Capturing the impact of individual characteristics on transport accessibility and equity analysis. (October 2020)

• Record Type: Journal Article
• Authors: Dixit, Malvika; Sivakumar, Aruna
• Is Part Of: Transportation research. Volume 87(2020)
• Publication Date: 2020-10
• Subjects: Accessibility -- Transport equity -- Logsum measures -- Individual characteristics -- Disaggregate analysis; Transportation -- Research -- Periodicals; Transportation -- Environmental aspects -- Periodicals; 354.76
• DOI: 10.1016/j.trd.2020.102473
• Languages: English
• ISSNs: 1361-9209

Abstract

Highlights: Use logsum to assess impact of individual characteristics on transport equity & accessibility. Alternate formulations of logsum with and without individual characteristics are compared. Ignoring individual characteristics leads to an underestimation of variability in accessibility. Individual characteristics in logsum measures provide more insight into the causes of inequity. Abstract: Transport accessibility experienced by an individual depends on their needs and abilities, as represented by their individual characteristics, such as age, income and gender. Although important from an equity perspective, the individual component of accessibility is currently ignored in most transport equity studies. This paper evaluates the impact of including individual characteristics into logsum-based accessibility measures for transport equity analysis. Using data from the London Travel Demand Survey (LTDS) 2011–13, two alternate logsum measures of accessibility are specified – with and without individual characteristics. An empirical analysis of spatial, social and economic equity is conducted using both the measures, and the outcomes are compared. The results clearly demonstrate that ignoring individual characteristics in logsum measures of accessibility can lead to unreliable outcomes for social and economic equity analysis, but do not add significant value when aggregated across large geographical zones for spatial equity analysis. Overall, ignoring individual characteristics masks the disparity in distribution of accessibility, as measured by the Gini index. Although not straightforward, the difference between accessibility patterns using the two logsum measures also yields insights into the possible causes of inequity, which can provide actionable inputs to policy makers. The study highlights that personal needs and abilities are often responsible for accessibility variations among individuals and ignoring them can result in a misleading picture of equity, as demonstrated quantitatively in this paper.