework using the Metropolis-Hastings algorithm. This approach is particularly efficient for high-dimensional models due to its fast convergence and straightforward implementation. The model was subsequently implemented within an agent-based transportation system simulation tool, POLARIS, to analyze the variations in drivers’ parking choice under diverse parking fee and capacity restriction scenarios. Analysis of the simulated scenarios for the Chicago network representing 8.5 million population revealed that while parking fee adjustments significantly impact travelers’ parking choices, fee variations during peak periods have minimal effect. For instance, a 50% rise in garage fees decreased the number of garage travelers by approximately 20%. However, raising garage fees by the same amount (50%) in the city during peak traffic periods led to a marginal drop of 7% in garage demand. Parking agencies generally set fees on the higher side to increase profit margins. However, parking policies should be designed to balance both travelers’ and transportation agencies’ interests in the long run. In addition, this study shows that allocating a portion of parking spaces to reserved parking or specific vehicle types, for a better curb space and parking management, significantly influences travelers’ decision-making in the parking choice selection.

有效设计的停车解决方案在缓解交通拥堵、过度油耗和安全性降低等城市挑战方面发挥着至关重要的作用。本研究将GPS数据与旅行者调查数据相结合，对停车选择行为进行建模，包括对停车类型的偏好和对特定车库的选择。考虑到选择的层次性，使用Metropolis-Hastings算法在Bayesian框架内估计嵌套logit模型。由于其快速收敛和简单的实现，该方法对高维模型特别有效。该模型随后在基于代理的交通系统仿真工具POLARIS中实施，以分析不同停车收费和容量限制情景下驾驶员停车选择的变化。对代表850万人口的芝加哥网络的模拟情景分析显示，停车费用的调整对旅客的停车选择有显著影响，而高峰时段的费用变化影响最小。例如，车库费上涨50%，车库旅行者的数量减少了大约20%。然而，在交通高峰期将车库费提高50%，导致车库需求小幅下降7%。停车代理机构通常将收费定得较高，以增加利润率。然而，从长远来看，停车政策的设计应该平衡旅客和运输机构的利益。此外，本研究还表明，为了更好地控制路边空间和管理停车，将一部分停车位分配给预留停车位或特定车型，显著影响出行者的停车选择决策。

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引用次数: 0

Understanding employee and managerial acceptance of flexible working arrangements as a transport policy in the Philippines: A sectoral comparative analysis 了解员工和管理接受灵活的工作安排作为运输政策在菲律宾：部门比较分析

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-11-29 DOI: 10.1016/j.cstp.2025.101677

Jayrill T. Condeza , Hitomi Sato , Tomio Miwa

Using behavioral theories, such as the modified unified theory of acceptance and use of technology (UTAUT), we extended the analysis of non-infrastructure travel demand management (TDM) strategies, such as flexible work arrangements (FWA), in managing the urban mobility of employees and managers beyond the constraints of classical transport policy evaluation. This study uses the classical UTAUT constructs – performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), and personal attitude (PA) – and additional psychological constructs, subjective wellbeing (SWB), work-life balance (WLB), and employee satisfaction (ES), to capture the underlying nuances, motivations, and concerns regarding the behavioral intention (BI) of adopting FWA. We further conducted a multigroup analysis to investigate whether the acceptance behavior of key stakeholders in the government and private sectors differ significantly. The findings suggest that the significant influence and perceived benefits of PA, PE, and WLB among employees and managers reveal the potential impacts of FWA in decongesting metropolitan urban spaces, especially during peak hours, reinforcing the idea of employing non-infrastructure TDM policies to help alleviate the worsening traffic conditions in major thoroughfares of the Philippines, as stipulated in the National Transport Policy. Additionally, these results identify the key areas of concern for both employees and managers affecting FWA adoption, enabling policymakers and organizational leaders to formulate more equitable sector-specific policies and guidelines to help achieve and sustain the identified potential benefits of time and cost savings, improved work performance, better quality of life, and positive environmental outcomes.

利用行为理论，如改进的技术接受和使用统一理论（UTAUT），我们扩展了非基础设施旅行需求管理（TDM）策略的分析，如灵活工作安排（FWA），在管理员工和管理人员的城市流动性方面超越了经典交通政策评估的约束。本研究使用经典的UTAUT构构——绩效期望（PE）、努力期望（EE）、社会影响（SI）、促进条件（FC）和个人态度（PA），以及额外的心理构构——主观幸福感（SWB）、工作与生活平衡（WLB）和员工满意度（ES），来捕捉采用FWA的行为意向（BI）的潜在细微差别、动机和关注点。我们进一步进行了多群体分析，以调查政府和私营部门关键利益相关者的接受行为是否存在显著差异。研究结果表明，PA、PE和WLB在员工和管理人员中的显著影响和感知效益揭示了FWA在缓解大都市城市空间拥堵方面的潜在影响，特别是在高峰时段，强化了采用非基础设施TDM政策来帮助缓解菲律宾主要道路交通状况恶化的想法，正如国家交通政策所规定的那样。此外，这些结果确定了影响FWA采用的员工和管理人员关注的关键领域，使政策制定者和组织领导人能够制定更公平的针对特定行业的政策和指导方针，以帮助实现和维持已确定的节省时间和成本、提高工作绩效、提高生活质量和积极的环境结果的潜在利益。

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引用次数: 0