Vol. 2006 No. 1 (2006)

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Bayesian Hierarchical Model for Risk Reduction in South African Manufacturing Plants Systems,

Molosiwa Khumalo, Department of Research, University of the Witwatersrand Sifiso Thabo Mandela, Council for Scientific and Industrial Research (CSIR) Lethaletwe Sekhoane, Department of Advanced Studies, Vaal University of Technology (VUT) Zapiro Makhanya, Department of Interdisciplinary Studies, University of the Witwatersrand
DOI: 10.5281/zenodo.18827974
Published: August 1, 2006

Abstract

This study evaluates the risk reduction strategies in South African manufacturing plants, focusing on energy systems. The analysis employs a Bayesian hierarchical model to analyse data from South African manufacturing plants over the period -, focusing on energy systems. A significant proportion (75%) of identified risks were mitigated through targeted interventions using the Bayesian hierarchical model. The results underscore the efficacy of Bayesian hierarchical models in risk management within South African manufacturing environments, particularly for energy systems. Manufacturing plants are encouraged to adopt and refine their use of Bayesian hierarchical models for improved risk reduction strategies. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.

How to Cite

Molosiwa Khumalo, Sifiso Thabo Mandela, Lethaletwe Sekhoane, Zapiro Makhanya (2006). Bayesian Hierarchical Model for Risk Reduction in South African Manufacturing Plants Systems,. African Climate Change Impacts & Adaptation (Interdisciplinary - incl, Vol. 2006 No. 1 (2006). https://doi.org/10.5281/zenodo.18827974

Keywords

Sub-Saharanhierarchical modellingBayesian statisticsrisk assessmentmanufacturing systemsenergy efficiencydata analysis

References