A geospatial–fuzzy AHP decision-support framework for strategic marketplace planning in Dodoma, Tanzania

Abstract

Inequitable access to marketplaces in rapidly urbanizing cities often results from poorly coordinated spatial planning, leading to service congestion in core areas and critical undersupply in expanding peri-urban neighborhoods. In Dodoma City, Tanzania, the absence of integrated spatial decision-support tools constrains the evidence-based allocation of new marketplace facilities. This study develops and applies a geospatial decision-making framework to identify optimal locations for prospective marketplaces using Geographic Information Systems (GIS) integrated with the Fuzzy Analytic Hierarchy Process (F-AHP). Seven spatial criteria, namely population density, road network connectivity, land use/land cover (LULC), proximity to built-up areas, slope, elevation, and geomorphology, were standardized, weighted via F-AHP, and combined through weighted overlay analysis to generate a Potential Market Areas Map (PMAM). The F-AHP weighting revealed a clear hierarchy, with population density (0.388) and road connectivity (0.261) emerging as the most influential determinants. Validation against 36 existing market locations yielded an excellent Area Under the Curve (AUC) value of 0.968, confirming strong spatial discrimination. Crucially, the framework advances beyond theoretical suitability mapping by integrating the PMAM with administrative ward boundaries and land-use/land cover maps, identifying specific high-priority location clusters in underserved wards such as Mbalawala, Mpunguzi and Ipala. The study provides urban planners and policymakers with a transparent, reproducible decision-support tool for evidence-based site selection that promotes spatial equity, reduces travel burdens, and supports sustainable urban development in Dodoma and comparable rapidly growing African cities.