African Management Information Systems (Business/ICT crossover) | 28 January 2001
Methodological Evaluation of Manufacturing Plants Systems in Kenya Using Time-Series Forecasting Models
K, i, s, i, m, i, w, a, O, l, e, c, h, e, ,, M, u, t, u, a, K, i, p, r, o, p, ,, O, n, d, i, e, p, i, O, g, w, a, b, i, y, a
Abstract
Manufacturing plants in Kenya have adopted various information systems (IS) to improve operational efficiency and productivity. A comprehensive review of existing literature on IS adoption metrics, focusing on time-series analysis techniques applied to real-world data from Kenya's manufacturing sector. The review identified a significant trend (p < 0.05) in the adoption rates of predictive maintenance systems over five years, with an estimated mean increase of 12% annually. Time-series models are effective for measuring IS adoption rates in Kenyan manufacturing plants, providing robust insights into system usage patterns and facilitating informed decision-making. Manufacturing companies should consider adopting time-series forecasting models to enhance their understanding of IS adoption trends and optimise resource allocation. Manufacturing systems, Kenya, Time-series forecasting, Adoption rates, IS metrics Model estimation used $\hat{\theta}=argmin<em>{\theta}\sum</em>i\ell(y<em>i,f</em>\theta(x<em>i))+\lambda\lVert\theta\rVert</em>2^2$, with performance evaluated using out-of-sample error.