Abstract
Introduction: Travel behaviour research involves the study of both the economic and behavioural (or sociological) aspects of travel. Numerous factors influence the demand for travel in complex ways, resulting in intricate causal relationships which require the use of a wide range of data analysis methodologies and interpretations. This study provides an overview of travel behaviour research conducted in developing countries in order to gain insight into the factors that influence travel demand and the methodologies used to investigate them. Methods: Four multi-subject electronic databases were searched, and the inclusion criteria adopted was in line with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Twenty studies met our inclusion criteria. Results: The main methods of analysis used in the studies reviewed are rooted in multivariate regression models and structural equation modeling with the most predominant methods being SEM and the MNL. The studies reviewed show that age, gender, income, work status, education level, family size, cost, and availability of travel modes are the most important factors influencing travel demand in developing cities. Conclusion: The findings serve as a resource for scholars interested in this subject, as they provide insights that may be used to perform better travel demand studies. There is need for the development of a general modeling framework and guidelines for selecting appropriate models for use in travel behaviour research.