Clustering and spatial dynamics of informal trading in Zimbabwe during the COVID-19 pandemic

Abstract

The COVID-19 pandemic led to significant disruptions across various sectors, with Zimbabwe's informal economy being acutely impacted. In response, the Zimbabwean government implemented measures to mitigate the economic challenges faced by informal traders, including the establishment of new trading spaces such as Nkulumane Sekusile in Bulawayo. This study investigates the spatial dynamics, understood as the clustering and grouping of different types of traders within Sekusile market during the pandemic. The research examines how the influx of traders from various regions altered the market's structure and competition. By employing advanced statistical clustering methods—such as hotspot analysis, the K-means algorithm, ordinary kriging, and persistence diagrams—this study provides critical insights into these spatial variations, informing policy recommendations aimed at enhancing the socio-economic resilience of informal traders.