Accommodating the rainy season in Third World location-allocation applications

While data limitations do not preclude the application of location-allocation (LA) models in the Third World, the socio-spatial circumstances in such locations are sufficiently different to warrant additional caution in applications. For example, the rainy season disrupts transportation and travel for long periods in many countries; yet, typical LA applications fail to consider it. Using the simple p-median and coverage models, this study examines the effect of the rainy season on Third World LA applications. The results indicate that ignoring the rainy season can produce potentially disastrous results, while accommodating it, perhaps by simply editing the data, is likely to produce better results. Moreover, embedded values in these models influence locational outcomes. The results thus call for considerable caution in Third World LA applications.