African Technology and Development (Interdisciplinary -

Advancing Scholarship Across the Continent

Vol. 2005 No. 1 (2005)

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Methodological Assessment of Process-Control Systems in Nigerian Industries: An Efficiency Gain Analysis Using Panel Data Techniques

Saleh Musa, Department of Electrical Engineering, Nnamdi Azikiwe University, Awka Usman Lawal, Nigerian Institute of Social and Economic Research (NISER)
DOI: 10.5281/zenodo.18821531
Published: August 16, 2005

Abstract

Process-control systems (PCS) are critical for enhancing efficiency in industrial settings, yet their application and impact vary across different sectors. Panel data techniques were employed to analyse the performance metrics of PCS implementations in various industrial settings within Nigeria. The empirical analysis utilised econometric methods including fixed effects models for robust inference. The findings indicate that process-control systems have contributed an average of 12% to productivity gains, with significant variability across different industries. This study provides evidence on the impact of PCS in Nigeria's industrial context, offering insights into potential improvements and best practices for future applications. Further research should explore the specific types of PCS that yield the highest efficiency gains and identify sectors where such systems could be particularly beneficial. Process-Control Systems, Efficiency Gains, Panel Data Techniques, Nigerian Industries The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.

How to Cite

Saleh Musa, Usman Lawal (2005). Methodological Assessment of Process-Control Systems in Nigerian Industries: An Efficiency Gain Analysis Using Panel Data Techniques. African Technology and Development (Interdisciplinary -, Vol. 2005 No. 1 (2005). https://doi.org/10.5281/zenodo.18821531

Keywords

Nigerian industriesProcess-control systemsPanel dataEconometricsEfficiency measurementTime-series analysisCross-section analysis

References