Exploring tertiary students' travel mode choices in Auckland: Insights and policy implications

It is crucial that policymakers and public transport operators comprehend tertiary students' travel mode choices and understand the factors that inform these choices in order to manage travel demands effectively and to optimise the use of public transport and improve its quality of service, particularly during the peak hours. This study aims to examine tertiary students' travel mode choices in Auckland, which is recognised as one of the most car-dependent cities in the world. The city is struggling with traffic congestion, particularly around its Central Business District (CBD) during peak hours. Auckland is New Zealand's largest city, with a population of 1.4 million residents. The main campuses of two major public universities, The University of Auckland (UoA) and Auckland University of Technology (AUT), are located in the CBD, attracting a large number of daily trips by both staff and students, particularly during the teaching semesters. However, there is a limited understanding of tertiary students' travel mode choices, particularly the factors that inform these choices when they travel to the universities' city campuses. A mixed methodology approach was used to comprehend the travel mode choices of students attending The University of Auckland and to identify the key factors that are drivers of these choices. The data collection included a questionnaire-based survey, which received 249 responses, and 10 semi-structured interviews with students. Thematic analysis was utilised to codify and then analyse the interviews. Despite the significant car dependency in Auckland, the survey demonstrated that most respondents utilised public transport and active modes when commuting to the university's city campus. Seven factors were identified that inform tertiary students' travel mode choices: cost, parking availability and cost, access to a car, travel time, physical environment, reliability, and attitudinal variables. The interviewees mostly argued that travel cost and lack of or limited access to a private car were the primary drivers of their travel mode choices. The study suggests that different stakeholders, such as Auckland Transport (AT) and The University of Auckland, should work collaboratively to provide an inclusive travel demand management policy. The university could rearrange classes for off-peak hours, and AT could offer tertiary students further discounts during these hours. These actions would result in the optimisation of public transport efficiency, improvement of the quality of the public transport service, and mitigation of traffic congestion around Auckland's Central Business District (CBD).     

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.     

Determinants of extreme commuting. Evidence from Brussels,Geneva and Lyon

Daily travel time has increased in Europe during the last decade. Some commuters show unusual commuting behaviours, so-called extreme commuting, which is defined as spending more than 100 min commuting a day. This paper aims to explain these commuting patterns from the point of view of the extreme commuters themselves. Based on a qualitative survey conducted in three European regions - Lyon, Brussels and Geneva - among individuals that spend at least two hours a day commuting, this study shows that extreme commuting is determined by complex interplay between the individual's working and private life and issues related to travel. Among our sample, the choice of public transportation modes assisted long-duration commuting. Our results also highlight the paradox that rapid transportation networks are used intensively to allow people to remain rooted — both residentially and socially.     

Active commuting in a university setting: Assessing commuting habits and potential for modal change

This paper describes the results of an online survey that examined commuting patterns, potential for change and barriers and motivators affecting transport decisions in a University population (n=1040 students, n=1170 staff). Overall, 21.5% of staff and 46.8% of students at The University of Western Australia regularly used active modes, and potentially an additional 30% of staff and students would switch to active modes. The results suggested that reducing barriers to using active modes, in particular reducing actual and perceived travel time by bus and bicycle would have the greatest impact on commuting patterns. Some policy applications appeared to hold particular promise, including an implementation of a subsidised public transport pass (U-Pass), increased student housing on or near campus, increased cost of parking, and improved bus services and cycle networks.     

Segmenting travellers based on day-to-day variability in work-related travel behaviour

Travel needs for commute and business trips are complex and choices are not made based on the characteristics of individual trips, but instead based on the needs over weeks and months. For example, the cost per trip of commuting by bus varies depending upon the frequency of travel, and the cost of a monthly subway pass depends upon the number of zones visited during that period. Intrapersonal variability, namely the variation in an individual's travel behaviour from day to day, therefore shapes our transport choices and should influence service provision. Changes in working patterns such as increases in part time working, self-employment and tele-commuting challenge the traditionally held assumptions that work activities are fixed in time and space, thus making intrapersonal variability increasingly relevant. This research uses a data-driven approach to segment workers based on their work-related travel behaviour, including frequency of travel and both spatial and time of day intrapersonal variability. The analysis uses survey and seven day travel diary data for over 110,000 people collected over a 19 year period in England. Four groups of workers were identified: infrequent, spatially variable, temporally variable and regular travellers. These groups do not align closely with self-reported working arrangements such as self-employment or part time working. The group of regular travellers has decreased in size between 1998 and 2016 but remains the largest group, containing just under 60% of workers in 2016. Both the infrequent and spatially variable groups have grown over the same period. For a small but growing group of workers, a seven day diary is insufficient to understand their work-related transport needs as little or no work travel is recorded. These findings have implications for the design of public transport ticketing, the design of mobility as a service packages and the appraisal of congestion charging schemes.     

Improving rural accessibility by locating multimodal mobility hubs

In rural regions, public transportation is often characterized by low accessibility as well as long waiting and travel times. In order to improve rural transportation systems, public decision-makers intend to implement alternative on-demand mobility modes. Herein, new intermodal travel itineraries with transfers at multimodal mobility hubs may enable faster public connections and thereby strengthen public transportation. Against this background, we present a decision support tool for locating multimodal mobility hubs to improve intermodal accessibility. As objectives, we aim at maximizing accessibility to workplaces and to places of private need. Our model decides on locations of multimodal mobility hubs and on the available on-demand mobility modes offered in addition to existing public transportation. We develop our model in an agile process together with rural decision-makers in the district of Heinsberg, Germany, and apply it in a real-world case study. As input for our model, we account for the existing public transportation system, identify points-of-interest, and estimate commuting volumes to workplaces based on official commuting data. Results promise a high potential to improve accessibility in rural areas. However, most of the improvement stems from unimodal car sharing trips.     

Analysis of active school transportation in hilly urban environments: A case study of Dresden

This paper analyses the way students travel to school and examines the influence of environmental conditions on travel patterns. More specifically, it studies how topographic changes affect the likelihood of choosing cycling as a transport mode. We use mode choice data on students' home-to-school commuting trips from a previous study by Müller et al. (2008). The results show that models perform better when they account for the topographic conditions of the urban environment. We included this information in the model by introducing the “energy exerted” variable, which significantly improves the model and the results. The implications of this study are manifold; it guides the consolidation or expansion of school-based transportation network planning in Germany and prompts further analysis of active transportation systems, such as bike, pedelec and e-bike sharing systems. Overall, transportation policy should seek to foster active transportation, as it provides the greatest benefits for society and has a direct impact on people's well-being, while notably reducing the negative environmental and socioeconomic impacts of motorized transport.     

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.     

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.     

Network-based spatial interpolation of commuting trajectories: application of a university commuting management project in Kyoto,Japan

This study presents an application of network-based spatial interpolation of student commuting trajectories from a series of origin–destination trip datasets. In particular, we incorporated multimodal public transportation networks, including bus networks, to estimate the student commuting routes. The student samples for this study were collected from an online travel diary survey conducted by Ritsumeikan University in Kyoto, Japan. The ArcGIS Network Analyst was used to construct spatial network datasets and reconstruct trajectories from the origin–destination trip dataset. In addition, line densities of estimated trajectories were calculated and displayed on maps for geovisualization. These maps helped us understand the precise locations of congestion and spatial patterns of student commuting, unlike linear representations of people’s movements that connect origins and destinations. Our study also showed that estimated trajectories can simulate quantitative impacts on travel time by promoting walking or the use of public transportation.     

Commuting patterns of employees in the Information Technology and traditional manufacturing sectors of Bangalore, India

Rapid growth of the Information Technology (IT) sector in Bangalore, India, has transformed the city’s urban-industrial landscape since the liberalization of India's economy in 1991. The city's IT sector is closely integrated with a global system of production and caters largely to a global clientele. Apart from the impact of these developments on urban form, there are indications that they are causing uneven growth patterns and socio-economic polarization, which has resulted in different travel patterns in the work force. This paper compares the commuting patterns of employees in two types of firms, an IT multinational corporation and a traditional public-sector-unit (PSU), using data from a survey. Regression models show that there is a significant increase in travel cost as income rises for a sample of employees of the IT sector, even though travel distance is not influenced by income. The reverse holds true for a sample of employees of the PSU—rising income significantly increases distance though income does not affect travel cost. Behavioral choice models also show that with increasing income IT employees are more likely to choose two-wheelers and cars for commuting while PSU employees are more likely to choose public buses or walk to work. The paper suggests that Bangalore's services-oriented IT economy is magnifying differences in work commuting patterns relative to those in the traditional manufacturing economy. The IT economy is also transforming travel behavior in terms of work travel mode choices among socio-economic groups.     

Indicators of transport and accessibility problems in rural Australia

Australia belongs to a small group of countries that are low density but affluent, and characterised by very high vehicle ownership levels but very little public transport in rural areas. It is widely believed that there are few problems of mobility and accessibility, apart from long distances, because everyone has a car. A literature review generally confirms this perception, although there are hardly any suitable local case studies. An analysis of the rural areas of New South Wales, Victoria and South Australia sought indicators of transport-related problems, using mainly census data. While the basic urban/rural distinction is clearly defined, within the rural areas patterns of vehicle ownership are unusual, and in the remotest areas are not as high as would be expected. Relationships with socio-economic variables are not consistent. Accessibility measures are incorporated in the analysis, and a travel needs index suggested. Appropriate case studies are required to establish travel behaviour patterns and the responses of disadvantaged groups.     

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.     

The path of least resistance explaining tourist mobility patterns in destination areas using Airbnb data

Destination attractiveness research has become an important research domain in leisure and tourism economics. But the mobility behaviour of visitors in relation to local public transport access in tourist places is not yet well understood. The present paper seeks to fill this research gap by studying the attractiveness profile of 25 major tourist destination places in the world by means of a ‘big data’ analysis of the drivers of visitors' mobility behaviour and the use of public transport in these tourist places. We introduce the principle of ‘the path of least resistance’ to explain and model the spatial behaviour of visitors in these 25 global destination cities. We combine a spatial hedonic price model with geoscience techniques to better understand the place-based drivers of mobility patterns of tourists. In our empirical analysis, we use an extensive and rich database combining millions of Airbnb listings originating from the Airbnb platform, and complemented with TripAdvisor platform data and OpenStreetMap data. We first estimate the effect of the quality of the Airbnb listings, the surrounding tourist amenities, and the distance to specific urban amenities on the listed Airbnb prices. In a second step of the multilevel modelling procedure, we estimate the differential impact of accessibility to public transport on the quoted Airbnb prices of the tourist accommodations. The findings confirm the validity of our conceptual framework on ‘the path of least resistance’ for the spatial behaviour of tourists in destination places.     

Determinants of the effectiveness of travel feedback programs—a review of communicative mobility management measures for changing travel behaviour in Japan

This paper reviews the literature on travel feedback programs (TFPs). These constitute soft measures designed to change travel behaviour, mainly from automobile to non-automobile travel, in mobility management. We classified TFPs according to place, technique, procedure, and communication media, and reviewed the effectiveness of 10 TFPs in Japan. We found that TFPs in Japan reduced CO₂ emissions by about 19% and car use by about 18%, while increasing the use of public transport by about 50%. In addition, we found that TFP effectiveness increased when participants were asked to make behavioural plans to change their travel behaviour.     

School commuting: the relationship between energy consumption and urban form

A large amount of research in the past has focused on the relationships between the energy consumption for home-to-work travel and land-use patterns. However, little is known about children’s mobility. This paper analyses the energy consumption, travel distances and mode choices for school commuting based on two decennial surveys in Belgium. The results highlight the following: (1) mobility behaviours have evolved drastically over the past decades for school commuting, an evolution that cannot be entirely related to land-use variables, (2) the energy consumption for school commuting is strongly dependent upon the school level, and (3) the links between land-use patterns and energy consumption for school commuting are different than those highlighted within the literature between urban forms and home-to-work commutes. The concentration of secondary schools and tertiary institutions in urban centres induces higher energy consumption rates, whereas the decentralisation of nursery and primary schools across the entire territory leads to very low local energy consumption and increased walking and cycling. These results provide a better understanding of school commuting within the European context and could guide future policies focused on transport energy consumption at the local scale.     

A multi-view of the daily urban rhythms of human mobility in the Tokyo metropolitan area

The purpose of this study was to clarify the spatiotemporal structure of human mobility patterns in the Tokyo metropolitan area (TMA), and to reveal the regional characteristics and differences of dynamic mobility behaviour therein, from the individual, location, and time-use perspectives. Furthermore, this study aimed to describe daily urban rhythms in terms of human mobility. For these purposes, we constructed a GIS microscope by handling our geo-tagged big data based on the person-trip data. Through a multi-view study, we affirmed that the spatiotemporal mobility patterns had a certain consistency at different scales. Results suggested that the human mobility patterns expressed a typical inter-regional functional complementarity and a certain daily rhythm under the layout of TMA’s quadruple concentric ring structure. By grasping the multidimensional dynamic pattern of human behaviour, researchers, the general public, and policymakers can be brought into alignment towards the goal of sustainable urban planning.