Final Report Summary - TRANSENDANC (Transport and Social Exclsuion: New Directions and National Comparisons)
The TranSENDaNC (Transport and Social Exclusion: New Directions and National Comparisons) project has been about bringing together researchers from the UK, Belgium and Chile to share their experience and knowledge on the topic of transport-related social exclusion (TRSE). An over-arching aim for the project was to develop a network of researchers and policy makers to compare transport and social exclusion in different national contexts and to convert state-of-the-art research knowledge into improved policy practices.
TRSE generally refers to individuals who lack the necessary transport resources needed to connect with everyday activities within the societies in which they live. Previous studies have shown it has many causal factors, which can be social, cultural, political and/or physical in nature. Past studies have highlighted the key roles played by low income/financial hardship, accessibility deficiencies due to mismatches between the supply of transport and the distribution of land uses and activity spaces, and low social capital This study has sought to develop a deeper understanding of TRSE by considering the linkages between financial hardship, accessibility deficiencies and low social capital in different geographical contexts – i.e. Merseyside (Liverpool) in the UK, Ghent in Belgium and Los Ángeles in Chile.
The research has been carried out in five distinct but overlapping phases: (1) exploration of the three core components of TRSE - transport disadvantage, social exclusion and social capital ; (2) derivation of a set of indicators for the objective and subjective measurement of three identified core components of TRSE; (3) empirical application of these indicators using various national and local level datasets; (4) qualitative explorations of the linkages between transport disadvantage, social exclusion and social capital; and (5) integrating the findings and communicating the implications for future research and policy.
Phase 1: Developing concepts and definitions
A review of the academic literature suggested that transport disadvantage, social exclusion and social capital are three key elements of TRSE; that each elements needs to be defined carefully; and that the linkages between them are heterogeneous and complex. As part of TranSENDaNC transport disadvantage has been defined as a relational and dynamic outcome of a lack of access to basic resources, activities and opportunities for interactions, of a lack of cognitive knowledge, know-how, aspirations and/or autonomy regarding travel and its externalities, and of a lack of influence on decision-making in the context of transport policy and governance. Transport disadvantage can be both absolute and relative, and it occurs at both individual and collective levels. Social exclusion has been defined as low levels of access to, participation in, and autonomy with regard to, economic life (including finances, employment and education), political life (including policymaking and governance), social life (including social ties and activities), cultural life (including public debate, arts and media) and health (both physical and mental). Social capital has been defined a person’s social network and the social resources or support that are embedded within them: their influence can be two directional in that they can both can prevent mobility or be seen as an alternative for participation. Central to our study is the idea that transport disadvantage, social exclusion and social capital can be understood as entwined processes.
Phase 2: Indicators development
A large set of potential indicators has been reviewed in order to articulate the potential interactions between transport disadvantage, social exclusion and social capital. This has led to the development of a composite ‘mobility/participation’ index (MPI) that is based on six indicators: (1) number of trips, (2) number of activity types participated in, (3) number of unique activity locations visited, (4) time spent out of home, (5) standard deviational ellipse, and (6) network distance travelled. The first four indicators can be derived from activity travel survey data, the latter two require specific analysis in a geographical information system (GIS).
Phase 3: Empirical analysis in the three case study cities
The main empirical analysis was undertaken using datasets that were already available from past studies in the 3 study cities of Ghent (Belgium), Los Ángeles in (Chile) and Merseyside (UK). Canonical correlation analysis has been used to identify the main determinants of the MPI in each city. The results indicate that education, age and combinations of gender and availability of specific transport modes (cars, bikes) help to explain variations in the scores on the MPI. However, the exact nature of the relationships differs across the individual cities. The analysis suggests a complex interplay between the personal attributes, capabilities and responsibilities of individuals and the spatiotemporal opportunities that are available to them within the specific cities in which they live. As such, it would seem to be important to consider both measures of personal mobility and the level of their participation in activities if we are to understand how transport-related social exclusion occurs within a given time and space.
Phase 4: The role of social capital and social networks
Two complementary lines of research have been pursued. First, a quantitative analysis has been undertaken of social networks dataset of 241 people living in Concepción across four different neighborhoods, two of which have low and two high incomes. A measure of accessibility to social networks and support has been specified and calculated, and this was related to indicators of transport and activity disadvantage for the 241 study participants. The findings are inconclusive: there was no statistically significant relationship between activity disadvantage and accessibility to social networks and support, although low-income households tended to experience some transport disadvantage when accessing social support.
Second, qualitative follow-up interviews have been undertaken with a subsample of 18 participants in the two low-income neighborhoods in Concepción to explore the everyday mobility challenges that different age groups face in these areas. Across age groups, official transport information provision was reported as not sufficient, and indicated to be potentially affecting mobility and social network. The price of public transportation is an issue, so is its infrequency after certain time of the day, and the lack of routes through certain areas. The ownership of automobiles is widely considered positive and improving life quality. People’s mobility choices and strategies to maintain their social networks also seem to depend on their generational experience of being exposed to the latest ICT technologies. The adoption of information and communications technologies (ICTs) and digital devices varies across age groups but the gap is noticeably shrinking.
Phase 5: Integration and Communication
Trying to capture and measure the ephemeral links between the three components of transport disadvantage, social exclusion and social capital remains a challenge. This is true even when, as we have attempted here, different datasets, methodologies approaches and analytical techniques from across the engineering and social sciences are brought together. Nonetheless, with some modification and the right datasets, composite indicators of mobility, accessibility and social capital offer a good opportunity to identify the processes whereby transport disadvantage leads to social exclusion and/or positive or negative consequences for social capital and vice versa. It will be necessary to conduct dedicated comparative studies in different geographical contexts to make any real further progress in this respect.
Our study has led to a number of successful workshops, seminars and bi-lateral meetings with policymakers in the Belgium, Chile and the UK and elsewhere in Europe to present our methodologies and consider the potential for further research. There is clearly a growing interest in this topic amongst policymakers who are concerned that austerity measures may lead to cutbacks in essential transport services, which will exacerbate the problem of transport-related social exclusion in many deprived areas of the city and urban periphery.
TRSE generally refers to individuals who lack the necessary transport resources needed to connect with everyday activities within the societies in which they live. Previous studies have shown it has many causal factors, which can be social, cultural, political and/or physical in nature. Past studies have highlighted the key roles played by low income/financial hardship, accessibility deficiencies due to mismatches between the supply of transport and the distribution of land uses and activity spaces, and low social capital This study has sought to develop a deeper understanding of TRSE by considering the linkages between financial hardship, accessibility deficiencies and low social capital in different geographical contexts – i.e. Merseyside (Liverpool) in the UK, Ghent in Belgium and Los Ángeles in Chile.
The research has been carried out in five distinct but overlapping phases: (1) exploration of the three core components of TRSE - transport disadvantage, social exclusion and social capital ; (2) derivation of a set of indicators for the objective and subjective measurement of three identified core components of TRSE; (3) empirical application of these indicators using various national and local level datasets; (4) qualitative explorations of the linkages between transport disadvantage, social exclusion and social capital; and (5) integrating the findings and communicating the implications for future research and policy.
Phase 1: Developing concepts and definitions
A review of the academic literature suggested that transport disadvantage, social exclusion and social capital are three key elements of TRSE; that each elements needs to be defined carefully; and that the linkages between them are heterogeneous and complex. As part of TranSENDaNC transport disadvantage has been defined as a relational and dynamic outcome of a lack of access to basic resources, activities and opportunities for interactions, of a lack of cognitive knowledge, know-how, aspirations and/or autonomy regarding travel and its externalities, and of a lack of influence on decision-making in the context of transport policy and governance. Transport disadvantage can be both absolute and relative, and it occurs at both individual and collective levels. Social exclusion has been defined as low levels of access to, participation in, and autonomy with regard to, economic life (including finances, employment and education), political life (including policymaking and governance), social life (including social ties and activities), cultural life (including public debate, arts and media) and health (both physical and mental). Social capital has been defined a person’s social network and the social resources or support that are embedded within them: their influence can be two directional in that they can both can prevent mobility or be seen as an alternative for participation. Central to our study is the idea that transport disadvantage, social exclusion and social capital can be understood as entwined processes.
Phase 2: Indicators development
A large set of potential indicators has been reviewed in order to articulate the potential interactions between transport disadvantage, social exclusion and social capital. This has led to the development of a composite ‘mobility/participation’ index (MPI) that is based on six indicators: (1) number of trips, (2) number of activity types participated in, (3) number of unique activity locations visited, (4) time spent out of home, (5) standard deviational ellipse, and (6) network distance travelled. The first four indicators can be derived from activity travel survey data, the latter two require specific analysis in a geographical information system (GIS).
Phase 3: Empirical analysis in the three case study cities
The main empirical analysis was undertaken using datasets that were already available from past studies in the 3 study cities of Ghent (Belgium), Los Ángeles in (Chile) and Merseyside (UK). Canonical correlation analysis has been used to identify the main determinants of the MPI in each city. The results indicate that education, age and combinations of gender and availability of specific transport modes (cars, bikes) help to explain variations in the scores on the MPI. However, the exact nature of the relationships differs across the individual cities. The analysis suggests a complex interplay between the personal attributes, capabilities and responsibilities of individuals and the spatiotemporal opportunities that are available to them within the specific cities in which they live. As such, it would seem to be important to consider both measures of personal mobility and the level of their participation in activities if we are to understand how transport-related social exclusion occurs within a given time and space.
Phase 4: The role of social capital and social networks
Two complementary lines of research have been pursued. First, a quantitative analysis has been undertaken of social networks dataset of 241 people living in Concepción across four different neighborhoods, two of which have low and two high incomes. A measure of accessibility to social networks and support has been specified and calculated, and this was related to indicators of transport and activity disadvantage for the 241 study participants. The findings are inconclusive: there was no statistically significant relationship between activity disadvantage and accessibility to social networks and support, although low-income households tended to experience some transport disadvantage when accessing social support.
Second, qualitative follow-up interviews have been undertaken with a subsample of 18 participants in the two low-income neighborhoods in Concepción to explore the everyday mobility challenges that different age groups face in these areas. Across age groups, official transport information provision was reported as not sufficient, and indicated to be potentially affecting mobility and social network. The price of public transportation is an issue, so is its infrequency after certain time of the day, and the lack of routes through certain areas. The ownership of automobiles is widely considered positive and improving life quality. People’s mobility choices and strategies to maintain their social networks also seem to depend on their generational experience of being exposed to the latest ICT technologies. The adoption of information and communications technologies (ICTs) and digital devices varies across age groups but the gap is noticeably shrinking.
Phase 5: Integration and Communication
Trying to capture and measure the ephemeral links between the three components of transport disadvantage, social exclusion and social capital remains a challenge. This is true even when, as we have attempted here, different datasets, methodologies approaches and analytical techniques from across the engineering and social sciences are brought together. Nonetheless, with some modification and the right datasets, composite indicators of mobility, accessibility and social capital offer a good opportunity to identify the processes whereby transport disadvantage leads to social exclusion and/or positive or negative consequences for social capital and vice versa. It will be necessary to conduct dedicated comparative studies in different geographical contexts to make any real further progress in this respect.
Our study has led to a number of successful workshops, seminars and bi-lateral meetings with policymakers in the Belgium, Chile and the UK and elsewhere in Europe to present our methodologies and consider the potential for further research. There is clearly a growing interest in this topic amongst policymakers who are concerned that austerity measures may lead to cutbacks in essential transport services, which will exacerbate the problem of transport-related social exclusion in many deprived areas of the city and urban periphery.