Commute Patterns Research Articles

Urban form, transit supply, and travel behavior in Latin America: Evidence from Mexico's 100 largest urban areas

This paper examines the relationship between urban form, transportation supply, and individuals' mode choice across Mexico's 100 largest urban areas. After documenting variation in mode choice, urban form, and vehicle ownership, we fit a multinomial logit model to data from 2.5 million commuters who reported a work commute on the 2015 Intercensus. We estimate whether a person commutes by transit, car, or walking/biking as a function of commuters' gender, age, employment status, household income, and seven measures of urban form and transportation supply. Across urban areas, commuters are less likely to drive in dense urban areas where jobs are spatially concentrated jobs and near population centers. Commuters are also less likely to drive in areas with better public transit supply and less roadway. Collectively the measures of urban form are as strongly related to the probability someone commutes to work by car as household income. Population density plays a particularly strongly role with an estimated elasticity four times as strong as recent studies from US urban areas. Taken together, our findings suggest that land use planning and transportation investments can and do influence commute patterns. Recent public policies have almost certainly contributed to increased, rather than decreased driving and associated congestion, pollution, and traffic fatalities.

Building reverse commute typologies through urban and suburban socioeconomic characteristics

The problem of employment access for the urban poor is often articulated across the urban-suburban divide in metropolitan areas, such that job opportunities concentrate in suburban areas, at a distance from areas of concentrated, racialized poverty in the inner city. The lack of public transit options that reasonably connect urban workers to suburban job opportunities only furthers this problem. However, transportation scholars have noted that a substantial population of the urban poor take this “reverse” commute. While these studies have grown knowledge on the characteristics of the reverse commuting population and their journey to work, they do not address, to the same extent, the demographic characteristics where reverse commuters live in the city and where they work in the suburbs. To learn more about the equity issues in the reverse commuting problem, this paper uses cluster analysis to develop typologies of commutes based on differences in key socio-demographic indicators between home (origin) and work (destination) geographies. This paper analyzes how commute patterns (intra-urban, suburb-city, etc.) and the number of jobs nested within these commute patterns, concentrate across socio-demographically defined commute typologies. Focus is given to how reverse commutes are distributed across these typologies. Reverse commutes constitute approximately 10% of all commutes in our sample and 10% of all primary jobs (the job that provides a worker the most income of all of their jobs) in the sample are accessed via reverse commute. The paper concludes with a number of transportation and social policy interventions that address issues facing particularly low-income, minority, reverse commuting workers. In light of the literature on metropolitan fragmentation, we recommend redistributive policies that build suburban, municipal accountability to urban, low-income reverse commuters.

MP50-09 REGIONAL VARIATION IN UTILIZATION OF URETEROSCOPY OVER SHOCKWAVE LITHOTRIPSY IN CALIFORNIA

You have accessJournal of UrologyStone Disease: Epidemiology & Evaluation II1 Apr 2018MP50-09 REGIONAL VARIATION IN UTILIZATION OF URETEROSCOPY OVER SHOCKWAVE LITHOTRIPSY IN CALIFORNIA Scott Wiener, Marshall Stoller, and Anne Suskind Scott WienerScott Wiener More articles by this author , Marshall StollerMarshall Stoller More articles by this author , and Anne SuskindAnne Suskind More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2018.02.1620AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Ureteroscopy (URS) and shockwave lithotripsy (SWL) are the most common procedures for renal and ureteral calculi. The percentage of stones treated by URS has risen over the past decade, surpassing the percentage treated by SWL as of 2010. The drivers behind this change remain unknown and likely vary by region. We sought to explore regional variation in utilization of URS and SWL over time in the state of California (CA) and to identify associated factors. METHODS We queried CA′s Office of Statewide Health Planning and Development (OSHPD) public inpatient and ambulatory surgical databases from 2005-2013. URS and SWL procedures for nephrolithiasis were identified via ICD-9/10 and CPT4 codes for inpatient and ambulatory procedures, respectively (codes for malignancy or ureteral stricture were excluded). Geographic regions were defined according to the CA Labor Market Information Division′s economic sub-regions (19 groups of counties where people live and work as assessed by population centers, commute patterns, and industry analysis). Information from the 2016 AUA and 2010 US censuses were incorporated, and Chi-square tests were used for comparisons. RESULTS A total of 237,461 URS and SWL procedures were identified from 2005-2013. URS accounted for 40% of stone procedures in 2005 and 57% of procedures by 2013. Between URS and SWL, category counts for age, gender, race, insurance, disposition, and comorbidities exhibited statistically significant but clinically irrelevant differences. However, 75% of URS versus 93% of SWL procedures were performed on an ambulatory basis (p<0.0001). Urologists practiced in all 19 regions in CA. Over time, 7 out of 19 regions (37%) shifted from SWL to URS predominance (Fig 1). These 7 regions contain 10 of 11 urology residency programs, 67% of the state population, and 68% of procedures performed. CONCLUSIONS Significant regional variation in practice patterns for the management of renal and ureteral calculi exists in the state of California and changes over time. Two patterns of practice emerge: some regions have adopted URS as the primary management, while others continue rely on SWL. The 7 regions which have predominantly adopted URS contain a majority of the population, almost all urology residency programs, and are the principal drivers of the statewide switch to URS based on the volume of URS performed. © 2018FiguresReferencesRelatedDetails Volume 199Issue 4SApril 2018Page: e678-e679 Advertisement Copyright & Permissions© 2018MetricsAuthor Information Scott Wiener More articles by this author Marshall Stoller More articles by this author Anne Suskind More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

Collective iteration behavior for online social networks

Understanding the patterns of collective behavior in online social network (OSNs) is critical to expanding the knowledge of human behavior and tie relationship. In this paper, we investigate a specific pattern called social signature in Facebook and Wiki users’ online communication behaviors, capturing the distribution of frequency of interactions between different alters over time in the ego network. The empirical results show that there are robust social signatures of interactions no matter how friends change over time, which indicates that a stable commutation pattern exists in online communication. By comparing a random null model, we find the that commutation pattern is heterogeneous between ego and alters. Furthermore, in order to regenerate the pattern of the social signature, we present a preferential interaction model, which assumes that new users intend to look for the old users with strong ties while old users have tendency to interact with new friends. The experimental results show that the presented model can reproduce the heterogeneity of social signature by adjusting 2 parameters, the number of communicating targets m and the max number of interactions n, for Facebook users, m=n=5, for Wiki users, m=2 and n=8. This work helps in deeply understanding the regularity of social signature.

SRC

Customized bus (CB) services that operate between residential areas and work places during rush hours have surfaced in many cities to deal with traffic congestion problem. One major challenge of CB services is to design service areas based on user demands. To solve this problem, we extract commute patterns from large-scale taxi GPS data for CB service area design. We present a novel clustering algorithm that embeds origin and destination data to a low dimensional feature space, such that the resulting patterns satisfy both the needs of commuters and operators. The algorithm has been tested on both synthesized and real-world data.

Improved estimation of commuter waiting times using headway and commuter boarding information

The average amount of waiting time spent by commuters is one of the key indicators of service quality for public bus operations. While actual measurements of actual waiting time is difficult to be done en masse, models of waiting time can be derived from bus headways and these models have been adopted by transport planners in monitoring and regulating service reliability of operators. However, these models are founded on several assumptions on the patterns of commuter arrival which may not be applicable for bus services that experience high demand and heavily fluctuating commuter patterns. Given the availability of granular data on commuter boarding from automated fare collection systems, we propose a new methodology to better estimate the average waiting time of commuters. The formulation is anchored and validated using a three-month dataset from ten selected bus routes in Singapore. Finally, we discuss how our new measure allows for minimization of commuter waiting time through schedule optimization.

Watching the clock on the way to work? Analysing trends in commuting activities, modes and gender differences in commute times, using hazard-based duration modelling methods

This study uses Hazard-based duration modelling methods to investigate commute patterns of males and females, with the aim of exploring the variability of commute times and modes over a period of nine years beginning in 2003. Securing two major datasets of the UK National Travel Survey (NTS) and Tyne and Wear household travel survey, as well as the level of detail that the chosen datasets offer, made it possible to ascertain the complexity of commuter travel at its fundamental level. Duration models have been very popular when analysing duration related activities. However, duration modelling research in the context of transport so far has been restricted to cross sectional one-off datasets. This is the first study that investigates commuting durations at a disaggregate level over a sustained period of nine years using duration modelling methods to acquire a fundamental understanding of the changes in commute durations. Gender aspects as well as the transport modes, including non-motorised transport (NMT), car and public transport (PT), were also addressed in the analysis. Probability density functions (PDFs), survival functions (S(f)) and hazard functions (H(f)) were employed when carrying out in-depth investigations into the patterns of commuting activities generated by males and females for the whole period of study over nine years, followed by year on year analysis. The descriptive analysis shows that commuting times are becoming longer as time goes by. Year on year analysis reveals that commute trips by car made by males are more likely to prevail in the system compared to PT, especially towards the end of the study period in 2010–11. The opposite is true for female commuting trips. NMT was an attractive mode for both males and females in 2009–10 even for longer commute trip durations of over 50min. As the complexity of the activity travel patterns of males and females has not been given adequate attention in previous research, this study made a step forward in investigating the gender aspects, with specific attention being given to the differences in commute times. Transport authorities' and policy makers' timely interventions, such as quality bus partnerships, cycle city guides, and cycle to work schemes, as well as Metro system reinvigorations, including smart ticketing, have been taken into account when rationalizing the results and the changes to commute times over the study period.

Patterns and correlates of active commuting in adults with type 2 diabetes: cross-sectional evidence from UK Biobank

ObjectivesTo describe the active commuting (AC) patterns of adults with type 2 diabetes and how these relate to physical activity and sedentary behaviour in UK Biobank. Social and environmental correlates...

Association between the neighborhood obesogenic environment and colorectal cancer risk in the Multiethnic Cohort

BackgroundInformation on the role of the neighborhood environment and colorectal cancer risk is limited. We investigated the association between a comprehensive suite of possible obesogenic neighborhood attributes (socioeconomic status, population density, restaurant and retail food environments, numbers of recreational facilities and businesses, commute patterns, traffic density, and street connectivity) and colorectal cancer risk in the Multiethnic Cohort Study. MethodsAmong 81,197 eligible participants living in California (35,397 males and 45,800 females), 1973 incident cases (981 males and 992 females) of invasive colorectal cancer were identified between 1993 and 2010. Separately for males and females, multivariable Cox regression models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for colorectal cancer risk overall and by racial/ethnic group (African American, Japanese American, Latino, white). ResultsIn males, higher traffic density was associated with an increased risk of colorectal cancer (HR=1.29, 95% CI: 1.03–1.61, p=0.03, for quintile 5 vs. quintile 1; p-trend=0.06). While this association may be due to chance, this pattern was seen (albeit non-statistically significant) in all racial/ethnic groups except whites. There were no other significant associations between other neighborhood obesogenic attributes and colorectal cancer risk. ConclusionFindings from our large racial/ethnically diverse cohort suggest neighborhood obesogenic characteristics are not strongly associated with the risk of colorectal cancer.

Determinants of long-duration commuting and long-duration commuters' perceptions and attitudes toward commuting time: Evidence from Kunming, China

Understanding the commuting patterns of long-duration commuters and the possible changes in these patterns can help policymakers adopt the more reasonable land use and transportation policies. With Kunming in China as a case study, the determinants of long-duration commuting trips were identified based on logistic regression model. The results indicated that age, education level, number of workers, presence of retirees, and residential location have a significant impact on the occurrence of long-duration commuting trips. The ideal commuting times and tolerance thresholds of commuting time of long-duration commuters were also investigated. The statistical results revealed the distributions of ideal commuting times and tolerance thresholds of commuting time of both short- and long-duration commuters. The average tolerance threshold of commuting time and the average ideal commuting time of long-duration commuters were greater than those of short-duration commuters. For 97.2% of the long-duration commuters, their actual commuting time was longer than the ideal commuting time; this finding indicates that most long-duration commuters are dissatisfied with their commuting time. The actual commuting time of 40.1% long-duration commuters exceeded their tolerance thresholds; these commuters are eager to reduce their commuting time.

Preterm birth and its associations with residence and ambient vehicular traffic exposure

Preterm birth (PTB) is a multifactorial disorder, and air pollution has been suggested to increase the risk of occurrence. However, large population studies controlling for multiple exposure measures in high-density settings with established commuter patterns are lacking. We performed a geospatial analysis with the use of a publicly available database to identify whether residence during pregnancy, specifically with regard to exposure to traffic density and mobility in urban and suburban neighborhoods, may be a contributing risk factor for premature delivery. In our cohort study, we analyzed 9004 pregnancies with as many as 4900 distinct clinical and demographic variables from Harris County, Texas. On the basis of primary residency and occupational zip code information, geospatial analysis was conducted. Data on vehicle miles traveled (VMT) and percentages of inhabitants traveling to work were collected at the zip code level and additionally grouped by the three recognized regional commuter loop high-density thoroughfares resulting from two interstate/highway belts (inner, middle, and outer loops). PTB was categorized as late (34 1/7 to 36 6/7 weeks) and early PTB (22 1/7 to 33 6/7 weeks), and unadjusted odds ratios (OR) and adjusted ORs were ascribed. PTB prevalence in our study population was 10.1% (6.8% late and 3.3% early preterm), which is in accordance with our study and other previous studies. Prevalence of early PTB varied significantly between the regional commuter loop thoroughfares [OR for inner vs outer loop: 0.58 (95% confidence interval, 0.39-0.87), OR for middle vs outer loop, 0.74 (0.57-0.96)]. The ORs for PTB and early PTB were shown to be lower in gravidae from neighborhoods with the highest VMT/acre [OR for PTB, 0.82 (0.68-0.98), OR for early PTB, 0.78 (0.62-0.98)]. Conversely, risk of PTB and early PTB among subjects living in neighborhoods with a high percentage of inhabitants traveling to work over a greater distance demonstrated a contrary tendency [OR for PTB, 1.18 (1.03-1.35), OR for early PTB, 1.48 (1.17-1.86)]. In logistic regression models, the described association between PTB and residence withstood and could not be explained by differences in maternal age, gravidity or ethnicity, tobacco use, or history of PTB. While PTB is of multifactorial origin, the present study shows that community-based risk factors (namely urban/suburban location, differences in traffic density exposure, and need for traveling to work along high-vehicle density thoroughfares) may influence risk for PTB. Further research focusing on previously unrecognized community-based risk factors may lead to innovative future prevention measures.

The Effectiveness of Healthy Community Approaches on Positive Health Outcomes in Canada and the United States

Healthy community approaches encompass a diverse group of population based strategies and interventions that create supportive environments, foster community behavior change and improve health. This systematic review examined the effectiveness of ten most common healthy community approaches (Healthy Cities/Communities, Smart Growth, Child Friendly Cities, Safe Routes to Schools, Safe Communities, Active Living Communities, Livable Communities, Social Cities, Age-Friendly Cities, and Dementia Friendly Cities) on positive health outcomes. Empirical studies were identified through a search of the academic and grey literature for the period 2000–2014. Of the 231 articles retrieved, 26 met the inclusion criteria with four receiving moderate quality ratings and 22 poor ratings using the Effective Public Health Practice Project Quality Assessment Tool. The majority of studies evaluated Safe Routes to School Programs and reported positive associations with students’ active commute patterns. Fewer studies assessed benefits of Smart Growth, Safe Communities, Active Living Communities and Age-Friendly Cities. The remaining approaches were relatively unexplored in terms of their health benefits however focused on conceptual frameworks and collaborative processes. More robust studies with longer follow-up duration are needed. Priority should be given to evaluation of healthy community projects to show their effectiveness within the population health context.

Mitigation of Vehicle Distribution in an EV Sharing Scheme for Last Mile Transportation

Last mile transportation , the movement of people and goods from a central hub to a final destination, is a challenging topic in implementing eco-friendly transport systems in modern cities. Much research has been focused on implementing a shared fleet of vehicles in achieving this goal. However, diverse commuter patterns as well as a large number of final destinations can lead to uneven distribution of the shared vehicles. In this paper, we propose and design a system platform for mitigation of vehicle distribution in an electric vehicle (EV) sharing scheme for last mile transportation by means of a remote driving approach. In this approach, a driver at a remote destination is enabled to maneuver the vehicle wirelessly and assist in the proper redistribution of the shared vehicle. Major technical challenges, such as handling wireless transmission latency, minimizing blind spots, and enhancing reliability, safety and security in the context of the remote driving system are identified and appropriate solutions are proposed and implemented. The developed system is validated with different performance-test measures and the outcomes are compared to that of normal driving. The results indicate that the proposed system platform can provide an adequate solution for last mile transportation through remote driving.

The Impact of Workforce Commuting Patterns on Parking Demand

This paper documents the methodological approaches and estimates of parking demand for the City of Pittsburgh using secondary data from the US Census Bureau. An appreciable degree of the empirical analysis is directed at commuters and the rationale for this is the need to focus on daytime parking when most of the peak demands were observed, a direct result of the composition of the city’s workforce and their commuting habits. Pittsburgh’s workforce to residential population ratio is 0.92, the highest of all the cities analyzed. On any workday, Pittsburgh’s daytime population increases to 463,186. This net gain of 155,702 is as a result of workers commuting to the city and is equivalent to more than 50% increase in the city’s overall population. Of this figure, more than three out of every four drive to work alone.The pressure that this puts on City parking is enormous, and is expected to increase given Pittsburgh’s favorable workforce growth trend and this realization underscores the fact that a supply side response may not be viable given the magnitude of the financial constraints involved in increasing parking supply. Effective demand related policy options are however limited as observed with the limited variation across cities in the preferences exhibited by commuters for driving alone though encouraging travel mode shift among by investing in public transit holds more promise. Particularly noteworthy is the ease with which the approach could be replicated in other cities and the use of US Census data provides a common data source that allows for comparative analysis.

Pricing and mode choice based on nested logit model with trip-chain costs

Commuters can complete their “home-work-home” trips by three options: subway-only mode, auto-only mode, and park-and-ride mode on a bottleneck-constrained corridor. The purpose of this paper is to enhance the insights into pricing mechanism for subway and parking and corresponding mode choice behavior on the corridor with elastic demand. A nested logit-based stochastic user equilibrium model is proposed to characterize the commuters’ modal choice. Dispersion parameters in the nested logit model reflect the risk or uncertainty of mode choice. It is found by sensitivity analysis that the impacts of subway fare and parking fee on the commute pattern are not always monotonous. Optimal strategies of subway fare and parking fee are discussed, respectively, under four market schemes by assuming that the subway and the parking lot at workplace are operated by either the government or a private owner. A numerical example is presented to illustrate how the pricing policies affect demand implementation, mode choice behavior and benefits of private owners and the whole transportation system.

Commuting patterns of workers in a village of Barddhaman district, West Bengal

Commuting helps to keep balance between residence and workplace of workers. With growing accessibility and connectivity, the importance of commuting is increasing all over the world. It is becoming a major substitute to migration. In commute-studies, commute-pattern is an important chapter. It highlights commuters’ directions of movement, distance they cover, modes of transport they use, the time they take to commute, etc. Unlike the urban-based commute pattern, commute pattern in rural areas are relatively an under-researched issue. In fact, traditionally rural people are thought to carry a sedentary lifestyle. Using primary data, this study aims to explore the commute patterns of rural workers located in the village of Gandharbapur of Barddhaman district of West Bengal, India. All the commuters were found to be engaged in non-farm work. Commuters stem from two major groups. One group of commuters is accumulated farm-income induced. They possess sufficient agricultural land. Investing their surplus farm-income, they have established non-farm works. The second group of commuters is poverty-driven. They are landless poor or are marginal farmers and to escape poverty, they have slipped into these works. Located beyond the suburban area (Memari being the nearest town), most commuters commute to nearby rural areas. Due to non-availability of public transport, women commute less than men do. Regular-paid government employees commute longer than other workers commute. The article concludes with a summary of findings and recommendations for further research.

A49 Visualizing active travel sentiment in an urban context

Abstract Background Commuting stress is known to be a root of many problems, including cardiovascular problems such as increased heart rate, increased blood pressure, back problems, as well as certain types of cancer. Examining how travel stress (or enjoyment) varies through time and space may reveal previously unknown relationships among active commute modes, intangible/tangible urban context, and daily weather. The present study set out to investigate these linkages using Geographic Information Systems (GIS) and space-time modeling techniques. Methods This research utilized exploratory spatiotemporal analysis and modeling of alternative commuter sentiment. Social media data was retrieved from twitter users in 6 metropolitan cities in the U.S., emotional content in the form of pleasure/arousal/dominance was extracted from it, spatial and aspatial data was obtained from various federal and local sources. A spatiotemporal weight was developed based on the space and time differentials for each daily tweeter. Exploratory analysis consisted of analyzing spatiotemporal patterning of tweeters using GIS techniques. Specifically, activity space analysis, surface estimation, spatial autocorrelation analysis (Getis-Ord hotspot analysis), global regression, and a spatiotemporal regression model was instituted. Results Preliminary exploratory analysis found that the majority of commuters tweeted once per day. When tweets were examined yearly, it was found that seasonality greatly affected commute sentiment patterns. Space-time weighted activity spaces varied significantly from un-weighted spaces. Furthermore, a weighted inverse-distance-weighted model demonstrated that travel mode affects human sentiment in both time and space. When hotspot analysis was visually examined in 3D, unique sentiments based on travel mode were observed in space and time. A global spatiotemporal regression model (OLS) indicated that weather, car usage, and mass-transit affected human sentiment (p-value Conclusions This analytical framework should be of interest to transportation planners seeking to understand how to promote alternative travel modes as well as health policy researchers studying the effect of commuting infrastructure on commuter’s well-being using a live, streaming dataset.

Streets, strolls and spots: Sex work, drug use and social space in detroit

BackgroundIn this paper, we explore social spaces related to street sex work and illicit drug use in Detroit. We consider these spaces as assemblages (Duff, 2011, 2013; Latour, 2005) that reflect the larger moral geography (Hubbard, 2012) of the city and fulfill specific functions in the daily lives of drug using sex workers. MethodsWe draw on thirty-one in-depth qualitative interviews with former street sex workers who were recruited through a court-based treatment and recovery program, as well as ethnographic field notes from drug treatment and law enforcement settings. ResultsOur interview findings reveal highly organized and routine activities that exist in a relatively stable, symbiotic relationship with law enforcement practices, employment and commuter patterns, and built environments. While the daily life of street sex work involves a good deal of individual agency in terms of moving between spaces and negotiating terms of exchange, daily trajectories were also circumscribed by economics, illicit substance use, and the objective risks of the street and the police. ConclusionWe consider the implications of these results for future policy directed at harm reduction in the street setting.

The impact of targeted outreach for parking mitigation on the UC Berkeley campus

Universities with urban campuses and constrained budgets such as the University of California at Berkeley (UC Berkeley) often find that repurposing parking facilities is more cost effective than obtaining new land for expansion. In spring 2013, UC Berkeley began closing off parking sites for building construction. However, rather than exploring the construction of new parking the campus began to explore targeted outreach encourage mode-shift for drivers whose travel patterns have been directly impacted.This study, conducted by campus researchers, analyzes change in commute patterns of UC Berkeley permit holders after targeted marketing campaign that not only provided customized information on their commute alternatives, but that delivered it in a softer, more personal, manner – taking advantage of one-on-one contact. The overall findings show that campus commuters did shift away from driving alone when they receive targeted outreach, although at a low rate when compared to other transportation demand management tools.We conclude that while such a program can fill an information gap, providing better or ‘curated’ information, it is just one of many practices that need to be used by urban campuses. Campuses, as such, should consider bundling it with more comprehensive policy and programs to reduce parking demand.

Effects of Jobs–Residence Balance on Commuting Patterns

Jobs–residence balance is believed to be an important way to reduce commuting distance and related externalities. Although literature on jobs–residence balance is rich, relatively few studies investigate it in relation to employment industry sectors. However, consideration of the unique features of different industry sectors, such as workers’ ability and working hours, is necessary to gain useful knowledge. In addition, variability in commuting distance is an important factor often neglected in previous studies. Low variability implies a high potential for car sharing and for use of transportation services. This paper fills the voids of existing literature by investigating three employment industry sectors in relation to both averages and standard deviations of commuting distances. A seemingly unrelated regression model with spatial error was applied to examine the relationship between jobs–residence balance and commuting patterns. The investigation also considered the effects of urban forms, which had been found to be influential in commuting patterns. Two groups of cities, compact and sprawled, were used as the cases of different urban forms. Results showed that jobs–residence balance was more sensitive to the goods-producing sector and to compact regions. Meanwhile, an efficient commuting pattern was associated with a high jobs–residence ratio, clustered industry distribution, and dense road networks with few intersections.