Construction and validation of a public bus passenger safety scale. (October 2019)

• Record Type: Journal Article
• Authors: Sam, Enoch F.; Brijs, Kris; Daniels, Stijn; Brijs, Tom; Wets, Geert
• Is Part Of: Transportation research. Volume 66(2019)
• Page Start: 47
• Page End: 62
• Publication Date: 2019-10
• Subjects: Scale development -- Public bus passengers -- Safety evaluations -- Psychometric properties; Automobile drivers -- Psychology -- Periodicals; Automobile driving -- Psychological aspects -- Periodicals; Transportation -- Psychological aspects -- Periodicals; 629.283019
• DOI: 10.1016/j.trf.2019.08.017
• Languages: English
• ISSNs: 1369-8478

Abstract

Highlights: No scale exist to measure public bus users' safety evaluations. The public bus passenger safety scale measures three facets of PT users' safety. The new scale evidenced adequate reliability and validity. Abstract: Public transport (PT) passengers make safety evaluations, yet to the best of our knowledge, there exists no instrument that captures what is considered by public transport users when they make such personal safety evaluations. What exists is a generalised service quality scale (SERVQUAL). Unfortunately, this scale does not adequately capture the content domain of personal safety which is important to PT users, especially in developing countries where PT vehicle accidents are both frequent and severe. This study discusses the development and validation of a public bus passenger safety scale (PBPSS), for measuring public bus passengers' safety. The results of two independent studies suggest that the PBPSS measures three facets of public bus passengers' safety: driver-related, transport operator-related and vehicle-related. Through both exploratory Principal Component Analysis (PCA) and Confirmatory Factor Analysis (CFA) (using IBM SPSS Statistics and AMOS respectively), we demonstrated that the new scale is reliable, psychometrically sound and can be utilised to assess public bus passengers' safety. The 3-factor model observed through PCA was confirmed using CFA, indicating that the same factor structure existed in both datasets. The final 3-factor, 17-item model exhibited an acceptable model fit and evidenced both convergent and discriminant validity.