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.     

Mobility effects of b2c and c2c e-commerce in the Netherlands: a quantitative assessment

For more than a decade researchers have been interested in the implications of e-commerce for personal travel and freight transport. So far it is mostly the mobility effects of business-to-consumer (b2c) e-commerce that have been studied. However, consumer-to-consumer (c2c) e-commerce is becoming popular and may have important implications for mobility as well. Moreover, most studies conducted thus far have looked at the consequences of b2c e-commerce for either personal or freight travel, but not for both.This paper takes a more comprehensive approach. Using a nationwide sample of 3000 Dutch e-shoppers we calculated the potential impacts of both types of e-commerce on personal and freight travel. The results indicated that personal travel in the Netherlands has only marginally decreased as a result of e-shopping, while freight transport has slightly increased. The outcomes showed a net mobility effect, as the reduction in personal travel was not fully compensated by the increase in freight transport. However, this mobility reduction was fully attributed to b2c e-commerce, as c2c e-commerce led to an increase in both personal travel and freight transport.     

Job accessibility and the modal mismatch in Detroit

Transportation scholars are challenging traditional formulations of the spatial mismatch hypothesis because previous studies have disregarded the considerable difference between travel modes. This case study of the Detroit metropolitan region uses 2000 census data and a gravity-based model of transportation accessibility to test differences in access to jobs among places and people, and provides support for recent calls for reconceptualizing spatial mismatch. It shows that even though Detroit experiences the greatest distance between African Americans and jobs of any region in the country, most central city neighborhoods offer an advantage in accessibility to jobs compared to most other places in the metropolitan region – as long as a resident has a car. Policies aimed at helping carless people gain access to automobiles may be an effective means of improving the employment outcomes of inner-city residents.     

The end of travel time matrices: Individual travel times in integrated land use/transport models

To reduce inaccuracies due to insufficient spatial resolution of models, it has been suggested to use smaller raster cells instead of larger zones. Increasing the number of zones, however, increases the size of a matrix to store travel times, called skim tables in transport modeling. Those become difficult to create, to store and to read, while most of the origin-destination pairs are calculated and stored but never used. At the same time, such approaches do not solve inaccuracies due to lack of temporal resolution. This paper analyzes the use of personalized travel times at the finest spatial resolution possible (at x/y coordinates) and a detailed temporal resolution for synthetic agents. The approach is tested in the context of an existing integrated land use/transport model (ILUT) where travel times affect, among others, household relocation decisions. In this paper, person-level individual travel times are compared to traditional skim-based travel times to identify the extent of errors caused by spatial and temporal aggregation and how they affect relocation decisions in the model. It was shown that skim-based travel times fail to capture the spatial and temporal variations of travel times available at a microscopic scale of an agent-based ILUT model. Skims may provide acceptable averages for car travel times if a dense network and small zones are used. Transit travel times, however, suffer from temporal and spatial aggregation of skims. When analyzing travel-time-dependent relocation decisions in the land use model, transit captive households tend to react more sensitively to the transit level of service when individual travel times are used. The findings add to the existing literature a quantification of spatial biases in ILUT models and present a novel approach to overcome them. The presented methodology eliminates the impact of the chosen zone system on model results, and thereby, avoids biases caused by the modifiable spatial unit problem.     

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.     

Measuring individuals' travel behaviour by use of a GPS-based smartphone application in Dar es Salaam,Tanzania

A range of mega-cities in the Global South have started to invest in Bus Rapid Transit (BRT) systems, as a complement or replacement for informal paratransit services, in an effort to improve the mobility and accessibility in the city. Yet, few studies have tried to analyse the impact of such systems on the mobility patterns of cities' residents, in part because traditional travel diary surveys are often too expensive to conduct and unsuitable to capture spatial mobility patterns in fast growing cities with a high level of informality in spatial development. In this study, we analyse the applicability of a new method of data collection, i.e. a GPS-based smartphone application, to capture individuals travel behaviour in fast growing mega-cities in the Global South. Our case study is the city of Dar es Salaam (DES) in Tanzania, where the first BRT line is currently being implemented. In our study, the GPS-based app was used by individuals in DES to record distances, departure times and destinations of their trips. Socio-demographic data of respondents were recorded in short questionnaires. The spatial distribution of the trip patterns shows the mobility demand in both high and less connected areas. The results reveal a variation in departure times, travel destinations and trip distances that are one the one hand spatially limited within neighbourhoods and away from the planned BRT, and on the other hand along major roads connecting to the Central Business District (CBD). The short average distances of the trips (<3 km) reveal the characteristics of paratransit modes. The GPS-based smartphone application provides an opportunity to policy makers to engage deeply with the spatial reality of local communities, as a basis for transport investments and policy improvements as steps towards an integrated public transport system.     

Reducing the uncertainty induced by spatial aggregation in accessibility and spatial interaction applications

Analyses of spatial interaction are to some degree plagued by uncertainty regarding the impact of spatially dispersed interaction masses within zones on travel times. In this paper, interaction-weighted travel times are computed from a matrix between regularly distributed points at fine resolution, and used together with secondary data to improve estimates of interaction weighted travel time based on commonly applied methods. The paper proposes a method for computing intra-zonal, interaction weighted travel times that is considerably less sensitive to spatial aggregation than existing approaches, and demonstrates that population-weighted centroids are to be preferred over geographically-weighted centroids.     

Beyond absolute space: An exploration of relative and relational space in Shanghai using taxi trajectory data

The nature of urban space has long-drawn geographers' interest and David Harvey's conceptual framework of multiple spaces (i.e., absolute, relative, and relational) within cities has been widely adopted and developed. With its high spatial and temporal resolution, geospatial big data plays an increasingly important role in our understanding of urban structure. Taxi trajectory data is particularly useful in travel purpose estimation and allows for more granular insights into urban mobility due to the door-to-door nature of these trips. This article utilizes taxi trajectory data and explores the interaction among absolute space, relative space, and relational space in Harvey's framework using Structural Equation Modeling (SEM). Through an empirical study of Shanghai's downtown area, this paper highlights the importance of Harvey's framework in understanding cities' dynamic structure and argues for changes in urban planning and development to better coordinate land use and travel demand. We find an insignificant relationship between relative and relational space in Shanghai due to a mismatch between urban mobility and the built environment. This mismatch concentrates the transportation flow near the city's core area, transforming the polycentric structure of Shanghai's built environment in absolute space to a single-node structure in relational space. After identifying the contributing factors to this problem in Shanghai, this article suggests combining Harvey's conceptual framework of multiple spaces with geospatial big data to inform planning strategies that address the challenges of rapid urbanization.     

Spatial-modal scenarios of greenhouse gas emissions from commuting in Hong Kong

Transportation is a major source of greenhouse gas emissions in cities. Multiple strategies including green technologies, transport management, urban planning and behavior changes are required to mitigate transport emissions. This paper aims to introduce an analytical framework to investigate the impacts of different spatial-modal strategies on reducing commuting emissions. Based on the optimization approach of excess commuting, the proposed framework incorporates the minimum, maximum and random (unpredictable) travel outcomes to inform planning of an urban form embedded with fewer emissions. This analytical framework is applied to Hong Kong to estimate the emissions ranges (the minimum and maximum amounts) under 42 spatial-modal scenarios - a combination of six spatial strategies (status quo, monocentric, highly polycentric, moderately polycentric, dual-centric and tri-centric) and seven modal strategies (status quo, pro-rail (high), pro-rail (moderate), pro-bus (high), pro-bus (moderate), pro-car (high) and pro-car (moderate)). The findings illustrate the emissions impacts if Hong Kong is further developed following a job concentration or decentralization principle. It also indicates that if Hong Kong is reconstructed to be a city with multiple CBDs, a dual-centric strategy is desirable because both minimum and maximum commuting are shorter than that of a tri-centric strategy. Moreover, the modal strategy to actively promote rail usage shows more impacts on emissions reduction and car usage should be maintained at the current level. If commuter's travl is less predictable, the high rail usage under a dual-centric city form is a more sustainable spatial-modal strategy. The proposed analytical framework of city's commuting emissions affected by structural and modal changes is transferrable to other places and could offer planners different benchmarks of travel pattern to substantiate their sustainable city planning vision.     

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.     

Regional labour markets and job accessibility in City Network systems in Germany

Spatial labour markets are subjected to the forces of regional economic activity and competing network effects. Commuting is, therefore, an important equilibrating vehicle in a City Network constellation. Cities act as attractors of commuters, as most economic activity occurs in cities, thus providing a high share of attractive workplaces. Cities that are centrally connected in a network may act as both centripetal and centrifugal forces in the whole system. The present paper focuses on what is named the City Network (CN) approach. A central idea is the accessibility concept, which is interpreted here as the potential of opportunity for interaction, which has a positive impact on economic growth. In our paper, the accessibility concept and the CN concept are linked together by positioning accessibility in the CN system. Since accessibility measures give geographical insights into the distribution of economic activities and the related (dis)equilibrium of regional development patterns, the connection with the labour market is evident, and, therefore, a second focus of our analysis.In an applied setting, our paper aims to investigate spatial accessibility patterns in the main CN in Germany. The 17 districts which belong to the country’s CN were chosen from the 439 German labour market districts on the basis of three criteria: (a) their connection to the high speed railway network; (b) the most accessible districts according to previous results (2002); (c) relevant districts for the German economy. Our applied modelling research concerns home-to-work commuters travelling between the selected districts belonging to the German CN, for both 2003 and 2007. Here, a comparative analysis of the ranking of the most accessible districts - also for different intra-zonal travel times - is carried out in order to map out the changes in accessibility between 2003 and 2007, especially in the light of new high speed connections and commuting flow dynamics.     

Determinants and spatial variability of after-school travel by teenagers

This research work targeted teenagers to investigate after-school travel patterns and factors affecting their modal choice characteristics in Okinawa, Japan, where teenagers are not allowed to drive. The analysis is based on the cross-sectional data collected for discrete choice modeling of students’ travel in the prefecture. In this study, high school students’ trips from school to home have been analysed using a multinomial logit model. This has revealed the impact of individual, modal, and spatial variables on the mode choice decisions and return trip patterns. A comparative analysis made of downtown and suburb schools exposed differences in travel patterns induced by spatial factors and some existing constraints in modal choice options.     

Locational dynamics of logistics facilities: Evidence from Tokyo

This study uses data from a large-scale freight survey conducted in the Tokyo Metropolitan Area to jointly analyze the spatial distribution of logistics facilities and their proximities to the locations of shipment origins and destinations. The aim of the study is to examine in detail the argument that logistics sprawls increase truck trip distances, and thus would incur negative impacts to the society. We found that between 1980 and 2003, logistics facilities in the Tokyo Metropolitan Area have migrated outward, albeit in a much smaller scale than the cases documented in some U.S. and European cities. Our analysis of the shipment data confirms that logistics sprawl increases truck travel. Furthermore, we found that, regardless of their age, logistics facilities tend to increase shipping distances as their distances to the urban center increase, due to the spatial mismatch between the locations of the facilities and the shipment origins and destinations. The findings underscore the importance of comprehensive efforts to coordinate land use, not only for logistics facilities but also other businesses that generate freight movements.     

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.     

Residential self-selection and travel behaviour: What are the effects of attitudes,reasons for location choice and the built environment?

In studies of the effect of built environment on travel behaviour, residential self-selection is an increasingly important issue. Self-selection implies that households locate in places that provide them with conducive conditions for their preferred way of travelling. In these studies, it is assumed that attitudes toward different travel modes are an important factor in location choice, and that households are unconstrained in choosing their preferred residential location. This paper challenges these assumptions, by distinguishing between the more passive travel attitude and travel considerations as a deliberate reason to locate in a certain place. Based on a survey among 355 recently relocated households in Dutch TOD locations, we find that the association between travel attitude and residential environment is weak, and that the association between travel attitude and travel as a factor in location choice is moderate at best. Multivariate models show that both travel attitude and travel being a reason for location choice influence travel mode use, suggesting that travel attitude is insufficient to fully reflect self-selection processes. In comparison to other travel modes, train travel is most influenced by the fact whether residents deliberately chose to live in an environment conducive to using this mode.     

How do passengers allocate and evaluate their travel time? Evidence from a survey on the Shanghai–Nanjing high speed rail corridor,China

Although previous studies have demonstrated that travel time is not wasted, only a limited number of studies have conducted an in-depth investigation of how passengers allocate their travel time and what factors will impact their subjective valuation of travel time (SVTT). Investigating such questions will uncover some of the possible economic, social, technological and behavioral reasons that influence SVTT. Using a survey of 822 passengers traveling along the Shanghai-Nanjing high speed rail (HSR) corridor in 2016, this study examines passengers' allocation of their travel time, and explores the determinants of SVTT for business and non-business travelers, respectively. Empirical results indicate that around half of the respondents spend the longest amount of travel time on ICT discretionary activities, but there are some differences across trip purpose. Ordered logit models suggest that SVTT is determined by a range of factors, which are classified into travel time allocation, HSR environment, travel attributes, and socio-demographic characteristics. However, the specific factors associated with SVTT are somewhat different between business and non-business trips. The findings of this study provide a better understanding of the perceived value of travel time in a supportive travel environment and in a typical e-society of a developing country, and offer implications for more comprehensively exploring determinants of SVTT in the future.     

Exploring the interplay between the use of risk-related information,risk perception formation,and the stages of travel product consumption

This study examined using patterns of risk and warning-related information by backpackers who develop their own travel risk perceptions. It looked at the preferences of information sources and usage levels among Israeli backpackers. Using a simulating approach, interviewees were asked to report on their preference and usage patterns in four stages of the travel consumption sequence – (a) prior to choice of destination; (b) after choice of destination but before departure; (c) during the trip, and (d) after returning home. Based on a sample of 467 former backpackers, the study revealed that they use a relatively wide range of risk-related sources of information yet their preference and usage levels in those sources vary as they moved from one consumption stage to the other. The most innovative finding of this study is that unlike previous findings there was a significant and direct correlation between the level of risk-related information consumption and the backpackers’ level of risk perception in each of the tourist product consumption stages. Further research directions derived from these findings as well as management implications are provided.     

A multilevel Gini decomposition approach to measuring the geographic concentration of tourism

This research highlights findings from an application of a multilevel Gini decomposition method to measure the degree of spatial concentration of tourism markets in Australia. The overall level of spatial concentration in Australia is decomposed into two levels: inbound country and travel purpose. While travel purpose is an important factor associated with the concentration patterns of tourism, the nature of its impact differs significantly by country of origin. Due to the variation in market share and the market’s underlying dispersal characteristics, an increase in the share of one market may require a more than proportionate increase in the shares of several markets in order to counterbalance the spatial concentration pressures. Findings show that considering only one factor in the decomposition process can hide important offsetting influences of market segments on concentration and dispersion.     

Analysis on spatiotemporal urban mobility based on online car-hailing data

As an emerging travel mode, online car-hailing plays an increasingly important role in people's daily travel. Car-hailing data provide a new source to study human mobility in urban areas. This study focuses on identifying the distribution of regions with high travel intensity and the correlation between travel intensity and points of interest (POIs), based on the online car-hailing data collected in Chengdu, China. Firstly, the whole city area was divided into 16,100 uniform blocks and the number of pick-up and drop-off activities in each block was counted. Then, all POIs were categorized into 13 types and the number of different types of POIs in each block was counted. On this basis, the grade of travel intensity and POIs density in each block was identified according to the number of travel activities and POIs respectively. Finally, the correlation between the travel intensity and the POIs density was explored with ordered logistic regression. Experiment results showed that regions with high travel intensity are mainly distributed within the Second Ring Road, while those in the suburbs of city are usually the large transportation hubs, such as airports and train stations. Different types of POIs have different impacts on the online car-hailing travel intensity, and the density of traffic facilities has the greatest impact, including pick-up and drop-off, followed by density of scenic spot. The densities of service facilities and sports facility have an impact on the intensity of pick-up, while the impact on the intensity of drop-off is not significant. The density of company has no significant impact on the intensity of neither pick-up nor drop-off. These findings can contribute to a better understanding of online car-hailing travel activities and their relation with the urban space, and can provide useful information for urban planning and location-based services.     

Location quotient-based travel costs for determining accessibility changes

Accessibility is not a static feature because it is affected by a large number of factors, such as changes in transport infrastructure, the spatial distribution of human activities, and their interdependence. In this study, we examine the role of location quotient-based travel costs as the travel impedance function in accessibility measurement to better capture accessibility changes over time. The travel impedance function is one of the most widely studied aspects of accessibility. In most studies, travel impedance is determined by a negative exponential function in the travel cost assessment of the accessibility measure as a means to incorporate the distance decay effect. Here, we apply an accessibility index that uses location quotient-based travel costs and an accessibility measure with simple travel costs in order to test the proposed theory. The results of the two methods vary considerably. The location quotient method is discussed in detail, including its potential advantages for measuring accessibility changes. We argue that the location quotient-based travel cost is an appropriate method for determining the travel impedance function in accessibility measurements, especially for analyzing accessibility changes.