Societal context-dependent multi-modal transportation network augmentation in Johannesburg, South Africa.

In most developing countries, formal and informal transportation schemes coexist without effective and smart integration. In this paper, the authors show how to leverage opportunities offered by formal and informal transportation schemes to build an integrated multi-modal network. Precisely, the authors consider integration of rickshaws to a bus-train network, by taking into account accessibility and societal constraints. By modelling the respective networks with weighted graphs, a graph augmentation problem is solved with respect to a composite cost taking into account constraints on the use of rickshaws. The solution, is based on finding a minimum cost spanning tree of a merged graph. The method is applied in the South African context, in the city of Johannesburg where rickshaws are not yet a significant part of the transportation system. The implications of the study reveal that using non-motorised transportation services is a viable option of improving mobility in the city. The composite cost introduced herein could be used for new routing algorithm including societal, environmental, architectural contexts and commuter experiences through rating.

Mapping spatial locational trends of informal economic enterprises using mobile geographic information data in the city of in Harare, Zimbabwe.

Spatial planning for informal economic enterprises globally and cities of the developing world such Harare in particular is made difficult by the lack of appropriate data. In most cases, informal economic enterprises are discussed descriptively and statistically, leaving out their spatial characteristics. This makes the orderly planning for the enterprises very difficult if not impossible, especially given that the informal economy dominates the economies of most developing countries. This article presents geographic information data that was collected by means of mobile geographic positioning systems over time. In the absence of any other spatial datasets in the City of Harare, this unique data is handy in revealing spatial locational trends of informal economic enterprises and the preferred locational behaviour of informal economic entrepreneurs in the city.