Mobility, social exclusion and well-being: Exploring the links

Building on a growing research foundation, transport policy makers have begun to associate the ability to be mobile with having a role in the facilitation of social inclusion. However, the further connection to well-being is not as well understood. This paper explores the association between a person’s travel patterns, their risk of social exclusion and self-assessed well-being. Key influences on social exclusion are discussed, with trip making emerging as a significant influence. Trip making is not a significant direct influence on well-being but does exercise an indirect influence through the impact on risk of social exclusion. The modelling process enables a value for additional trips to be estimated, the value being about four times the values derived from conventional generated traffic approaches. Similar high values are found in separate metropolitan and regional case studies, confirming the significance of the results.     

Planning transport for social inclusion: An accessibility-activity participation approach

Social equity is increasingly becoming an important objective in transport planning and project evaluation. This paper provides a framework and an empirical investigation in the Greater Toronto and Hamilton Area (GTHA) examining the links between public transit accessibility and the risks of social exclusion, simply understood as the suppressed ability to conduct daily activities at normal levels. Specifically, we use a large-sample travel survey to present a new transport-geography concept termed participation deserts, neighbourhood-level clusters of lower than expected activity participation. We then use multivariate models to estimate where, and for whom, improvements in transit accessibility will effectively increase activity participation and reduce risks of transport-related social exclusion. Our results show that neighbourhoods with high concentrations of low-income and zero-car households located outside of major transit corridors are the most sensitive to having improvements in accessibility increase daily activity participation rates. We contend that transit investments providing better connections to these neighbourhoods would have the greatest benefit in terms of alleviating existing inequalities and reducing the risks of social exclusion. The ability for transport investments to liberate suppressed activity participation is not currently being predicted or valued in existing transport evaluation methodologies, but there is great potential in doing so in order to capture the social equity benefits associated with increasing transit accessibility.     

Exploring the role of social capital influence variables on travel behaviour

This paper explores the potential role of individual trip characteristics and social capital network variables in the choice of transport mode. A sample of around 100 individuals living or working in one suburb of Madrid (i.e. Las Rosas district of Madrid) participated in a smartphone short panel survey, entering travel data for an entire working week. A Mixed Logit model was estimated with this data to analyze shifts to metro as a consequence of the opening of two new stations in the area. Apart from classical explanatory variables, such as travel time and cost, gender, license and car ownership, the model incorporated two “social capital network” variables: participation in voluntary activities and receiving help for various tasks (i.e. child care, housekeeping, etc.). Both variables improved the capacity of the model to explain transport mode shifts. Further, our results confirm that the shift towards metro was higher in the case of people “helped” and lower for those participating in some voluntary activities.     

The impacts of Internet use upon activity participation and travel: Results from a longitudinal diary-based panel study

At the outset of this research, two fields of transport research were in the ascendant. The first reflected technological change, considering the growth of new information and communications technologies and their impacts for transport systems and travel behaviour. The second reflected social change, considering the growth in inequality and disadvantage and the contribution of transport systems and travel behaviour to the same. This paper investigates a potential link between the two, exploring the hypothesis that virtual mobility, via the Internet, could provide a viable alternative to physical mobility in reducing mobility-related social exclusion. The paper presents data from a longitudinal, panel-based diary study. Results support the hypothesis that virtual mobility can provide a viable alternative to physical mobility in reducing aspects of mobility-related exclusion, by providing additional accessibility (virtual accessibility) without an increase in physical mobility. Furthermore, there is no evidence in this research to support a link between physical mobility and virtual mobility; and no evidence to suggest a negative effect of virtual mobility for sociability.     

Assessing the social costs of urban transport infrastructure options in low and middle income countries

ABSTRACT

This paper develops cost models for urban transport infrastructure options in situations where motorcycles and various forms of taxis are important modes of transport. The total social costs (TSCs) of conventional bus, Bus Rapid Transit (BRT), Monorail, Metro (Elevated Rail), car, motorcycle, Taxi and Uber are calculated for an urban corridor covering operator, user and external costs. Based on the parameters for a 7?km corridor in Hanoi, Vietnam, the results show the lowest average social cost (ASC) transport modes for different ranges of demand. Motorcycle might be the best option at low demand levels while conventional bus has advantages with low-medium demand. At medium demand levels, bus-based technologies and Monorail are competitive options while Metro, with a higher person capacity, is the best alternative at the highest demand levels. Compared to other modes, the ASCs of car and Taxi/Uber are greater because of high capital cost (related to vehicles) per passenger and low occupancy. Transport planners and decision makers in low and middle income countries (LMICs) can draw on the findings of this study. However, various limitations are identified and additional research is suggested.     

Investigating Links between Social Capital and Public Transport

Abstract

Social capital (SC) describes the advantage individuals and communities can gain from social participation, mutual assistance and trust. The provision of travel options for those who are socially disadvantaged is a major rationale for providing public transport. While there has been recent work on how transport can address social exclusion, SC has been overlooked. This article describes the theoretical basis of SC and suggests ways in which the concept might relate to public transport planning, research and practice. Disadvantaged groups can lack SC, mobility and accessibility. Public transport can provide mobility for this group and, in doing so, provide a greater opportunity to create social networks, trust and reciprocity. Although these concepts are abstract, plausible links are identified between the concepts of enhanced positive social interaction associated with the ‘livable city’ concept and those engendered in SC theory. Public transport by definition involves travelling with others and hence provides opportunities for social interaction while travelling. While a series of possible links between SC and public transport are theorized, it is unlikely these are necessarily strong since other mobility options are available and a range of land‐use and non‐transport alternatives can address social needs. Aspects of the SC concept are already covered by the social mobility and accessibility literature, although it does offer a wider insight into the potential advantages of improving access and mobility for disadvantaged communities. The concept of SC is complex and suffers from a ‘fuzzy’ definition. There is a lack of quantitative primary research associated with measuring SC. Measuring the influence of improved mobility options on SC in disadvantaged communities would be a worthwhile research area. Despite the challenges associated with researching SC, the links between SC and travel present an opportunity to understand how public transport acts to address social disadvantage through the provision of mobility to disadvantaged communities.     

Providing transport for social inclusion within a framework for environmental justice in the UK

This paper examines emerging trends in transport policy in the UK, as identified by the 2004 Transport White Paper and the supporting policy guidance to local transport authorities for addressing social exclusion through local transport provision; accessibility planning. It moves on to identify potential barriers to delivery at the local level and more fundamental challenges, risks and policy tensions. In this context, it critiques UK policies to deliver social equity through transport programmes in light of its Climate Change Agenda and the identified need to significantly reduce traffic levels on UK roads.It identifies the potential synergy between these two policy ambitions, but argues that currently there is a serious policy conflict between these agendas within the UK policy framework. In the light of this conclusion, it offers some key recommendations on the best way forward, which it recommends must be based on the synergistic and integrated delivery of policies for social and environmental equity within the transport sector. It concludes by identifying the key challenges this implies for applied research in this area.     

Developing socially inclusive transportation policy: transferring the United Kingdom policy approach to the State of Victoria?

The role of transport disadvantage in the social exclusion of low income and marginalised households and communities has received increasing academic and policy interest over the last 10 years or so. Against a backdrop of studies that have predominantly considered this issue within various national contexts, this paper offers a unique opportunity to compare different national context. The paper is informed by a commissioned study for the State of Victoria Department of Transport (Lucas, Study of transport exclusion in the state of Victoria: It doesn’t have to be this way, 2008), which wished to draw lessons from the United Kingdom in order to promote a similar policy agenda for the State. It is the authors’ contention that the issue of transport-related social exclusion is likely receive growing international policy recognition in the context of global recession, associated local job losses and reduced disposable incomes, as well as the ageing structure of most Western societies. The paper seeks to disseminate the important findings of our study about the potential for policy transfer to other national and local contexts to a wider academic, policy and practitioner audience.     

Technology engagement and privacy: A cluster analysis of reported social network use among transport survey respondents

New technologies are constantly being researched and developed to improve the sense of security of transport users. However, security technologies could also pose their own risks with regard to transport users’ privacy through the potential for data collection and storage. Transport, in particular, allows the data collector potential access to information on the users’ habits through the location information that could be collected during an individual’s interaction with technology during their travels. Some technologies, such as personal security apps (which essentially turn a smartphone into a type of panic alarm) also allow for the linking of the security technology and social networking apps. Given this link and the extent to which personal data, including location data, can be included in an individual’s social networking account, it was decided to investigate if the use of social networks could be related to individuals’ opinions on the use of their data through new technologies, such as personal security apps. This paper presents an exploration of the possibility of grouping respondents to a transport survey (N = 469) based on their answers to questions on their social networking (SNS) use. It was hypothesised that if distinct groups exist within the SNS data, then they could be used as a supplementary personal variable for underlying privacy concerns and levels of engagement with technology in future transport studies. This would be in addition to the socio-demographic information collected in the survey. This paper presents the initial dimension reduction of the response variables to create composite variables. That is followed by the exploratory clustering of responses using two-step cluster analysis. Finally, the paper discusses the hypothesis testing of the resultant clusters against the socio-demographic responses to ascertain if additional information is provided by the clustering results. The transport survey responses were collected in Ireland, and a subset of responses, from the Greater Dublin Area, were used for the analysis in this paper. The results demonstrate that there is scope for this type of method to be used when researching new security technologies in transport.     

Exploring the capacity of social media data for modelling travel behaviour: Opportunities and challenges

In the past few years, the social science literature has shown significance attention to extracting information from social media to track and analyse human movements. In this paper the transportation aspect of social media is investigated and reviewed. A detailed discussion is provided about how social media data from different sources can be used to indirectly and with minimal cost extract travel attributes such as trip purpose, mode of transport, activity duration and destination choice, as well as land use variables such as home, job and school location and socio-demographic attributes including gender, age and income. The evolution of the field of transport and travel behaviour around applications of social media over the last few years is studied. Further, this paper presents results of a qualitative survey from travel demand modelling experts around the world on applicability of social media data for modelling daily travel behaviour. The result of the survey reveals positive view of the experts about usefulness of such data sources.     

Tweeting Transit: An examination of social media strategies for transport information management during a large event

Social media platforms are seeing increasing adoption by public transport agencies, as they provide a cost-effective, reliable, and timely mechanism for sharing information with passengers and other travellers. In this paper, we use a case study of the @GamesTravel2014 Twitter account to evaluate how this social media platform was used over the course of the 2014 Commonwealth Games in Glasgow, Scotland to provide and share transport-related information and respond to information requests. The case study provides an exemplar for the public co-ordination of information from multiple partners in a complex environment during a time of transport disruption. We evaluate both the structure and intent of the @GamesTravel2014 social media strategy via interviews with involved parties and an analysis of Tweets related to the account. Findings indicate the potential for future applications of social media by transport operators and authorities in producing a more effective network of communication with passengers.     

Modelling the relationship between travel behaviours and social disadvantage

The purpose of this paper is to model the travel behaviour of socially disadvantaged population segments in the United Kingdom (UK) using the data from the UK National Travel Survey 2002–2010. This was achieved by introducing additional socioeconomic variables into a standard national-level trip end model (TEM) and using purpose-based analysis of the travel behaviours of certain key socially disadvantaged groups. Specifically the paper aims to explore how far the economic and social disadvantages of these individuals can be used to explain the inequalities in their travel behaviours.The models demonstrated important differences in travel behaviours according to household income, presence of children in the household, possession of a driver’s licence and belonging to a vulnerable population group, such as being disabled, non-white or having single parent household status. In the case of household income, there was a non-linear relationship with trip frequency and a linear one with distance travelled. The recent economic austerity measures that have been introduced in the UK and many other European countries have led to major cutbacks in public subsidies for socially necessary transport services, making results such as these increasingly important for transport policy decision-making. The results indicate that the inclusion of additional socioeconomic variables is useful for identifying significant differences in the trip patterns and distances travelled by low-income.     

Automating a framework to extract and analyse transport related social media content: The potential and the challenges

Harnessing the potential of new generation transport data and increasing public participation are high on the agenda for transport stakeholders and the broader community. The initial phase in the program of research reported here proposed a framework for mining transport-related information from social media, demonstrated and evaluated it using transport-related tweets associated with three football matches as case studies. The goal of this paper is to extend and complement the previous published studies. It reports an extended analysis of the research results, highlighting and elaborating the challenges that need to be addressed before a large-scale application of the framework can take place. The focus is specifically on the automatic harvesting of relevant, valuable information from Twitter. The results from automatically mining transport related messages in two scenarios are presented i.e. with a small-scale labelled dataset and with a large-scale dataset of 3.7 m tweets. Tweets authored by individuals that mention a need for transport, express an opinion about transport services or report an event, with respect to different transport modes, were mined. The challenges faced in automatically analysing Twitter messages, written in Twitter’s specific language, are illustrated. The results presented show a strong degree of success in the identification of transport related tweets, with similar success in identifying tweets that expressed an opinion about transport services. The identification of tweets that expressed a need for transport services or reported an event was more challenging, a finding mirrored during the human based message annotation process. Overall, the results demonstrate the potential of automatic extraction of valuable information from tweets while pointing to areas where challenges were encountered and additional research is needed. The impact of a successful solution to these challenges (thereby creating efficient harvesting systems) would be to enable travellers to participate more effectively in the improvement of transport services.     

An exploration of the importance of social influence in the decision to start bicycling in England

The purpose of this paper is to gain a better understanding, through qualitative exploration, of the ways in which social influence affects the decision to start bicycling in England. ‘Social influence’ is defined as the process by which an individual’s thoughts and actions are changed by the thoughts and action of others. Its role was investigated at three levels: the immediate family, household members and significant others (direct social influence); the extended family, friends, peers and colleagues (less direct social influence); and the wider cultural context (indirect social influence). Interviews with 61 individuals living in 12 towns and cities across England were analysed. Half of the interviewees were new regular bicyclists and the other half did not bicycle at all, or only occasionally. Social influence was found to be the dominant factor for a minority of the cases where participants started bicycling regularly. It played a role alongside other factors in other cases. It could take the form of direct influence from family, friends and peers or indirect influence from the social and cultural context. The analysis illustrates the difficulty of capturing social influence which is often hidden and emerges incidentally in the course of the interviews and interacts with other contributing factors. The role of social influence found in this research challenges the rational approach to explaining travel decision making that has traditionally dominated transport studies. The paper suggests that social processes could be harnessed to improve the efficacy of bicycling promotion programs.     

Functional requirements for inclusive transport

Transport related social exclusion is one aspect of people with disabilities’ marginal position in economic, social and civic life. This study aims at presenting main tendencies in empirical research on transport and disability, and therein defining functional requirements that transport solutions must comply with in order to facilitate social inclusion. Based on review of thirty-four empirical studies, this study presents eight functional requirements for inclusive transport. Aspects of each requirement are described and links to social exclusion are explored. Further, the strengths and limits of the review as well as relevance for practice is discussed. Although the study is limited to research in English and Scandinavian languages, the authors believe that the transferability of the results beyond the geographical scope of this study is not challenged by the requirements themselves, but rather to what degree and in what ways these requirements are championed and pursued. The functional requirements are defined without reference to particular travel purposes or mode of transport and represent a systematic approach for making discretional assessment of transport solutions.

     

Exploring the propensity to perform social activities: a social network approach

Conceptual and empirical models of the propensity to perform social activity–travel behavior are described, which incorporate the influence of individuals’ social context, namely their social networks. More explicitly, the conceptual model develops the concepts of egocentric social networks, social activities, and social episodes, and defines the three sets of aspects that influence the propensity to perform social activities: individuals’ personal attributes, social network composition, and information and communication technology interaction with social network members. Using the structural equation modeling (SEM) technique and data recently collected in Toronto, the empirical model tests the effect of these three aspects on the propensity to perform social activities. Results suggest that the social networks framework provides useful insights into the role of physical space, social activity types, communication and information technology use, and the importance of “with whom” the activity was performed with. Overall, explicitly incorporating social networks into the activity–travel behavior modeling framework provides a promising framework to understand social activities and key aspects of the underlying behavioral process. Juan Antonio Carrasco a PhD candidate in Civil Engineering at the University of Toronto, holds a MSc degree in Transportation Engineering from the Pontificia Universidad Católica de Chile. His doctoral research explores the relationships between social networks, activity–travel behavior, and ICTs. His research interests also include microsimulation, land use-transportation, and econometric modeling. Eric J. Miller is Bahen-Tanenbaum Professor of Civil Engineering at the University of Toronto where he is also Director of the Joint Program in Transportation. His research interests include integrated land-use/transportation modeling, activity-based travel modeling, microsimulation and sustainable transportation planning.     

An empirical investigation into the time-use and activity patterns of dual-earner couples with and without young children

This paper examines the time-use patterns of adults in dual-earner households with and without children as a function of several individual and household socio-demographics and employment characteristics. A disaggregate activity purpose classification including both in-home and out-of-home activity pursuits is used because of the travel demand relevance of out-of-home pursuits, as well as to examine both mobility-related and general time-use related social exclusion and time poverty issues. The study uses the Nested Multiple Discrete Continuous Extreme Value (MDCNEV) model, which recognizes that time-decisions entail the choice of participating in one or more activity purposes along with the amount of time to invest in each chosen activity purpose, and allows generic correlation structures to account for common unobserved factors that might impact the choice of multiple alternatives. The 2010 American Time Use Survey (ATUS) data is used for the empirical analysis. A major finding of the study is that the presence of a child in dual-earner households not only leads to a reduction in in-home non-work activity participation (excluding child care activities) but also a substantially larger decrease in out-of-home non-work activity participation (excluding child care and shopping activities), suggesting a higher level of mobility-related social exclusion relative to overall time-use social exclusion. To summarize, the results in the paper underscore the importance of considering household structure in activity-based travel demand models, as well as re-designing work policies in the United States to facilitate a reduction in work-family conflict in dual-earner families.     

A latent class accelerated hazard model of social activity duration

Over the past decade, activity scheduling processes have gained increasing attention in the field of transportation research. However, still little is known about the scheduling of social activities even though these activities account for a large and growing portion of trips. This paper contributes to this knowledge. We analyze how the duration of social activities is influenced by social activity characteristics and characteristics of the relationship between the respondent and the contacted person(s). To that end, a latent class accelerated hazard model is estimated, based on social interaction diary data that was collected in the Netherlands in 2008. Chi-square tests and analyses of variance are used to test for significant relations between the latent classes and personal and household characteristics. Findings suggest that the social activity characteristics and the characteristics of the relationship between the socializing persons are highly significant in explaining social activity duration. This shows that social activities should not be considered as a homogenous set of activities and it underlines the importance of including the social context in travel-behavior models. Moreover, the results indicate that there is a substantial amount of latent heterogeneity across the population. Four latent classes are identified, showing different social activity durations, and different effects for both categories of explanatory variables. Latent class membership can be explained by household composition, socio-economic status (education, income and work hours), car ownership and the number of interactions in 2 days.     

Measuring social effective speed to improve sustainable mobility policies in developing countries

Over the last few decades, many developing countries have experienced car fleet growth, which has contributed to congestion, increased travel times, and deteriorated public transport reliability and punctuality. However, alternatives to urban mobility can be found by creating policies to stimulate sustainable transportation modes with equal opportunities for all citizens. In this paper, measures of social effective speeds are presented to improve sustainable urban mobility policies in developing countries. Data from the 2018 Origin-Destination Survey of the Metropolitan Region of Recife (Brazil) were used to estimate social effective speeds. The results showed that motorized modes had lower effective speed than non-motorized modes. In addition, total external costs were $2 billion USD per year. The social effective speed will be valuable if inserted in sustainable urban mobility policies in developing countries.