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on Transport Economics |
| By: | Circella, Giovanni; Makino, Keita; Matson, Grant; Malik, Jai |
| Abstract: | The proliferation of digital devices and online services over the past decades has changed how people travel, enabling new mobility options and offering greater opportunities for e-commerce and telework. Researchers are still trying to understand how these new technologies and emerging transportation services are being adopted by different socio-demographic groups, and what the current trends might mean for transportation sustainability. In 2019, researchers at UC Davis launched a national survey to gain insights on general travel behaviors and the adoption of various emerging technologies. The researchers looked at behaviors such as the adoption of smartphones and information and communication technology, telecommuting, new mobility options, electric vehicles, and other alternative-fuel vehicles. With the onset of the COVID-19 pandemic in early 2020, the researchers modified their plan to understand new trends, such as increased remote work, online/virtual meetings, and e-shopping, as well as changes in travel. The team launched additional rounds of surveys to collect information on several additional topics in spring 2020, fall 2020, and summer 2021 (with a new round of data collection planned for fall 2022). The longitudinal dataset provides insights into emerging changes in transportation patterns, including the generational or sociodemographic differences in those changes, before and during the COVID-19 pandemic. This policy brief describes the key discoveries from the research. View the NCST Project Webpage |
| Keywords: | Social and Behavioral Sciences, Longitudinal Data Collection, Individual Lifestyles, Shared Mobility, Travel Behavior, Vehicle Ownership, COVID-19 |
| Date: | 2022–09–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt4f01x6fg&r= |
| By: | Florent Laroche (LAET - Laboratoire Aménagement Économie Transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique); Ayana Lamatkhanova (LAET - Laboratoire Aménagement Économie Transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | The paper explores the effect of the competitive tender for users through prices and frequencies in the regional railway passenger market. The analysis is original by an extended perimeter to seven European countries (France, Germany, Italy, Netherlands, Sweden, Switzerland, UK) and a total of 103 routes mixing market open to competition by tendering with market still under monopoly. Data are cross sectional and have been selected for one day. The method is based on an econometric analysis (Sureg) developed for other modes (air, coach) but never yet applied to the rail market and its specificities in terms of competition. For the regional services where competition is "for the market", the competition is analyzed through a dummy as a threat to lose the tender. Intermodal competition is limited to the coach services (dummy) and carpooling services (dummy). Results show that the threat of intra-modal competition can increase price for users but have no significant effect on frequencies. The analysis country by country highlights a similar performance for Sweden and Switzerland in spite of high differences in terms of competition. It suggests that the ability to negotiate contracts of public authorities and political choices can be more determinant than potential competition. Finally, effect of intermodal competition are weak mainly because of a limited offer. Results show that the probability to find a carpooling service increases when prices of train are increasing. |
| Keywords: | market structure,competition,tender,regional train,Railway competition,Regional Economy,Tender offer regulation,Working Papers du LAET |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:halshs-02930832&r= |
| By: | Circella, Giovanni; Makino, Keita; Matson, Grant; Malik, Jai |
| Abstract: | This study investigates the disruptive changes brought to transportation by emerging technologies and the COVID-19 pandemic through the analysis of repeated cross-sectional datasets that were collected with multiple survey waves administered in various regions of the United States and Canada. The first data collection was administrated in 2019 through the recruitment of respondents with an online opinion company. As the COVID-19 pandemic started to disrupt the world starting in 2020, two additional rounds of data collection were carried out in Spring 2020 and Fall 2020, to study the disruptions in activity and travel patterns that were caused by the pandemic. Starting in 2020, the data collection was extended to 15 U.S. regions: Los Angeles, Sacramento, San Diego and San Francisco in California; Atlanta, Boston, Chicago, Denver, Detroit, Kansas City, New York, Salt Lake City, Seattle, Tampa and Washington D.C. in other U.S. regions. In addition, the study covered also Toronto and Vancouver in Canada. Several thousands of respondents participated in the various waves of surveys. Some of these respondents were part of the longitudinal component of the dataset, built through inviting previous survey respondents to participate in the new waves of data collection. Additional respondents were recruited using online opinion panels and convenience sampling. The study enabled by the analysis of the data collected with this series of surveys helps understand how mobility patterns are evolving in the country as new technologies disrupt the transportation sector and they evolve from the pre-pandemic to the post-pandemic era. It helps make planning decisions and guide policymaking through an annual data collection that allows us to collect critically-needed information on the evolution of travel patterns and the adoption of new transportation technologies and trends in the selected regions, every year. In this report, the researchers briefly describe the series of data collection and present some summary findings from the analysis of the data collected before and during the COVID-19 pandemic. View the NCST Project Webpage |
| Keywords: | Social and Behavioral Sciences, Longitudinal Data Collection, Individual Lifestyles, Shared Mobility, Travel Behavior, Vehicle Ownership, COVID-19 |
| Date: | 2022–09–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt6h44p57d&r= |
| By: | Giuliano, Genevieve; Fang, Jiawen; Binder, Robert B; Ha, Jaehyun; Holmes, Andrea |
| Abstract: | The growth of urban e-commerce has had enormous impacts on urban transportation and land use. Retailers are competing through free and 1-or 2-day delivery which has incentivized small-scale deliveries (small packages in small trucks) to personal residences. From an urban freight perspective, these trips are less efficient than large-scale deliveries to retail locations. However, there remain questions regarding the overall impact of online shopping on passenger travel and vehicle miles traveled (VMT). This project focuses on how delivery preferences affect individual travel behavior in California and the Greater Los Angeles Region. The research puts special emphasis on alternative delivery methods that cluster local deliveries, such as automated parcel lockers (APLs) offered by Amazon. Clustered local deliveries could reduce truck VMT while only marginally increasing passenger VMT. The research team conducted two separate but related surveys to explore the potential of APLs as an alternative for residence deliveries: The first survey examines e-shopping behavior in general; the second addresses the use of APLs. The researchers find that online shopping is ubiquitous. The pandemic increased e-shopping, expanding it to older age cohorts and more diverse products. The use of APLs is rare. Convenience is the dominant factor in the delivery choice. The potential market for APLs could be increased if there were more locations available near home or workplace. Future research directions include modeling the impact of delivery methods on passenger VMT and incorporating product returns into our understanding of APL use. View the NCST Project Webpage |
| Keywords: | Social and Behavioral Sciences, E-commerce, automated parcel lockers, e-shopping behavior |
| Date: | 2022–10–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt19t2r64b&r= |
| By: | Steven Bond-Smith (UHERO, University of Hawai'i at Manoa); Philip McCann (University of Manchester, Alliance Manchester Business School; The Productivity Institute, Manchester, United Kingdom) |
| Abstract: | In this paper we set out the relationships between the behavioural, technological and spatial changes in systems that allow for heterogeneous responses to workingfrom- home by different types of actors, and also identifies the channels via which such changes take place. Unlike all other papers on the subject, the analytical framework we propose centers explicitly on the role of frequency of commuting. In particular, we find that the optimal frequency of commuting is positively related to the opportunity costs of less-than-continuous face-to-face interaction and inversely related to the travel plus travel-time costs. The results also support recent empirical findings of a “donut effect†with greater growth in the suburbs and hinterlands around large cities, but also capture inter-city effects for the first time. Counterintuitively, the reduction in the frequency of commuting makes larger cities and their hinterlands more desirable places, in spite of longer commuting distances. Taken together, our results imply enhanced productivity of larger cities over smaller cities. |
| Keywords: | Working-from-home, agglomeration economies |
| JEL: | R1 |
| Date: | 2022–09 |
| URL: | http://d.repec.org/n?u=RePEc:hae:wpaper:2022-6r&r= |
| By: | Ridderstedt, Ivan (Swedish National Road & Transport Research Institute (VTI)); Nilsson, Jan-Eric (Swedish National Road & Transport Research Institute (VTI)) |
| Abstract: | Although most public procurements involve decisions concerning bundling there is only a limited body of empirical research guiding policy on this matter. In this paper, we examine the cost effects of pure bundling in the competitive tendering of highway pavement replacement with hot-mix asphalt. For this we use linear regression on data from a comprehensive sample of such contracts procured by the Swedish infrastructure manager (IM) during the period 2012–2015. We find that bundling affects the procurer’s cost in multiple and partly counteracting ways. Our results show that economies of scale are strong but diminishing and counteracted by costs of bundling and bundling related factors. Overall, the findings support Swedish IM’s current design of bundles but also suggest that most of the contracts are still inefficiently small. Whilst not perfectly generalizable to other markets, the findings provide some support the increased promotion and use of bundling of small-scaled road rehabilitation projects in the US. Two main implications of the results are that bundling policy should emphasize proximity and similarity rather than whether work is small-scale and that the scope for efficient bundling should be accounted for when optimizing the timing of pavement replacement. |
| Keywords: | Public procurement; Efficiency; Bundling; Grouping; Highway; Road work |
| JEL: | H57 R42 R48 |
| Date: | 2022–10–07 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:vtiwps:2022_004&r= |
| By: | Daniel de Wolf (TVES - Territoires, Villes, Environnement & Société - ULR 4477 - ULCO - Université du Littoral Côte d'Opale - Université de Lille); Ngagne Diop (TVES - Territoires, Villes, Environnement & Société - ULR 4477 - ULCO - Université du Littoral Côte d'Opale - Université de Lille); Moez Kilani (LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | The model, which is described in detail in Kilani et al. covers the North of France and includes both urban and intercity trips. It is a multi-agents simulation based on the MATsim framework and calibrated on observed traffic flows. We find that the decrease in emissions of pollutant gases decreases in comparable proportion to the market share of the electric vehicles. When only users with shorter trips switch to electric vehicles the impact is limited and demand for charging stations is small since most users will charge by night at home. When the government is able to target users with longer trips, the impact can be higher by more than a factor of two. But, in this case, our model shows that it is important to increase the number of charging stations with an optimized deployment for their accessibility. |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-03763391&r= |
| By: | Florent Laroche (LAET - Laboratoire Aménagement Économie Transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | Paris-Lyon is the busiest High-Speed Line in Europe and has been open to open access competition since 18 December 2021. The purpose of this article is to explore the first effects on the price and frequency of competition between the Italian company Trenitalia and the French incumbent SNCF. The analysis is based on a large database (n = 971) collected from September 2019 to July 2022. The main challenge is to isolate the COVID-19 pandemic effect from the competition. A similar route without competition (Paris-Bordeaux) was selected to control the effects. The method relies on a descriptive analysis with an original dynamic timetable approach in the discussion. The results highlight an increase of frequency by 5% and a decrease in price by 10%. The prices charged by the newcomer are lower than those of the incumbent (-30% to -40%) though without enough volume to change the global equilibrium. Although far from a big bang, the comparison with the control route suggests a positive effect on price that moderates the economic catch-up effect following the COVID-19 pandemic in an inflationary context. More specifically, SNCF appears relatively insensitive to competitive pressure from Trenitalia. It has not significantly changed its price since the new offer was introduced and has maintained its trains. |
| Keywords: | Open-access competition,price,frequency,France,regulation,railroads,Working Papers du LAET |
| Date: | 2022–09 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:halshs-03770508&r= |
| By: | Gutiérrez, Antonio |
| Abstract: | Urban mobility patterns are changing as a response to new behaviours in cities. With more journeys, increased demand for motorised vehicles and longer distances to travel the need to study urban mobility is necessary to guide society towards a more sustainable horizon. Big Data and the digital footprint of people and vehicles have created a new source of appropriate information for urban mobility studies. Therefore, this article presents the different tools that offer high-frequency and spatial-temporal resolution data along with a review of the literature that uses these datasets in urban mobility research. |
| Keywords: | urban mobility; social network; big Data |
| JEL: | C80 R40 |
| Date: | 2022–10–03 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:114854&r= |
| By: | Julien Pascal |
| Abstract: | I explore the links between commuting costs and local employment dynamics using a spatial discontinuity introduced by a French reform in September 2015. The reform decreased the cost of public transportation in selected areas of the Paris region, but did not affect other areas. In the baseline regression framework, which only includes units that are geographically close to each other, I find that areas benefiting from the reform experienced a 0:25 percentage point decline in the unemployment rate, a 0.60 percentage point increase in the share of employed workers commuting using public transport, and a 1.4% increase in the price of residential real estate. I extend the regression framework to take into account the heterogeneity of treatment introduced by the reform, which allows me to analyze the mechanisms driving the results. I also show that a calibrated spatial search-and-matching model can rationalize the estimated treatment effects. |
| Keywords: | Local employment, Commuting Costs, Policy, Search-and-Matching |
| JEL: | E24 J68 R13 R23 |
| Date: | 2022–10 |
| URL: | http://d.repec.org/n?u=RePEc:bcl:bclwop:bclwp167&r= |
| By: | Despina Gavresi (University of Ioannina); Anastasia Litina (Department of Economics, University of Macedonia); George Tsiachtsiras (University of Bath, School of Management) |
| Abstract: | This paper explores the interplay between the extent of transportation infrastructure and various aspects of trust (interpersonal and political trust). We test our hypothesis by exploiting cross regional variation during the period 2002-2019. We focus on two measures of infrastructure, i.e., the length of railroads and railways in European regions. Interpersonal and political trust variables are derived from individual level data available in nine consecutive rounds of the European Social Survey. We document that individuals who live in regions with extended infrastructure network manifest higher trust both in people and political institutions. To mitigate endogeneity concerns, we extend our analysis to a sample of international and inter-regional immigrants. We further adopt an IV approach, where we use as an instrument the pre-existing Roman roads networks. The results from all three specifications are aligned to those of the benchmark analysis. We explore access to differential levels of trust as one of the underlying mechanisms behind our results. Relying on an expanding literature we hypothesize that the effect of infrastructure on trust operates directly via the degree of exposure to new people and ideas, as well as indirectly, via the effect of infrastructure on the structure of the economy. |
| Keywords: | motorways, railroads, political trust, interpersonal trust |
| JEL: | Z10 P48 R10 R40 |
| Date: | 2022–09 |
| URL: | http://d.repec.org/n?u=RePEc:mcd:mcddps:2022_08&r= |
| By: | Yicong Liu; Kaili Wang; Patrick Loa; Khandker Nurul Habib |
| Abstract: | The COVID-19 pandemic dramatically catalyzed the proliferation of e-shopping. The dramatic growth of e-shopping will undoubtedly cause significant impacts on travel demand. As a result, transportation modeller's ability to model e-shopping demand is becoming increasingly important. This study developed models to predict household' weekly home delivery frequencies. We used both classical econometric and machine learning techniques to obtain the best model. It is found that socioeconomic factors such as having an online grocery membership, household members' average age, the percentage of male household members, the number of workers in the household and various land use factors influence home delivery demand. This study also compared the interpretations and performances of the machine learning models and the classical econometric model. Agreement is found in the variable's effects identified through the machine learning and econometric models. However, with similar recall accuracy, the ordered probit model, a classical econometric model, can accurately predict the aggregate distribution of household delivery demand. In contrast, both machine learning models failed to match the observed distribution. |
| Date: | 2022–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2209.10664&r= |