Exploring the connections among job accessibility, employment, income, and auto ownership using structural equation modeling

Abstract

Using structural equation modeling, this study empirically examines the connections between job accessibility, workers per capita, income per capita, and autos per capita at the aggregate level with year 2000 census tract data in Sacramento County, CA. Under the specification of the conceptual model, the model implied covariance matrix exhibits a reasonably good fit to the observed covariance matrix. The direct and total effects are largely consistent with theory and/or with empirical observations across a variety of geographic contexts. It is demonstrated that structural equation modeling is a powerful tool for capturing the endogeneity among job accessibility, employment, income, and auto ownership.

Car ownership as a mediating variable in car travel behaviour research using a structural equation modelling approach to identify its dual relationship

“…We removed five outliers at a time and observed the changes in goodness-of-fit indices of the model and individual parameter estimates. Comparable to other studies (e.g., Gao et al, 2008), we found that the χ ² statistic generally increased after each step of removing outliers. This indicates a worse-fitting model since the χ ² statistic is the product of the sample size minus one (N-1) and the minimized fit function (F min ) (Byrne, 2001, p. 78;Kline, 2005, p. 135).…”

“…Total effects are the sum of direct and indirect effects. Whereas other studies sometimes find opposing direct and indirect effects (e.g., Gao et al, 2008;), all variables with a direct as well as an indirect influence have synergistic effects resulting in even larger total effects. However, focusing on direct effects only would lead to inconsistent conclusions in some cases.…”

“…Most studies pointed out that accessibility is negatively associated with car ownership (e.g., Chen et al, 2008;Gao et al, 2008;Kockelman, 1997;Simma and Axhausen, 2003). Rajamani et al (2003) found that higher accessibility by a given mode is likely to result in higher usage of that mode.…”

How much is enough? Assessing the influence of neighborhood walkability on undertaking 10-minute walks

“…In this regard, various parking policies can be explored as a way to discourage households from purchasing a vehicle. Furthermore, improving transit services in a neighborhood can contribute to reducing car ownership as greater accessibility to jobs by transit leads to lower amount of vehicles per capita (Gao, Mokhtarian, & Johnston, 2008). In sum, multiple transport policies can be implemented as a way to reduce car ownership and support healthy walking behavior in various walkable environments.…”

The Impact of Employer Attitude to Green Commuting Plans on Reducing Car Driving: A Mixed Method Analysis

“…However, focusing on direct effects only would lead to inconsistent conclusions in some cases [26,27]. Based on the extended conditional logit choice model by incorporating mediating variable with a structural equation model, the indirect effects of socio-demographic attributes, and latent variables through mediating variable car ownership were recognized.…”