Bibliometric analysis of quality of service in public transportation: Current and future trends

Abstract

Public transport is a fundamental aspect of urban life and its quality of service can significantly impact the daily life of passengers. Research on quality of service in public transport is vital to creating efficient and inclusive public transport systems. This study which is both timely and imperative, provides a systematic literature review and bibliometric analysis of quality of service in public transport with special focus on gender and machine learning. The study employed a systematic search in Web of Science using relevant keywords. Based on 270 published articles on the Web of Science, we evaluate the state of knowledge through keyword analysis, co-occurrences, and co-citations. It appears that key themes in quality of service in public transportation have shifted from efficiency to user satisfaction and perceptions. However, there is limited literature on public transport service quality in the global south, particularly in Africa, compared to the global north. In particular, the study revealed that the total publications focusing on gender in Africa is two. Moreover, much of the literature on the African continent emanates from authors and countries outside the continent. It often does not reflect the lived realities of the state of public transport in Africa. Similarly, emerging issues pertaining to machine learning and gender in public transport also require consideration. This paper paves the way for policy, practice, and further research. The review will be useful reference for evolutions of quality of service in public transport research.

Keywords

• Prisma
• Vosviewer
• Quality of service
• Public transport
• Gender
• Machine learning