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on Transport Economics |
| By: | Xiaojuan Yu (Zhongnan University of Economics and Law); Vincent A.C. van den Berg (Vrije Universiteit Amsterdam); Erik T. Verhoef (Vrije Universiteit Amsterdam) |
| Abstract: | When traveling in an autonomous car, the travel time can be used for performing activities other than driving. This paper distinguishes users’ work-related and home-related activities in autonomous cars and proposes an activity-based bottleneck model to investigate travelers’ behavior in the morning commute, shedding light on how the scope to undertake in-vehicle activities affects travelers’ trip-timing preferences and decisions, and therewith social welfare. These welfare effects can be expected to depend on the optimality of both the market for trips, and the market for vehicles. We therefore consider different supply regimes for automobiles, and un-priced congestion versus queue-eliminating road pricing. We reveal analytically the relationship between users’ various in-vehicle activities and trip timing choices by autonomous and normal car users. Three supply regimes for autonomous cars are investigated: welfare-maximizing public supply, competitive marginal cost supply, and profit-maximizing private supply. Pricing rules under different supply regimes are compared analytically, and the relative efficiencies in terms of the welfare gains are compared numerically. Results show that travelers’ in-vehicle activity choices have significant impacts on the travel patterns, congestion externality, supply decisions and the associated welfare effects. |
| Keywords: | Activity based modelling; Autonomous cars; Bottleneck model; Private vs public supply; Traffic congestion |
| JEL: | R48 R41 D62 |
| Date: | 2022–01–18 |
| URL: | http://d.repec.org/n?u=RePEc:tin:wpaper:20220004&r= |
| By: | Nakamura, Ryota (Hitotsubashi University); Albanese, Andrea (LISER); Coombes, Emma (University of East Anglia); Suhrcke, Marc (University of York) |
| Abstract: | This study investigates the impact of economic incentives on travel-related physical activity, leveraging the London Congestion Charge's disincentivising of sedentary travel modes via increasing the cost of private car use within Central London. The scheme imposes charges on most types of cars entering, exiting and operating within the Central London area, while individuals living inside the charging zone are eligible for a 90% reduction in congestion charges. Geographical location information provides the full-digit postcode data necessary to precisely identify the eligibility for the discount of participants in the London Travel Demand Survey for the period 2005–2011. Using a boundary regression-discontinuity design reveals a statistically significant but small impact on active commuting (i.e. cycling and walking) around the border of the charging zone. The effect is larger for lower-income households and car owners. The findings are robust against multiple specifications and validation tests. |
| Keywords: | economic incentive, health behaviour, London Congestion Charge, geographical information system, regression-discontinuity |
| JEL: | D04 I12 R48 |
| Date: | 2021–12 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp14957&r= |
| By: | Tong Zhang; Paul J. Burke |
| Abstract: | This study estimates the effect of gasoline prices on road deaths by vehicle mode using annual data for 62 countries for 2000–2018 and all states of the United States (US) for 1998–2018. Higher gasoline prices are associated with fewer overall road deaths. The proportional effect on motorcyclist deaths tends to be smaller or even have the opposite sign, especially in countries that are not highly dependent on motorcycles. For the US, a positive effect of gasoline prices on motorcyclist deaths is found, with an elasticity of about 0.3. There is also a positive relationship between gasoline prices and motorcycle registrations in the US. The results confirm that additional attention towards motorcyclist safety is warranted in times of high fuel prices. |
| Keywords: | fuel price, road deaths, motorcyclist deaths, fuel efficient |
| JEL: | R41 H23 Q43 |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:een:camaaa:2021-79&r= |
| By: | Jourquin, Bart (Université catholique de Louvain, LIDAM/CORE, Belgium) |
| Abstract: | Modal choice models for strategic freight transportation studies covering large inter-regional or international areas generally rely on basic explanatory variables such as transportation costs and transit times. Using origin-destination matrixes, it is also possible to compute an accessibility measure that can further be used as an additional explanatory variable. This paper shows that the inclusion of an accessibility measure in the utility functions used for a logit model significantly improves its predictive power. Moreover, when the refined model is used to compute cost and transit time elasticities, the obtained (absolute) values are somewhat lower. The use of an accessibility measure in the modal choice model has thus a double advantage for policymakers: it improves the predictive power of the freight transport model, giving more accurate traffics on the modal networks, and it avoids overestimations of own and cross-elasticities. |
| Keywords: | Freight transport model ; Modal choice ; Accessibility ; Elasticity |
| Date: | 2021–12–21 |
| URL: | http://d.repec.org/n?u=RePEc:cor:louvco:2021031&r= |
| By: | Vincent A.C. van den Berg (Vrije Universiteit Amsterdam); Henk Meurs (Radboud University); Erik T. Verhoef (Vrije Universiteit Amsterdam) |
| Abstract: | Travellers often combine transport services from different firms to form trip chains: e.g. first taking a train and then a bus. Integration of different forms of public and private transport into a single service is gaining attention with the concept of Mobility as a Service (MaaS). Usually the attention focuses on such things as ease of use for travellers and shifting demand away from the car. We focus on the effects of MaaS on behaviour and welfare via the market structure of transportation. In particular, we analyse three archetypical ways in which MaaS could be operationalised: Integrator, Platform, and Intermediary. |
| Keywords: | MaaS, market structure, platform, intermediary, integrator, regulation |
| JEL: | R4 D21 D43 |
| Date: | 2022–01–17 |
| URL: | http://d.repec.org/n?u=RePEc:tin:wpaper:20220002&r= |
| By: | Oliver Chiriac; Jonathan Hall |
| Abstract: | The goal of this paper is to revise the Henderson-Chu approach by dividing the commuters into two income-based groups: the `rich' and the `poor'. The rich are clearly more flexible in their arrival times and would rather have more schedule delay cost instead of travel delay. The poor are quite inflexible as they have to arrive at work at a specified time -- travel delay cost is preferred over schedule delay cost. We combined multiple models of peak-load bottleneck congestion with and without toll-pricing to generate a Pareto improvement in Lexus lanes. |
| Date: | 2021–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2112.12179&r= |
| By: | Lesley Mashiri; Aly Karam |
| Abstract: | Purpose: The interaction between rail transit and the urban property market is a crucial foundation for transit orientated development and policy planning in Metropolitan Cities. However, there are only a few studies which report on the impact transit access has on commercial property value in African cities. This paper presents an empirical study from the City of Johannesburg’s inner-city, to contribute to this subject matter.Design/Methodology: The paper utilises multiple regression models to determine statistical significance relating to the impact that a rail transit station has on commercial property values due to proximity and access. This is based on 87 observations of commercial properties located within a 1km radius of the Jeppestown PRASA railway station located in Johannesburg CBD. The paper also discusses the possible impact of other amenities found around close to the commercial properties.Findings: The findings of the study were that proximity to a railway station alone does not significantly impact commercial property values within a 1km radius. The results also show that there are other determinants which influence commercial property value, namely distance to schools, property age, industrial, and abandoned property. Hence, there is limited impact of the railway station on commercial property value.Implications: The discussion in this paper also delves deeper into providing gaps in knowledge on how railway stations relate to urban property market, especially commercial real estate values in Metropolitan cities. Finally, the findings will contribute towards more effective transit-oriented development policies and a better understanding of how public sector investments can help create value for properties. |
| Keywords: | commercial property; Planning; Property Value; railway transit; South Africa |
| JEL: | R3 |
| Date: | 2021–09–01 |
| URL: | http://d.repec.org/n?u=RePEc:afr:wpaper:2021-025&r= |
| By: | Yu, Bo (Deakin University); Tran, Trang (University of Maryland at College Park); Lee, Wang-Sheng (Monash University) |
| Abstract: | Following market liberalisation, the vehicle population in China has increased dramatically over the past few decades. This paper examines the causal impact of the opening of a heavily used high speed rail line connecting two megacities in China in 2015, Chengdu and Chongqing, on air pollution. We use high-frequency and high spatial resolution data to track pollution along major highways linking the two cities. Our approach involves the use of an augmented regression discontinuity in time approach applied on data that have been through a meteorological normalisation process. This deweathering process involves applying machine learning techniques to account for change in meteorology in air quality time series data. Our estimates show that air pollution is reduced by 7.6% along the main affected highway. We simultaneously find increased levels of ozone pollution which is likely due to the reduction in nitrogen dioxide levels that occurred. These findings are supported using a difference-in-difference approach. |
| Keywords: | air pollution, China, green infrastructure, high-speed railway, regression discontinuity, machine learning |
| JEL: | L92 O18 Q53 Q54 R41 |
| Date: | 2021–11 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp14900&r= |
| By: | Jie Xiong (ESSCA - Groupe ESSCA); Shuyan Zhao (Shenzhen Longhua Aiyi School); Yan Meng (Grenoble Ecole de Management); Lu Xu (CleRMa - Clermont Recherche Management - ESC Clermont-Ferrand - École Supérieure de Commerce (ESC) - Clermont-Ferrand - UCA - Université Clermont Auvergne); Seong-Young Kim (ESC Rennes School of Business - ESC Rennes School of Business) |
| Date: | 2022–02 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-03469528&r= |
| By: | ITF |
| Abstract: | This report provides an overview of technological, operational and policy measures that can accelerate the decarbonisation of aviation. Its goal is to support governments and aviation stakeholders looking to introduce aviation decarbonisation measures regionally, nationally and internationally. All measures are discussed in light of their cost-effectiveness and the potential barriers to their implementation. The report summarises the conclusions from an expert workshop held in February 2020 as part of the International Transport Forum’s Decarbonising Transport initiative. |
| Date: | 2021–07–29 |
| URL: | http://d.repec.org/n?u=RePEc:oec:itfaab:94-en&r= |
| By: | Marc Ivaldi (TSE - Toulouse School of Economics - UT1 - Université Toulouse 1 Capitole - Université Fédérale Toulouse Midi-Pyrénées - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Milena J Petrova (Unknown); Miguel Urdanoz (Unknown) |
| Abstract: | Airline alliances have a long history yet there is no academic consensus on how they affect price levels and their impact on price dispersion has not yet been studied. We address this question using a novel methodology motivated by the service homogenization and increased price competiton in this industry in the recent years. Establishing an equivalence between the online sales process and a reverse English auction, we use methods from auction econometrics to work in a new way with the standard industry data set: using individual ticket sales where only aggregated prices have been used in the past. Applicable to other industries where sellers compete in prices, this approach allows us to reconsider the effect of airline alliances on the distribution of airfares in the US domestic market. We find lower price mean and dispersion in markets where airlines belong to an alliance as a result of the lower variability of costs. The methodology we apply here can be used to study any distribution of individualized prices, which are now prevalent since the advent of the digital economy. |
| Keywords: | Airline,cooperation,auction,price dispersion,price distribution. |
| Date: | 2021–11–12 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-03455506&r= |
| By: | van der Hagen, L.; Agatz, N.A.H.; Spliet, R.; Visser, T.R.; Kok, A.L. |
| Abstract: | Online grocers typically let customers choose a delivery time slot to receive their goods. To ensure a reliable service, the retailer may want to close time slots as capacity fills up. The number of cus- tomers that can be served per slot largely depends on the specific order sizes and delivery locations. Conceptually, checking whether it is possible to serve a certain customer in a certain time slot given a set of already accepted customers involves solving a vehicle routing problem with time windows. This is challenging in practice as there is little time available and not all relevant information is known in advance. We explore the use of machine learning to support time slot decisions in this context. Our results on realistic instances using a commercial route solver suggest that machine learning can be a promising way to assess the feasibility of customer insertions. On large-scale routing problems it performs better than insertion heuristics. |
| Keywords: | time slot management, vehicle routing, supervised machine learning |
| Date: | 2022–01–17 |
| URL: | http://d.repec.org/n?u=RePEc:ems:eureri:137095&r= |
| By: | FERNANDEZ LLORCA David (European Commission - JRC); GOMEZ Emilia (European Commission - JRC) |
| Abstract: | This report aims to advance towards a general framework on Trustworthy AI for the specific domain of Autonomous Vehicles (AVs). The implementation and relevance of the assessment list established by the independent High Level Expert Group on Artificial Intelligence (AI HLEG) as a tool to translate the seven requirements that AI systems should meet in order to be trustworthy, defined in the Ethics Guidelines, are discussed in detail and contextualized for the field of AVs. The general behaviour of an AV depends on a set of multiple, complex, interrelated Artificial Intelligence (AI) based systems, each dealing with problems of different nature. The application context of AVs can intuitively be considered high-risk, and their adoption involves addressing significant technical, political and societal challenges. However, AVs could bring substantial benefits, improving safety, mobility, and the environment. Therefore, although challenging, it seems necessary to deepen the application of the assessment criteria of trustworthy AI for AVs. |
| Keywords: | AI, autonomous vehicles |
| Date: | 2021–12 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc127051&r= |
| By: | Nicholas S. Caros; Jinhua Zhao |
| Abstract: | A gradual growth in flexible work over many decades has been suddenly and dramatically accelerated by the COVID-19 pandemic. The share of flexible work days in the United States is forecasted to grow from 4\% in 2018 to over 26\% by 2022. This rapid and unexpected shift in the nature of work will have a profound effect on the demand for, and supply of, urban transportation. Understanding how people make decisions around where and with whom to work will be critical for predicting future travel patterns and designing mobility systems to serve flexible commuters. To that end, this paper establishes a formal taxonomy for describing possible flexible work arrangements, the stakeholders involved and the relationships between them. An analytical framework is then developed for adapting existing transportation models to incorporate the unique dynamics of flexible work location choice. Several examples are provided to demonstrate how the new taxonomy and analytical framework can be applied across a broad set of scenarios. Finally, a critical research agenda is proposed to create both the empirical knowledge and methodological tools to prepare urban mobility for the future of work. |
| Date: | 2022–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2201.01321&r= |