Photo: African Urban Transport

The Lagos State University, Lagos, Nigeria

Comparative Analysis of the E-Hailing Mobility Services in Selected Cities In West, East and Southern Africa

EP-2019-MAC-08, Professor Samuel Gbadebo Odewumi

 

Abstract

Mobility and Access in sub-Saharan Africa is perennially challenged. Many solutions have been thrown at it but the problem keeps escalating. Emerging recently and spreading widely, is the shared mobility solution, taking advantage of the boom in ICT; bringing under its umbrella many of the existing informal modes like Car-taxi, Tricycle, Motorcycle, Bicycle variously called “Okada”,”Boda-boda” and “Keke” in many sub-Saharan African countries. In Nigeria, all these are termed “e-hailing” services.

However, there has been very little known study of this emerging business model. Is the rapid growth an indication of its acceptability or limited choices for the users? What are the challenges, opportunities and threats facing it? What is the role of government in it?

We are therefore motivated to undertake an exploratory research into this emerging business model and compare it across the west, east and southern Africa as represented by Lagos, Nairobi and Johannesburg. It is an investigation into types, coverage and operations of the e-hailing services. We seek to identify the source and feature of the applications; reveal the demographic characteristics and the attitude of the operators of the services; their competitors and relevant governments’ official to e-hailing business. We will compare the travel time and travel costs of the e-hailing with the traditional equivalents.

For data collection and analysis, our methods shall include participant observer whereby field enumerators will take at least 40 rides on each mode while obtaining information of routes, time and cost with the GPS. Data Extraction, using Map-source will be used to chart the trips, time and costs; accompanied with structured and unstructured questionnaire for demographic and opinion survey of the stakeholders. To aid our analysis we descriptive statistics is adopted to summarize and classify the quantitative data, utilizing Microsoft office tools for graphical presentations.


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