Why do they live so far from work? Determinants of long-distance commuting in California

Mitra, Suman; Saphores, Jean-Daniel

doi:10.1016/j.jtrangeo.2019.102489

Cited by 29 publications

(12 citation statements)

References 70 publications

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“…We now estimate Equation (1) omitting country fixed effects and including instead a set of indices, defined at the country-year level, related to factors associated with commuting behavior. These indices, obtained from the World Bank Database, serve as proxies for transport infrastructure, road security, travel behavior, economic growth, and urban distribution, all of which have been identified as determinants of commuting time (Naess, 2003(Naess, , 2006(Naess, , 2009Santos et al, 2013;Mitra and Saphores, 2019;Gimenez-Nadal, Molina and Velilla, 2020a). Specifically, we consider the number of passengers carried by railway, multiplied by kilometers traveled (divided by 1,000), and the length of railway routes available for train service (divided by 1,000), as national indices for transport infrastructure availability.…”

Section: Personal Factors Associated To Asymmetries In Commuting Timementioning

confidence: 99%

Two-way commuting: Asymmetries from time use surveys

Giménez-Nadal

Molina

Velilla

2021

Journal of Transport Geography

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Any opinions expressed in this paper are those of the author(s) and not those of IZA. Research published in this series may include views on policy, but IZA takes no institutional policy positions. The IZA research network is committed to the IZA Guiding Principles of Research Integrity. The IZA Institute of Labor Economics is an independent economic research institute that conducts research in labor economics and offers evidence-based policy advice on labor market issues. Supported by the Deutsche Post Foundation, IZA runs the world's largest network of economists, whose research aims to provide answers to the global labor market challenges of our time. Our key objective is to build bridges between academic research, policymakers and society. IZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author.

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Section: Personal Factors Associated To Asymmetries In Commuting Timementioning

confidence: 99%

Two-way commuting: Asymmetries from time use surveys

Giménez-Nadal

Molina

Velilla

2021

Journal of Transport Geography

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“…This will cause the distance between people's living area and work area to become longer due to urban expansion. A common phenomenon is that the increase in the distance people travel to work [4] has caused serious road blockages in some areas during peak hours.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Planning and Research on Urban Traffic Congestion

Zhu

Liu

et al. 2021

Future Internet

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For large and medium-sized cities, the planning and development of urban road networks may not keep pace with the growth of urban vehicles, resulting in traffic congestion on urban roads during peak hours. Take Jinan, a mid-sized city in China’s Shandong Province, for example. In view of the daily traffic jam of the city’s road traffic, through investigation and analysis, the existing problems of the road traffic are found out. Based on real-time, daily road traffic data, combined with the existing road network and the planned road network, the application of a road intelligent transportation system is proposed. Combined with the application of a road intelligent transportation system, this paper discusses the future development of urban road traffic and puts forward improvement suggestions for road traffic planning. This paper has reference value for city development, road network construction, the application of intelligent transportation systems, and road traffic planning.

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“…One of the objectives of CHTS is to also derive prototypical traveler profiles that encompass heterogeneity in long-distance travel behavior to understand long-distance travel. An extensive analysis of CHTS data, with focus on long commute trips, revealed a strong relationship between residential location characteristics and distance of the commute trip ( 5 , 6 ). Using CHTS these studies found that long-distance travel and cost of housing are strongly related, and higher-income and employed persons travel more ( 6 ).…”

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confidence: 99%

“…An extensive analysis of CHTS data, with focus on long commute trips, revealed a strong relationship between residential location characteristics and distance of the commute trip ( 5 , 6 ). Using CHTS these studies found that long-distance travel and cost of housing are strongly related, and higher-income and employed persons travel more ( 6 ).…”

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confidence: 99%

“…First, the literature contains a variety of definitions for “long-distance” travel, including ones based on distance (e.g., longer than 50 miles, 100 miles, or longer than 100 kilometers) and travel time (e.g., 40 minutes). Second, long-distance travel researchers have also considered a variety of indicators including number of long-distance trips, activity before and/or after travel to workplace, mode used, time of day of trip, and destination ( 6 – 16 ). Most studies, however, did not address trip chaining (e.g., people going to a business location, then to a leisure destination, and then back home).…”

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confidence: 99%

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Tour-Based Path Analysis of Long-Distance Non-Commute Travel Behavior in California

Davis

McBride

Janowicz

et al. 2018

Transportation Research Record

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Data of long-distance tours by each household from an 8-week California Household Travel Survey travel log are analyzed in this paper. Each tour record contains summary data from a single-day diary, household sociodemographic information, and place of residence characteristics. Each tour contains a main trip, selected tours with a main trip that is not a commute trip, and added destination descriptors from Foursquare. Path analysis is used on three censored variables (tour miles by air, miles driving, and miles by public transportation) and two categorical variables (main trip tour purpose) and number of overnight stays. Annual household income is a major determinant of air travel and multiple overnight stays. Moreover, travel by air is more likely to be in large dense destinations with high attractiveness ratings. In contrast, car ownership is a major determinant of more mileage accrued driving a car to urban environments. In terms of main trip purpose, work and shopping are not associated with overnight stays and vacation/sightseeing is the purpose associated with longer overnight stays. Moreover, California destinations are more likely to be in tours completed within a day. It was also found that vacation, sightseeing, and leisure trips are more likely to be combined with other vacation and sightseeing trips. In contrast, business and combined business and leisure trips are less likely to be combined with vacation trips. There were also substantial and significant differences in long-distance tour behavior among residents of urban versus rural environments.

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Why do they live so far from work? Determinants of long-distance commuting in California

Cited by 29 publications

References 70 publications

Two-way commuting: Asymmetries from time use surveys

Two-way commuting: Asymmetries from time use surveys

Intelligent Planning and Research on Urban Traffic Congestion

Tour-Based Path Analysis of Long-Distance Non-Commute Travel Behavior in California

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