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

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.

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Publication Details

Journal
Scientific African
Published
2025-03-22
DOI
https://doi.org/10.1016/j.sciaf.2025.e02662
Primary Topic
African studies and sociopolitical issues
Type
article
Field-Weighted Citation Impact
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article

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

Meshach Ndlovu
Scientific African
African studies and sociopolitical issues
article

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

Meshach Ndlovu
article en

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.

Scientific AfricanVol. 28
Gwanda State University (ZW)
Openalex Percentile: Top 93%
African studies and sociopolitical issues
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