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The impact of loadshedding on remote work productivity : a data-driven analysis of online engagement patterns
Thesis   Open access

The impact of loadshedding on remote work productivity : a data-driven analysis of online engagement patterns

Claire Muriel Sandra Niombella-Mawokola
Master of Applied Data Science, University of Johannesburg
2025
Handle:
https://hdl.handle.net/10210/521335

Abstract

Situated within the domain of remote work and organisational productivity, this study examines the impact of loadshedding on remote work productivity and online engagement among employees in South Africa. As power disruptions have become a frequent feature of the working environment, their effects on remote work outcomes remain underexplored in both theory and practice. The purpose of this research is to investigate how consistent energy instability, organisational support, flexibility and resources preparedness influence productivity and online engagement in a remote work environment. Shaped by Job Theory (Jobs-to-be-Done), a quantitative survey approach was adopted, targeting remote workers across different sectors, and generating 150 valid responses. Data were analysed using Python (Jupyter Notebook) through a combination of descriptive and inferential statistical techniques. Descriptive statistics provided insight into the frequency and duration of loadshedding events, access to backup resources, and self-reported measures of productivity and engagement. Reliability of the composite indices was assessed using Cronbach’s alpha, while correlation analysis and multiple regression models were applied to evaluate the relationships between loadshedding, resource availability, flexibility, and remote work outcomes. The findings revealed that loadshedding significantly disrupts both productivity and online engagement, with engagement being more vulnerable than task completion. Resource preparedness, particularly access to backup internet and power, was found to mitigate productivity losses, while employer-supported flexibility was more effective than reactive time-based adjustments. The results further suggest that proactive adaptation strategies sustain both productivity and engagement, whereas reactive strategies primarily protect task completion at the expense of collaboration. The study extends Job Theory to contexts characterised by limited infrastructure by distinguishing between core (productivity) and relational (online engagement) work functions and by framing resources preparedness as a critical connecting factor. In conclusion, maintaining effective remote work under energy instability calls for more than individual coping mechanisms; it requires coordinated organisational support and enabling policy frameworks. Future research is encouraged to examine longitudinal effects of energy instability and to explore technology-driven interventions that enhance remote work resilience in infrastructure-constrained environments.
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