Multilevel Regression Analysis to Evaluate Adoption Rates of Process-Control Systems in Ghana's Manufacturing Enterprises

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1. Verfasser: Storey, Gavin
Format: Recurso digital
Sprache:Englisch
Veröffentlicht: Zenodo 2014
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author Storey, Gavin
author_facet Storey, Gavin
contents <p>Process-control systems (PCSs) are critical for enhancing manufacturing efficiency in Ghana's enterprises. However, their adoption rates vary significantly across different sectors and companies. A multilevel logistic regression model was employed to analyse data from a sample of 150 manufacturing enterprises across various sectors. Data collection involved questionnaires and interviews, supplemented by secondary sources for contextual information. The analysis revealed that the proportion of companies adopting PCSs in the food processing sector is significantly higher than in other sectors (72% vs. 38%, p < 0.05). Multilevel regression models provide a robust framework for understanding complex adoption dynamics and can inform policy decisions aimed at increasing PCS utilization. Implementing targeted interventions, such as financial incentives or technical support programmes, is recommended to promote PCS adoption in sectors with lower rates of implementation. Process-Control Systems, Multilevel Regression Analysis, Manufacturing Enterprises, Ghana The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_19067288
institution Zenodo
language eng
publishDate 2014
publisher Zenodo
record_format zenodo
spellingShingle Multilevel Regression Analysis to Evaluate Adoption Rates of Process-Control Systems in Ghana's Manufacturing Enterprises
Storey, Gavin
Ghanaian
Multilevel
Regression
Hierarchical
Adoption
Evaluation
Manufacturing
<p>Process-control systems (PCSs) are critical for enhancing manufacturing efficiency in Ghana's enterprises. However, their adoption rates vary significantly across different sectors and companies. A multilevel logistic regression model was employed to analyse data from a sample of 150 manufacturing enterprises across various sectors. Data collection involved questionnaires and interviews, supplemented by secondary sources for contextual information. The analysis revealed that the proportion of companies adopting PCSs in the food processing sector is significantly higher than in other sectors (72% vs. 38%, p < 0.05). Multilevel regression models provide a robust framework for understanding complex adoption dynamics and can inform policy decisions aimed at increasing PCS utilization. Implementing targeted interventions, such as financial incentives or technical support programmes, is recommended to promote PCS adoption in sectors with lower rates of implementation. Process-Control Systems, Multilevel Regression Analysis, Manufacturing Enterprises, Ghana The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.</p>
title Multilevel Regression Analysis to Evaluate Adoption Rates of Process-Control Systems in Ghana's Manufacturing Enterprises
topic Ghanaian
Multilevel
Regression
Hierarchical
Adoption
Evaluation
Manufacturing
url https://doi.org/10.5281/zenodo.19067288