Piecing it Together: A Structural Equation Model of Transport, Social Exclusion and Well-Being

Abstract

Abstract Purpose — This chapter describes the process used to empirically link the concepts of transport disadvantage, social exclusion and well-being. It fills three important gaps in the research literature: (1) the empirical limitations in measuring the relationship between transport disadvantage and social exclusion, (2) the somewhat homogenous groups used in most studies of social exclusion and (3) the lack of integration with measures of well-being. Methodology — Structural equation modelling (SEM) is a statistical methodology that examines the underlying structural relationship between variables and displays these relationships pictorially. The methods used to define and measure transport disadvantage, social exclusion and well-being are described. SEM uses principal component analyses to isolate underlying ‘latent’ variables (e.g. social exclusion) using measurable ‘observed’ variables (e.g. income, being employed or not). Regression techniques are then used to examine the structural relationships between these three variables. Findings — Modelling of the hypothesised relationships between the three variables showed a good statistical fit. The link between transport disadvantage and social exclusions was of a medium–small size (0.28) and statistically significant. Social exclusion had a larger and statistically significant negative impact on well-being (−0.73). Transport disadvantage also had a small but direct negative impact on well-being (−0.15).