Identifying key explanatory variables for cycling in Sub-Saharan Africa : Case study : Quelimane (Mozambique)

Abstract

Cycling is widely perceived as healthy, environmentally friendly, enables easy access to jobs, and also provides flexible jobs. Cycling is influenced by many factors such as personal characteristics, attitudinal factors, built environment factors and natural and environmental factors. However, the intensity of these factors on cycling is very influenced by the urban context, and in medium-size Sub-Saharan Africa (SSA) cities it has been very little tested.The main objective of this study is to identify who are the cyclists and where they cycle. The study searches for empirical pieces of evidence from data collected among 1084 commuters of Quelimane, a medium-sized city in central Mozambique. First, a literature review is conducted to explore the existing cyclist groups in SSA cities and factors influencing their cycling behaviour. Then, to identify who are the cyclists, the underlying factors structuring the population sample were determined through factor analysis, and a clustering process was applied. Cyclists' travel patterns were then recreated using GIS to assess the influence of road quality on cycling. The results identified three clusters of cycling commuters: informal workers with children, short-distance students, and occasional cyclists. The clusters were based on household composition, employment status and cycling frequency to work/school. It was found that over 40% of cycling trips took place within the city periphery and about 10% between the city periphery and suburban areas. Most people cycle to carry products to sell in local markets and as a bicycle-taxi. The study findings provided a clear understanding of commuter cyclists and served as an empirical basis for developing more targeted policies to encourage cycling. Next, attitudinal market segmentation approach was used to identify potential markets of bicycle commuters. Factor analysis is used to identify key latent factors and Structural Equation Modelling (SEM) estimates the correlation between those latent factors. Then, TwoStep clustering process is used to segment the bicycle commuting market into several submarkets. Three attitudinal market segments are obtained which are Demanding cyclists, Cautious cyclists, and Forced cyclists. The study reveals that Demanding Cyclists have the most positive attitude towards cycling and they could be motivated to more cycling by providing proper cycling facilities and improved traffic and good road infrastructure conditions. The Cautious Cyclists with moderate and low cycling attitude could be motivated to increased cycling by providing easy access to bicycles. The Forced Cyclists with a high need for the economy cycle purposely to generate income. The results provide a basis to plan and develop policies and promotional strategies that most serve the needs of each market segment for increased bicycle commuting. To identify where people cycle, the importance that 9 cycling route choice variables received from individuals in 3 attitudinal cycling segments (identified in the previous chapter) was assess...