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.     

Monitoring trucks to reveal Belgian geographical structures and dynamics: From GPS traces to spatial interactions

Despite the fact that freight transport has a huge impact on the economy and the environment, Belgian datasets have always been scarce or restricted to very small a-spatial samples. Spatial data collected in Belgium for toll-paying trucks are here examined, and geographical structures and dynamics are extracted from this massive dataset. The originality of this dataset is its exhaustivity and its real-time approach: the location of all the trucks circulating in Belgium is collected every 30 s.The paper first relates to the methodology applied when using and transforming big data generated by On Board Units GNSS (cleaning, transforming and pre-processing). Second, it maps and comments on the movements (traffic) and stops of trucks within the whole country, providing a clear picture of the Belgian situation, useful for regional planners and logistics companies. Finally, the flows of trucks observed between Belgian locations enable the country to be divided into mathematical communities of places that interact the most. Analyses are performed for sub-categories based on the country of registration, underlining the spatial specificities of freight transit in Belgium. This exploratory spatial data analysis enables to reveal not only multi-level spatial structures associated with urban hierarchies and the transport infrastructure, but also firm locations or political organizations and to consider the complexity and interconnectivity of any measure taken for a more sustainable future. With a clear methodological framework to cope with the data pre-processing, this paper opens the way to various potential applications linked with freight transportation in Belgium.     

Long-term impact of network access to bike facilities and public transit stations on housing sales prices in Portland,Oregon

Planners and economists generally accept that housing market values increase with proximity to transportation facilities through the provision of improved access to activity locations. While the market benefits of rail station access are well-documented, inconsistent and insufficient methods have led to limited agreement on the true value associated with this locational amenity. Far fewer hedonic price studies have assessed the influence of bike facility access on housing sales prices, and those that have generally analyze cross-sectional data. In this study, we estimated a spatial hedonic model using a bootstrapped pseudo panel to determine the joint impact of network proximity to bike lanes and off-street multi-use paths, as well as light rail and streetcar stations, on housing sales in Portland, Oregon, from 2002 to 2013. Our findings revealed housing sales prices increased as network distance to the nearest light rail transit and streetcar station decreased. Likewise, owner-occupied single-family and multifamily housing sales rose in conjunction with reduced street network access to regional multi-use bike paths; however, improved proximity to on-street bike lanes negatively affected housing values. In sum, we believe these findings may help to inform non-automotive transportation infrastructure financing mechanisms that rely on rising property values.     

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.     

The social aspect of residential location choice: on the trade-off between proximity to social contacts and commuting

Commuting has been found to be one of the least enjoyable activities. As it is a consequence of the choice of home and work location, the question arises as to how its disutility is compensated. Urban location theory suggests a compensation in the housing or the labor market. While this provides part of the explanation, individuals' personal networks may provide additional insights.Data from a social network survey were used to investigate proximity to social contacts as a factor in residential location choice.The results indicated that proximity to social contacts was an important factor and that it was traded off against commute time. The notion that the disutility of commuting is not compensated for may be a consequence of ignoring the effect of personal networks.The results contribute to the understanding of residential location choice and have implications for urban planning and policies that seek to reduce commuting.     

Linking expected mobility production to sustainable residential location planning: some evidence from Flanders

Based on a set of spatial proximity characteristics this paper develops a model that estimates for every neighbourhood in Flanders (Belgium) the amount of traffic that would be generated by an additional residential unit when socio-economic variables are held constant. The results show that residential density, land use diversity and proximity of facilities influence daily travelled distances when these variables are measured in the immediate vicinity of the residential location of the respondent (within a radius of 1 km). When aggregating these variables at a larger geographical scale, in most cases the impact proves no longer significant. Variables based on the spatial distribution of jobs, or on the global accessibility of the entire population in the study area, do not show any significant effects on the travel distance.Despite the statistical significance only a fraction of the observed variance in reported distances is explained by characteristics of spatial proximity. However, we can assume that the importance of spatial structure in the genesis of mobility patterns will increase in case the cost of transport would rise (cf. peak oil). For this reason, the application of the mapped results of the proposed model could contribute to the practice of sustainable spatial planning.     

Combined impacts of highways and light rail transit on residential property values: a spatial hedonic price model for Phoenix,Arizona

This study analyzes the positive and negative relationships between housing prices and proximity to light rail and highways in Phoenix, Arizona. We hypothesize that the accessibility benefits of light rail transit (LRT) and highways accrue at nodes (stations and highway exits specifically), while disamenities emanate from rail and highway links as well as from nodes. Distance decay of amenities and disamenities is captured using multiple distance bands, and hypotheses are tested using a spatial hedonic model using generalized spatial two-stage least-squares estimation. Results show that proximity to transport nodes was associated significantly and positively with single-family detached home values. As a function of distance from highway exits and LRT stations, the distance-band coefficients form an inverted-U pattern consistent with a positive longer-range distance–decay accessibility effect minus a smaller and shorter-range distance–decay disamenity effect. The positive accessibility effect for highway exits extends farther than for LRT stations. Coefficients for the distance from highway and LRT links, however, were not significant. We also test the effect of highway design on home values and find that below-grade highways have relatively positive impacts on nearby houses compared to those at ground level or above.     

Mapping bicycle use and the risk of accidents for commuters who cycle to work in Belgium

This paper explores the spatial patterns of bicycle use for commuting and the risk cyclists run being injured in a road accident when commuting to work in Belgium. Exploratory data analyses suggest that the observed differences in the use of the bicycle to get to work are strongly linked to the urban hierarchy: commuters are more inclined to cycle in cities and specifically in regional towns (with 25 000 to 120 000 inhabitants). In large cities (more than 200 000 inhabitants), less commuting by bicycle takes place. The relationship between bicycle use and the risk of being seriously injured or killed in a road accident is also studied. A cluster analysis confirms that high proportions of commuter cyclists are correlated with low risks of becoming a casualty. It also shows that there are strong spatial differences (regional and between different types of towns) in bicycle use and the risk of an accident. This suggests that cycling policies should be spatially differentiated.     

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.     

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.     

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.     

Decomposing excess commuting: a Monte Carlo simulation approach

Excess or wasteful commuting is measured as the proportion of actual commute that is over minimum (optimal) commute when assuming that people could freely swap their homes and jobs in a city. Studies usually rely on survey data to define actual commute, and measure the optimal commute at an aggregate zonal level by Linear Programming (LP). Travel time from a survey could include reporting errors and respondents might not be representative of the areas they reside; and the derived optimal commute at an aggregate areal level is also subject to the zonal effect. Both may bias the estimate of excess commuting. Based on the 2006–2010 Census for Transportation Planning Package (CTPP) data in Baton Rouge, Louisiana, this research uses a Monte Carlo approach to simulate individual resident workers and individual jobs within census tracts, estimate commute distance and time from journey-to-work trips, and define the optimal commute based on simulated individual locations. Findings indicate that both reporting errors and the use of aggregate zonal data contribute to miscalculation of excess commuting.     

Impact of new motorway on housing prices in rural North-East Slovenia

The literature generally agrees that improved accessibility has a positive effect on housing values. The motorway constructions in north-eastern Slovenia, completed between 2002 and 2018, significantly improved the accessibility of less developed areas. In this article, we examine how the new motorway has affected the housing values in the mostly rural north-eastern part of Slovenia. We analysed the distance decay effect of amenities and disamenities of motorway links and ramps as well as bus stops, train stations, and railway links on housing prices. In addition to the transport infrastructure variables, we analysed numerous other structural and environmental variables. We estimated three different spatial hedonic regression models: the spatial autoregression model, the spatial error model, and the spatial autocorrelation model.The results indicate that none of proximities to the bus stop, train station, or motorway link have had a significant effect on housing value. However, the rail track proximity exhibited a significant negative association with price. Furthermore, the effect of distance to the nearest motorway ramp on housing value is significant: it is stronger for closer distances (i.e. starting from 500 m) and decreases up to 6 km, while the effect of distances below 500 m is insignificant. Our results also show that bigger dwellings, more rooms, and the presence of a balcony, elevator, central auto heating system, new installation, and air conditioning as well as an apartment in a single house, are associated with a higher housing price. On the contrary, selling the dwellings together with a parking place and basement reduced the average price of the housing property. Comparing our results to the literature, we proved our hypothesis that the negative effect of a motorway is less pronounced in rural areas compared to urban areas and that the positive effect of accessibility is stronger in rural areas and extends over a wider geographical area.     

Impact of the jobs-housing balance on urban commuting in Beijing in the transformation era

This empirical study examines the impact of the jobs-housing balance on individual commuting time in Beijing in the period of transformation of the Chinese economy and society. The results of the analysis show that the jobs-housing balance has a statistically significant association with a worker’s commuting time when the factors of transport accessibility, population density and worker’s socioeconomic characteristics are controlled. The higher the jobs-housing balance, the shorter the worker’s commuting time. The finding suggests that the jobs-housing balance still has significant implications for commuting time, although the recent market-oriented reforms in housing are changing the jobs-housing balance in the danwei system that prevailed in the socialist era. As the housing markets are imperfect, with strong government intervention in Beijing, the finding implies that the co-location hypothesis - which believes development management would create ‘barriers’ to a jobs-housing balance and increase commuting time - needs to be rethought before it can be generalized and applied to China’s cities. The results of the analysis also show that the workers living in danwei housing still have shorter commuting time. The finding indicates that the housing marketization is likely to induce a local jobs-housing imbalance and thereby increase commuting time. In this sense, a deterioration in the jobs-housing imbalance and increased commuting time in Beijing may owe much to the adoption of market-based housing supply.     

Modeling job accessibility using online map data: An extended two-step floating catchment area method with multiple travel modes

Current quantitative measures of job accessibility rarely consider the interaction between job opportunities and labor force, and the effects of dynamic travel mode choice. Drawing upon multiple open-source datasets, we develop a job accessibility index by extending the two-step floating catchment area method (2SFCA). The job accessibility indices are calculated for different commuting scenarios concerning distance, time, and travel modes. The results suggest that job accessibility is very sensitive to travel modes, and using a single travel mode would contribute to a biased job accessibility index. The job accessibility indices with combined travel modes are more geographically balanced than using a single travel mode. Furthermore, the new index is employed to examine the spatial pattern of job accessibility and explore the relationship between job accessibility, housing, and population in the Pudong district, Shanghai. The new job accessibility indices manifest the impacts of ring roads on the spatial distribution of job accessibility. A comparative analysis shows that the floating population has poor driving-based job accessibility but can access job opportunities using public transit. Also, poor job accessibility leads to low rent prices but has little impact on medium-high rent. Both transit-based and drive-based job accessibility indices are positively related to housing prices. Our study highlights the importance of considering dynamic travel mode choice in job accessibility research. The research outcomes also contribute to the literature on spatial mismatch by revealing the unique relationship between job accessibility, housing, and population in urban China.     

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.     

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.     

Allocation of tasks,arrangement of working hours and commuting in different Norwegian households

Weekly working hours and commuting distance can be seen as indicators of equality/inequality between spouses. Traditionally, it is women who adjust their career more readily to meeting family obligations. In an era with a focus on equality between the genders in regard to both education and paid work, it is obvious to think of equality regarding working hours as well, and of distance to and from work. In this study we utilized data from the Norwegian Travel Survey of 2009 to examine the results of adjustments made in weekly working hours and commuting distance in families in which both husband and wife are in paid work. These indicate that the family situation is significant, and that, among other things, children in a family does not lead to any reduction in men’s working hours or commuting distance.Living in the periphery of large cities is disadvantageous for women who want to work full time, while living within a city tends to be to their advantageous in this regard. The results from the analysis of commuting distance show that women do not commute as far as men in comparable groups (working hours, family type, education, place of living, income, access to a car and occupation) and that the policy of regional enlargement is far from gender neutral. So long as it is women who adjust their labour market participation – both temporal and spatial – an enlargement of the regional/geographical labour market resulting potentially in longer commuting distances will primarily favour those who have the possibility to travel irrespectively of family situation, i.e. men, not women.