| dc.description.abstract | As mobile banking industry is a relative newcomer in using GIS in the developing nations,
applications on the area is yet to be fully realized. This is partly due to the unavailability of
spatial datasets. GIS technology provides the ability to measure proximity and location.
However, use of spatial datasets from different sources, even if the datasets exhibit mismatch
in scales may still go a long way in helping understand suitability analysis for the purpose of
guiding broad policies in mobile banking industries in developing countries.
The overall objective of this study was to demonstrate how GIS can be used in the selection
and determination of new M-Pesa outlets. More importantly it investigates how the spatial
element of GIS can allow location to be modeled based on different weighted variables. The
results are of crucial value in strategic policy making in the mobile banking industry. Roads
data was digitized from Nairobi Toposheet. Data was also collected from the ground using
handheld GPS. Reclassification, buffering and overlaying was done in order to combine all
the identified variables within ArcGIS environment.
The study showed that the most suitable areas (hotspots) for new locations were those which had
a relatively high number of people, infra structural facilities as well as good level of
security.These results were a clear correlation of the weighting done and importance of each
element in the area. In conclusion, several proposed guidelines have been suggested for
incorporation in future M-Pesa recruitment processes.
Keywords: Mobile Banking, M-Pesa, GIS, Hotspots | en |
