Vol. 2009 No. 1 (2009)

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Methodological Assessment of Manufacturing Plant Systems in Senegal Using Quasi-Experimental Design for Risk Reduction Evaluation

Mariama Ndiaye, Department of Research, Institut Sénégalais de Recherches Agricoles (ISRA) Mamadou Touré, Department of Interdisciplinary Studies, Cheikh Anta Diop University (UCAD), Dakar Issa Sall, Department of Advanced Studies, Institut Sénégalais de Recherches Agricoles (ISRA)
DOI: 10.5281/zenodo.18890571
Published: June 25, 2009

Abstract

The review focuses on methodological assessments of manufacturing plant systems in Senegal. Quasi-experimental approaches were applied to analyse data from existing studies and case studies of manufacturing plants in Senegal. Statistical models including logistic regression were utilised to assess the effectiveness of implemented risk reduction strategies. A notable finding was a significant decrease (34%) in operational disruptions attributed to improved maintenance protocols, supported by robust standard errors. This review underscores the efficacy of quasi-experimental designs for evaluating manufacturing plant systems and identifies specific strategies for risk mitigation. Manufacturing plants should implement comprehensive maintenance programmes and conduct regular safety audits as key components of their risk reduction strategy. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.

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How to Cite

Mariama Ndiaye, Mamadou Touré, Issa Sall (2009). Methodological Assessment of Manufacturing Plant Systems in Senegal Using Quasi-Experimental Design for Risk Reduction Evaluation. African Cartography and Geovisualization (Earth Science Methodology), Vol. 2009 No. 1 (2009). https://doi.org/10.5281/zenodo.18890571

Keywords

African GeographyQuasi-Experimental DesignMethodological EvaluationManufacturing SystemsRisk ManagementStatistical AnalysisTheory of Change

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Vol. 2009 No. 1 (2009)
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African Cartography and Geovisualization (Earth Science Methodology)

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