Commute Time and Labor Supply

Investigating travel time satisfaction and actual versus ideal commute times: A path analysis approach

This paper identifies the causal effect of commute time on labor supply in urban China and provides implications for the development of active commuting. Labor supply is measured by daily workhours, workdays per week and weekly workhours, and city average commute time is adopted as an instrumental variable to correct the endogenous problem of individual commute time. We find that in urban China, commute time does not have effect on daily labor supply but has negative effects on workdays per week and weekly labor supply. These results are different from those found in Germany and Spain, and are potentially related to the intense competition among workers in the labor market of China. Moreover, the effect of commute time on workdays per week is stronger for job changed workers. In addition, the effects of commute time on labor supply are not different between males and females. Finally, policy implications for active commuting are discussed.

El objetivo de la investigación fue analizar el sistema de transporte urbano de la ciudad de Puno, se propone de infraestructura vial urbano para tener una capacidad vial de acuerdo al tipo de vía y así poder optimizar el tiempo de viaje del pasajero según la tendencia de movilidad, movilidad de origen destino según zonas, movilidad del transporte urbano. Se analizó el recorrido de rutas de transporte público urbano para determinar la velocidad promedio y así poder conocer los tiempos de viajes. La hipótesis que se ha formulado es: con el análisis del sistema de transporte urbano se propone infraestructura vial urbana para optimizar el tiempo de viaje del pasajero de la ciudad de Puno-2018, se analiza la tendencia de movilidad según origen destino, la movilidad del transporte urbano, rutas de transporte urbano público e infraestructura vial urbana. La investigación centró su metodología, bajo un enfoque cuantitativo, diseño no experimental. Se aplicó un cuestionario como un instrumento para el análisis; de los cuales permitieron recoger información y analizar las variables de estudio y efectuar las correlaciones. La muestra estuvo conformada de 384 pasajeros y 8 microbuses que brindan servicio en las principales rutas de transporte público urbano. Como resultado se tiene que el sistema de transporte urbano de la ciudad de Puno es concentrado debido al uso de suelo en la zona céntrica, la movilidad vehicular tiene obstáculos en el flujo debido al uso de la calzada como estacionamiento y que las vías superan su capacidad vial la cual no optimiza los tiempos de viajes en ciudad de Puno para lo cual se requiere de infraestructura vial urbana como son: terminales terrestres, pavimentado de las vías paraderos, declarar zonas rígidas las vías que son utilizadas por las rutas de transporte urbano e implementar un sistema inteligente de gestión de tráfico en las intersecciones principales de la ciudad.

To examine relationships of residential crowding and commute time with early child development. We used the Early Development Instrument (EDI), a teacher-reported, population-health measure of child development. The sample included child-level observations spanning 8 US states from 2010 to 2017 (n = 185 012), aggregated to the census tract (n= 2793), stratified by percentage of households in poverty. To test the association of commute times, crowding, and child development, we tested overall readiness and 5 EDI domains by using adjusted census tract-level multivariate regression with fixed effects. In the full sample, a 1-standard-deviation increase in crowding was associated with 0.064- and 0.084-point decreases in mean score for cognitive development and communication skills, respectively. For the high-poverty subsample, a 1-standard deviation increase in commute time was associated with 0.081- and 0.066-point decreases in social competence and emotional maturity. In neighborhoods with increased crowding or commute time, early child development suffers. This study suggests a potential relationship between the changing urban landscape and child health. Children would benefit from more multisector collaboration between urban planning and public health.

In this paper bus travel time and delay is significant measures in public transportation. This research aims to explore impact of stops for the selected bus route and to find some simple suitable solutions to reduce the travel time and minimize delays for scheduling preferences of travellers. Delays data were collected using automatic vehicle location system (GPS technology) for the bus route #51 in Tashkent. Based on the collected GPS data were proposed the developed a linear and a logistic multivariate regression model. Travel time reliability were estimated regarding to a multivariate regression models and performed. The result shows that very good statistical suitable as expected and thus can be used in the public transportation to determine any travel time using real-time and available offline data. These outcomes, in the future it is expected that will be applicable and more efficient bus public transportation system in Tashkent.

Evaluation of urban public transportation efficiency in Kutahya, Turkey

The effect of commute time on labor supply is estimated in a unique labor market in which workers are subject to daily exogenous variation in commute time and are free to make daily labor supply decisions: substitute teaching. Data on both accepted and rejected job offers received by substitute teachers are used to estimate a sequential binary-choice model of job-offer acceptance decisions. The elasticity of the offer–acceptance probability with respect to commute time is found to be about −0.4. The aversion to commuting is about 36% larger on extremely cold mornings, but precipitation has essentially zero impact on commuting preferences. The effect of fuel price is of the expected sign, but imprecisely estimated. Women are particularly averse to commuting on cold mornings and are more sensitive to variation in fuel prices than men, but no statistically significant difference in the overall aversion to commuting is found between men and women.

Commute Costs and Labor Supply: Evidence from a Satellite Campus

Enhanced public transportation coverage and reduced travel times not only improve convenience for commuters but also contribute to a more efficient and sustainable transportation system.Both factors enable more people to use public transportation and reduce the reliance on personal vehicles, congestion and emissions.This paper aims to analyze the impact of new public transportation lines on network coverage and travel time reductions in different zones of the Greater Cairo Region (GCR), using Open Trip Planner and GTFS.The study compares the existing public transportation system, mainly relying on informal means such as "micro-busses" and limited metro lines, with the enhanced public transportation currently under development.The analysis is conducted on a grid of 1,200 origin points covering the whole city with 8 destination points resembling main zones of GCR.As a result of the analysis comparing the travel times and availability of public transportation lines serving these points considering both scenarios of the existing as well as more comprehensive system with new public transportation lines, large number of points exhibit reduced travel times, indicating that the new routes have effectively enhanced the connectivity to these areas.The travel time reduction ranged from 6 to 24 minutes, 5 to 21%, implies that commuters could experience significant time savings on their daily trips.The analysis also identifies points that remain inaccessible even with the introduction of new public transportation lines.Across all zones, there is a substantial number of points (ranging from 214 to 257) that are not accessible through either the old or new transportation system.

Quantifying errors in travel time and cost by latent variables

Travel time and delay are among the most important measures for gauging a transportation system’s performance. To address the growing problem of congestion in the US, transportation planning legislation mandated the monitoring and analysis of system performance and produced a renewed interest in travel time and delay studies. The use of traditional sensors installed on major roads (e.g. inductive loops) for collecting data is necessary but not sufficient because of their limited coverage and expensive costs for setting up and maintaining the required infrastructure. The GPS-based techniques employed by the University of Delaware have evolved into an automated system, which provides more realistic experience of a traffic flow throughout the road links. However, human error and the weaknesses of using GPS devices in urban settings still have the potential to create inaccuracies. By simultaneously collecting data using three different techniques, the accuracy of the GPS positioning data and the resulting travel time and delay values could be objectively compared for automation and statistically compared for accuracy. It was found that the new technique provided the greatest automation requiring minimal attention of the data collectors and automatically processing the data sets. The data samples were statistically analyzed by using a combination of parametric and nonparametric statistical tests. This analysis greatly favored the GeoStats GPS method over the rest methods.

Factors associated with commuter satisfaction across travel time ranges

This paper presents a real-world optimization problem in home health care that is solved on a daily basis. It can be described as follows: care staff members with different qualification levels have to visit certain clients at least once per day. Assignment constraints and hard time windows at the clients have to be observed. The staff members have a maximum working time and their workday can be separated into two shifts. A mandatory break that can also be partitioned needs to be scheduled if the consecutive working time exceeds a certain threshold. The objective is to minimize the total travel- and waiting times of the care staff. Additionally, factors influencing the satisfaction of the clients or the care staff are considered. Most of the care staff members from the Austrian Red Cross (ARC) in Vienna use a combination of public transport modes (bus, tram, train, and metro) and walking. We present a novel model formulation for this problem, followed by an efficient exact solution approach to compute the time-dependent travel times out of the timetables from public transport service providers on a minute-basis. These travel time matrices are then used as input for three Tabu Search based solution methods for the scheduling problem. Extensive numerical studies with real-world data from the ARC show that the current planning can be improved significantly when these methods are applied.

Travel time is a basic measure based on which intelligent transportation systems such as traveler information systems, traffic management systems, public transportation systems are developed. Although many methodologies have been proposed, they have not yet adequately solved many challenges associated with travel time, in particular, travel time estimation for all links in a large and dynamic urban traffic network is still an open problem that needs addressing. Typically focus is placed on major roads such as motorways and main city arteries but there is an increasing need to know accurate travel times for minor urban roads. Such information is crucial for tackling air quality problems, accommodate the growing number of cars and provide accurate information for routing. This study aims to address the aforementioned challenges by introducing a methodology, namely Similar Model Searching (SMS), to estimate travel times by using historical sparse travel time data. The SMS learns the temporal and spatial relationship between the travel time of adjacent links and utilize labeled data of similar models in order to improve its overall performance. The effectiveness of the proposed method is evaluated on a section of Leicestershire traffic network in the UK. The obtained results show that SMS efficiently estimates travel time of target links using models of adjacent traffic links.

The spectrum of employment-related geographical mobility ranges from hours-long daily commutes to journeys that take workers away from home for an extended period of time. Although distance and travel conditions vary, there is a strong consensus within existing literature that mobility has physical, psychological, and social repercussions. However, is time spent traveling considered as working time? This question is crucial as it dictates whether or not workers can effectively access different sets of labor rights. The objective of this paper is twofold. First, contributing to a deeper understanding of travel time by offering a more sustained and complex representation of the various employment-related travel schemes. Second, assessing the circumstances under which travel time counts as work time with regard to the employment standards legislation in force in four Canadian provinces: Quebec, Ontario, Alberta, and British Colombia.