Built environment,peak hours and route choice efficiency: An investigation of commuting efficiency using GPS data

Commuting efficiency measures the impact of commuting on urban spatial and social environments. Urban policies aim to reduce commuting distances and improve commuting efficiency by supporting mixed land-use and job-housing balance. Many studies have addressed these issues by examining excess commuting at the aggregate level, and most aggregated measurements of excess commuting are based on home-to-work commuting flows between zones. However, residents' travel behaviour does not consist solely of rational attempts at minimizing commuting distances but is instead affected by commuting hours, the complexity of the commuting chain and the built environment. Thus, commuting efficiency must be studied at the individual or disaggregated levels. This paper examined individual commuting efficiency in suburban Beijing using a GPS-facilitated activity-travel survey and investigated the differences in commuting distance and route choice efficiency between morning and evening peaks. Notably, in so doing, we considered non-work stops, and also explored the impact of urban spatial factors – in both residential and working areas – on commuting efficiency using multilevel mixed effects generalized linear models. The findings suggest that there are significant differences in commuting distance and commuting efficiency between morning and evening peaks based on the nature of commutes. Residents working in city centres or with jobs near railway stations, with higher road network densities or with lower facility densities seem to be more adept at selecting optimal routes.     

Day-to-day variation in excess commuting: An exploratory study of Brisbane,Australia

Commuting patterns where most if not all 'trips are optimised relative to a given distribution of jobs and housing can result in personal and socio-economic benefits. Excess commuting indicators provide useful information for academics and policy analysts to evaluate how the actual commuting pattern deviates from an optimal pattern where commuting costs are minimised. While actual commuting patterns vary from day-to-day, academic researchers have yet to quantify the temporal variation in these indicators over short time periods. This may be due to the lack of available longitudinal data as input for excess commuting indicators. This study shows that new, open and/or big data (NOBD) (e.g. smartcard data) can be exploited to serve as the input for such analysis. In this regard, our study uses half a year's worth of smartcard data from Brisbane, Australia to first derive/aggregate origins and destinations by small areas of the probable commuting trips by transit on all 122 weekdays over the study period. The study quantifies the day-to-day variation in excess commuting indicators for these trips and finds that excess commuting indicators vary considerably from one day to the next. Nevertheless, daily variations occur within a relatively consistent range which can be planned for. Our research suggests that more conscious and systematic utilisation of NOBD could change how commuting flows in cities are quantified, monitored and planned. In addition, with NOBD, we can more efficiently detect daily outliers in commuting patterns.     

Commute minimization in the Greater Toronto Area: applying a modified excess commute

Following the excess commuting literature, we develop a benchmark measure of the minimum required commute, conditional on the layout of the specific urban area. Through segmentation of the commuters into those that can be relocated and those that cannot, we try to explain the difference between the minimum required and actual commute. To determine the segmentation of the commuters we make use of a micro-level explanatory model of commuting distance. This micro-level modeling exercise informs a number of excess commuting simulations that address the contribution of certain groups of commuters to total commuting. Findings from the micro-analysis reaffirm similar findings in the literature for other urban areas. The simulation exercise suggests that varied levels of commute savings may result from policy directed at particular commuter groups.     

Commuting efficiency in the Beijing metropolitan area: an exploration combining smartcard and travel survey data

Using Beijing as an example, this research demonstrates that smartcard data can be used to (a) assemble the required data for excess commuting studies, and (b) visualise related results. Based on both smartcard and household travel survey data, we find that the theoretical minimum commute is considerably lower for bus users than for car users in Beijing. This suggests that there is a greater inter-mixing of jobs–housing functions (i.e., a better jobs–housing balance) associated with users of that mode compared to the corresponding land-use arrangement for car users, who locate further from the central area (Tian’anmen) than bus users. The commuting range for car users is 9.4 km greater than for bus users. Excess commuting is slightly higher for bus users (69.5%) than for car users (68.8%). Commuting capacity values are slightly lower for car users than for bus users, implying that car users consume less of their available commuting resources overall than bus users, albeit only marginally.     

Trends in regional jobs-housing proximity based on the minimum commute: The case of Belgium

This paper investigates recent trends in the efficiency of the Belgian territorial structure in terms of commuting, at both the urban and regional scales. The minimum commute distance (MCD) and excess rate (ER) are used to compare observed home-to-work trip lengths with an “optimal” alternative commuter pattern in which the sum of the distance traveled by the working population is minimized. The MCD is a proximity indicator that measures the spatial match between the labor market and the housing stock, which can also be regarded as an interesting indicator of potential border effects on travel behavior, especially in the inter-regional context of Belgium. An MCD calculation requires an origin–destination (OD) matrix and a distance matrix. In our Belgian case study, we employ a recent OD matrix (2010) originating from Social Security (ONSS) data. We compare this matrix with data from the 2001 and 1991 census surveys. In addition to identifying trends in jobs-housing proximity, the article assesses methodological implications regarding geographical scale arising from the use of the two data sources mentioned. Based on the available data, it was found that average actual commuting distance increased over both periods studied, while in general, growth rates of MCD are considerably lower than growth rates of the actual commuting distance. This indicates that the spatial proximity between the labor market and the housing stock in Belgium has declined over all periods studied, although this loss of spatial proximity only explains a small part of the increase of the actual commuting distance. Furthermore, we found that the comparison of excess commuting metrics between regions and time periods sets high standards on data requirements, in which uniformity in data collection and spatial level of aggregation is of great importance. Finally, as the main contribution of this study, the results demonstrate, through a statistical approach, that municipalities that are experiencing a higher-than-average increase in MCD and ER in one of the considered time frames are more likely to continue to exhibit a higher-than-average increase in the subsequent period. Therefore, the observed trends appear to be consistent over time.     

Examining the impacts of the Great Recession on the commuting dynamics and jobs-housing balance of public and private sector workers

Research examining commuting-related phenomena remains a key area of geographical research. And although substantial research has attempted to explore the relationships between transportation and land use, little is known about how the impacts of major economic changes such as the Great Recession would affect related commuting dynamics. In addition, commuting studies examining the plight of workers in private versus the public sectors are also virtually non-existent, though the two-groups' commuting dynamics would potentially be affected very differently by the Great Recession. This study contributes to a better understanding of commuting and jobs-housing balance during the Great Recession. We employ metrics from the excess commuting and jobs-housing balance literature in an effort to examine the commuting dynamics of private and public sector workers, with a focus on the time period around the Great Recession. Our analysis is conducted for the Atlanta, GA Metropolitan area. Findings of the study are that private workers experienced better jobs-housing balance over the study period, but they commute longer and more inefficiently when compared with public workers. While the Great Recession worsened both groups' commuting situation, the effect was more significant for public workers in terms of increasing their travel burdens. Since the public sector response to the Great Recession was delayed, policy implications suggest monitoring employment trends during and after economic shocks and recognizing the transportation disadvantages public sector workers may face in future crises. Keywords: excess commuting, jobs-housing balance, the Great Recession, private and public employment, spatial optimization.     

Near “real-time” estimation of excess commuting from open-source data: Evidence from China's megacities

Urban commuting has continuously fascinated scholars and decision-makers. As few people live and work in the same place, there is always excess commuting (i.e., the non-optimal or surplus work travel occurring in cities because people do not minimize their journeys to work for most residents). Traditional commuting data sources (e.g., questionnaires and census surveys) are challenged by small samples, high cost, and low spatiotemporal resolution. In contrast, the big social-sensing data (e.g., smart card and mobile phone data) only consider one or two traffic mode of a route, which is not consistent with the real-life condition. This article proposes a framework for modeling excess commuting based on open-source data of the ten most populous megacities in China. We downloaded residential points of interest (POIs) from Lianjia Real Estate website and obtained workplace POIs from China's AMAP, which is widespread used as Google map. The stratified sampling approach was employed to derive commuting pairs. Both commuting distance and time were obtained by the shortest path under public transportation from AMAP. Then, the linear programming method was employed to calculate the theoretical minimum commuting time and distance of each city. We analyzed the statistical property and spatial distributions of excess commuting and found that (1) commuting distances and time (ranging from 9.1 to18.1 km and from 44.8 to 74.3  minutes) of all ten megacities follow a left-skewed normal distribution; (2) in terms of commute cost, all cities show universal core-periphery patterns where the spatial heterogeneity of the commuting time is more significant than that of distance; (3) for each city, the excess commuting measured by time (i.e. from 0.61 to 0.79) is lower than that measured by distance (i.e. 0.68 to 0.89); and (4) the role of mixing land use, waterbody distribution, and centripetal urbanization on urban commuting distance and time is significant.     

Comparison of efficiency between public and private transport modes using excess commuting: An experience in Dar es Salaam

The excess commuting concept is well-known in developed countries. Since the introduction of the concept in the developed countries, the excess commuting framework has been used to derive a set of benchmarks and indices for the analyses of spatial mismatch, jobs-housing balance, and commuting efficiency in urban regions. However, there are very few studies which have examined excess commuting parameters in relation to mode of transport in the current excess commuting literature. Additionally, very few studies on excess commuting have been undertaken in developing countries with no evidence on any study in African cities. This paper attempts to add to the excess commuting literature by examining and comparing excess commuting parameters between public and private transport modes in Dar es Salaam city. The study investigated the effects of land use patterns in the year 2007 (the base year) and the projected land uses in the year 2030 on excess commuting parameters. The results suggest that public transport in Dar es Salaam is very good in terms of providing excellent options to get everywhere in the city as it connects homes and jobs as well as private transport. This is very different from cities in the more developed world, especially in the USA, where public transport is less effective at connecting origins and destinations. It was also found that the land use scenario in the year 2030 encourages a travel pattern that increases the actual average travel distance.     

Systematic comparison of trip distribution laws and models

Trip distribution laws are basic for the travel demand characterization needed in transport and urban planning. Several approaches have been considered in the last years. One of them is the so-called gravity law, in which the number of trips is assumed to be related to the population at origin and destination and to decrease with the distance. The mathematical expression of this law resembles Newton's law of gravity, which explains its name. Another popular approach is inspired by the theory of intervening opportunities which argues that the distance has no effect on the destination choice, playing only the role of a surrogate for the number of intervening opportunities between them. In this paper, we perform a thorough comparison between these two approaches in their ability at estimating commuting flows by testing them against empirical trip data at different scales and coming from different countries. Different versions of the gravity and the intervening opportunities laws, including the recently proposed radiation law, are used to estimate the probability that an individual has to commute from one unit to another, called trip distribution law. Based on these probability distribution laws, the commuting networks are simulated with different trip distribution models. We show that the gravity law performs better than the intervening opportunities laws to estimate the commuting flows, to preserve the structure of the network and to fit the commuting distance distribution although it fails at predicting commuting flows at large distances. Finally, we show that the different approaches can be used in the absence of detailed data for calibration since their only parameter depends only on the scale of the geographic unit.     

Exploring job accessibility in the transformation context: an institutionalist approach and its application in Beijing

There is a strong need to explore the determinants of worker’s commuting time as the declines in job accessibility associated with the dramatic growth of commuting time have become a serious negative effect on the quality of urban life in megacities of China. Most well-developed theories exploring change in commuting time are based on neo-classical economic theory. This paper argues however that in the case of China institutional factors of the housing provision system and labour mobility management have been more important. The paper conceptualizes an institutionalist approach incorporating housing and controls over labour mobility and applies it to analyse these influences on workers’ commuting time in Beijing. The analysis shows that the interaction of housing provision, the market system and the Hukou system together have significant impact upon individual commuting time allowing for worker’s annual household income, occupation and transport mode. The findings suggest that the market-oriented housing reforms have changed the local jobs–housing balance that prevailed in pre-reform era and have thus induced growth of commuting time; the remaining the unfair treatment of residents according to their Hukou status may influence the floating worker’s ability to connect housing and workplace opportunities that could reduce commuting time. With respect to future studies, the institutionalist approach seems to be an efficient means of exploring particular factors that emerge in the transformation of an economy.     

Accessibility and the journey to work through the lens of equity

Inequality in transport provision is an area of growing concern among transport professionals, as it results in low-income individuals travelling at lower speeds while covering smaller distances. Accessibility, the ease of reaching destinations, may hold the key in correcting these inequalities through providing a means to evaluate land use and transport interventions. This article examines the relationship between accessibility and commute duration for low-income individuals compared to the higher-income, in three major Canadian metropolitan regions, Toronto, Montreal, and Vancouver using separate multilevel mixed effects statistical models for car and public transport commuters. Accessibility measures are generated for jobs and workers both at the origin (home) and the destination (place of work) to account for the impact of competing labor and firms. Our models show that the impacts of accessibility on commute duration are present and in many cases stronger for low-income individuals than for higher income groups. The results suggest that low-income individuals have more to gain (in terms of reduced commute time) from increased accessibility to low-income jobs at the origin and to workers at the destination. Similarly, they also have more to lose from increased accessibility to low-income workers at the origin and to low-income jobs at the destination, which are proxies for increased competition. Policies targeting improvements in accessibility to jobs, especially low-income ones, by car and public transport while managing the presence of competition can serve to bridge the inequality gap that exists in commuting behavior.     

Excess commuting: a critical review and comparative analysis of concepts,indices, and policy implications

The last three decades have witnessed substantial growth in the literature on excess commuting. Researchers have proposed and applied a number of commuting benchmarks and excess commuting indices that aim to evaluate the commuting efficiency and jobs-housing balance of cities. A comprehensive review and comparative evaluation of the proposed metrics in terms of their ability to capture the intended phenomena, while controlling for the other general characteristics of cities, has yet to be performed. This article attempts to fill this gap by examining four commuting benchmarks (minimum commute, maximum commute, random commute, and proportionally matched commute) and five excess commuting indices (excess commute, commuting potential utilized, commuting economy, normalized commuting economy, and effort). Our conceptual analysis of the indices is complemented with a comparative empirical analysis of commuting in thirty Canadian cities. We explore relationships between the indices and point out the strengths and limitations of each. The findings suggest that no single index can adequately capture the commuting performance of an urban area, while each index can be employed to address a specific policy question. Used together, the indices can provide a reasonably good understanding of urban form and commuting behavior.     

The jobs–housing relationship and commuting in Beijing,China: the legacy of Danwei

China’s market-oriented reform has not only revitalized the economy but also changed the physical structure of Chinese cities, which used to be largely determined by the socialist Danwei (or work unit) system. In order to understand the impacts of the reform and the influence of Danwei on jobs–housing relationships and commuting behavior, this study investigates whether there are differences in commuting behavior between individuals who live in houses provided by Danwei and those who reside in houses from private market sources in urban China. We apply the structural equations model to investigate the interactions between housing source (from Danwei or not), jobs–housing relationship, transport mode and commuting time in Beijing, the capital city of China. The results show that Danwei housing commuters have shorter commuting trips and higher usage of non-motorized transport mode than those who live in houses from the market sources. This finding implies that the diminishing influence of the traditional Danwei system and the market-oriented reform in urban development may have changed the jobs–housing balance and increased travel demand in Chinese cities.     

Relationships between commuting distance,frequency and telework in Finland

The average commuting distance in Finland has increased steadily during recent decades. Daily long-distance commuting especially increases the number of vehicle-kilometres travelled. The aim of this work was to determine the relationship between commuting distance and frequency. The focus was on direct impacts of telework on commuting, but the significance of second apartments close to the workplace was also estimated. The empirical analyses were based on aggregate national data concerning commuting distances and a survey providing data of 19 000 employed respondents. The results of the study indicated that telework reduced by 0.7% the total kilometres travelled in Finland. The probability of working at home increases with commuting distance, but when the commuting trip exceeds 100 km a second apartment near the workplace becomes common and has a stronger impact on commuting kilometres travelled than telework.     

Suburban travelers pressed for time: Exploring the temporal implications of metropolitan commuting in Barcelona

This study explores the multiple temporal dimensions that commuting to a suburban location can have as an intensive and recurrent daily practice. Focusing on the suburban commute to a university campus in the Barcelona Metropolitan Region, a mobility survey is first combined with tracking data to explore the clock-time side of this phenomenon. The manner in which this daily practice is experienced is delved into using in-depth interviews. Results point out that intensive commuting is to be understood both considering its relation with daily travel time and its territorial context. Qualitative analysis shows how these suburban commuters are concerned for time, and presents strategies at different spatial and temporal scales. This paper provides insight to mobility studies by exploring the multidimensional nature of travel time, and to a growing mixed-methods research field by combining traditional and innovative sources.     

Disability,wages, and commuting in New York

In the U.S., substantial employment and wage gaps persist between workers with and without disabilities. A lack of accessible transportation is often cited as a barrier to employment in higher wage jobs for people with disabilities, but little is known about the intraurban commuting patterns of employed people with disabilities in relation to their wage earnings. Our study compares wages and commute times between workers with and without disabilities in the New York metropolitan region and identifies the intraurban zones where residents experience higher inequities in wage earnings and commute times. We obtained our data from the Public Use Microdata Sample (PUMS) of the American Community Survey (ACS) for the 2008–2012 time period. We used linear mixed-effects models and generated separate models with log hourly wage or one-way commute time as the dependent variable. We find significant differences in wages and commute times between workers with and without disabilities at the scale of the metropolitan region as well as by intraurban zone. At the metropolitan scale, disabled workers earn 16.6% less and commute one minute longer on average than non-disabled workers. High commute and wage inequalities converge in the center, where workers with disabilities are more likely to use public transit, earn 17.1% less, and travel nearly four minutes longer on average than workers without disabilities. These results suggest that transport options are less accessible and slower for disabled workers than they are for non-disabled workers. Our findings indicate a need for more accessible and quicker forms of transportation in the center along with an increased availability of centrally located and affordable housing to reduce the disability gap in wages and commute times. We also find that workers with disabilities generally seek higher wages in exchange for longer commute times, but the results differ by race/ethnicity and gender. Compared to white men, minority workers earn much less, and white and Hispanic women have significantly shorter commute times. Our findings offer new geographic insights on how having a disability can influence wage earnings and commute times for workers in different intraurban zones in the New York metropolitan region.     

Suburbanization and transit-oriented development in China

The suburbanization of large Chinese cities has placed many residents in locations that are far less accessible than their prior residences, requiring motorized travel. This paper examines the impacts of relocation to outlying areas on job accessibility, commuting mode choice, and commuting durations based on a current-day and retrospective survey of recent movers to three suburban neighborhoods in Shanghai. Job accessibility levels were found to decline dramatically following the move, matched by increased motorized travel and longer commute durations. Relocating to a suburban area near a metrorail station, however, was found to moderate losses in job accessibility and for many, encourage switches from non-motorized to transit commuting. We conclude that transit-oriented development holds considerable promise for placing rapidly suburbanizing Chinese cities on a more sustainable pathway.     

Methods for determining route distances in active commuting - Their validity and reproducibility

Distance is a variable of pivotal importance in transport studies. Therefore, after checking the validity of a potential criterion method for measuring active commuting route distances, this method was used to assess the validity and reproducibility of four methods of approximating the commuting route distances covered by pedestrians and bicyclists. The methods assessed were: self-estimated distance, straight-line distance, GIS shortest-route distance, and GPS-measured distance. For this purpose, participants were recruited when walking or bicycling in Stockholm, Sweden. Questionnaires and individually-adjusted maps were sent twice to 133 participants. The distances of map-drawn commuting routes functioned as criterion distances. The participants were also asked to estimate their distances. The straight-line distance between origin and destination was measured using map-drawn routes. The shortest route between home addresses and workplace addresses was calculated with three GIS algorithms. Eighty-six trips were measured with GPS. The main results were that test-retest intraclass correlation coefficients (ICC) exceeded 0.99 for all methods, except for self-estimated distance (ICC = 0.76). No order effects existed between test and retest. Significant differences were, however, noted between criterion distance and self-estimated distance (114 ± 63%), straight-line distance (79.1 ± 10.5%), GIS shortest route (112 ± 18% to 121 ± 22%) and GPS distance (105 ± 4%). We conclude that commonly-used distance estimation methods produce systematic errors of differing magnitudes when used in a context of active commuting in suburban and urban environments. These errors can at average level be corrected for, whereas individual relative errors will remain.