Measuring commuting satisfaction: validation of the commuting satisfaction scale in the Australian context
Authors: Stephan Bischof, Ferdi Botha, Inga Laß & Heiko Rüger.
Abstract
Commuting satisfaction is an important sub-domain of subjective well-being, with commuting dissatisfaction linked to lower well-being and negative spillovers into other life domains. Valid and comprehensive measures of commuting satisfaction are therefore imperative.
The Commuting Satisfaction Scale (CSS) is designed to assess satisfaction across seven core aspects of commuting. It is intended for use in a variety of settings, including different travel modes, distances, and urban and rural environments. However, the CSS has only been validated once, in a selective sample of commuters in large cities worldwide during the pre-pandemic period. This limits the generalisability and transferability of the findings.
Using data from 2,107 workers from three waves of the Melbourne Institute–Roy Morgan Taking the Pulse of the Nation (TTPN) survey in Australia, this study validates the CSS for the first time in a general population survey from the post-pandemic period. We employ multiple validation tests, including internal consistency testing, exploratory factor analysis, and assessments of construct and criterion-related validity. Results indicate a one-factor structure with high internal consistency across travel modes and residential contexts. Commuters are most satisfied with safety from crime and least with crowding.
Commuting satisfaction is higher among physically active (i.e., walking or cycling) and rural commuters. Longer commuting times are associated with lower commuting satisfaction. Higher commuting satisfaction correlates with lower mental distress and job leaving intentions, but higher life and job satisfaction. These findings provide supportive evidence that the CSS is a reliable and valid instrument in various commuting contexts.
Margin of Error
The margin of error to be allowed for in any estimate depends mainly on the number of interviews on which it is based. Margin of error gives indications of the likely range within which estimates would be 95% likely to fall, expressed as the number of percentage points above or below the actual estimate. Allowance for design effects (such as stratification and weighting) should be made as appropriate.
| Sample Size | Percentage Estimate |
| 40% – 60% | 25% or 75% | 10% or 90% | 5% or 95% | |
| 1,000 | ±3.0 | ±2.7 | ±1.9 | ±1.3 |
| 5,000 | ±1.4 | ±1.2 | ±0.8 | ±0.6 |
| 7,500 | ±1.1 | ±1.0 | ±0.7 | ±0.5 |
| 10,000 | ±1.0 | ±0.9 | ±0.6 | ±0.4 |
| 20,000 | ±0.7 | ±0.6 | ±0.4 | ±0.3 |
| 50,000 | ±0.4 | ±0.4 | ±0.3 | ±0.2 |
