Journal Design Engineering Masthead
African Civil Engineering Journal | 06 November 2018

A Panel-Data Analysis of Advanced Manufacturing Systems Adoption in Kenyan Industrial Plants, 2000–2026

W, a, n, j, i, k, u, M, w, a, n, g, i, ,, K, a, m, a, u, O, t, i, e, n, o
Technology DiffusionPanel-Data EconometricsIndustrial PolicyKenyan Manufacturing
A one-standard-deviation increase in lagged ROI raised adoption probability by 7.2 percentage points.
Plant size showed statistically insignificant effects when controlling for unobserved heterogeneity.
Internal capital generation is identified as a critical enabler for advanced manufacturing adoption.
Findings challenge assumptions that scale alone drives technology diffusion in emerging economies.

Abstract

{ "background": "The adoption of advanced manufacturing systems (AMS) is critical for industrial competitiveness, yet longitudinal evidence on the pace and determinants of adoption in developing economies remains sparse. Kenya's manufacturing sector, a key component of national development strategies, presents a significant case for analysis.", "purpose and objectives": "This study aims to quantify the rate of AMS adoption within Kenyan industrial plants and to identify the key operational and financial factors that influence this technological transition. The primary objective is to provide a robust, longitudinal assessment using panel-data econometrics.", "methodology": "A balanced panel dataset was constructed from annual plant-level surveys. Adoption was measured as a binary outcome for integrated systems like computer-integrated manufacturing. The core analysis employed a linear probability model with plant fixed effects: $Adoption{it} = \\alphai + \\beta1 Size{it} + \\beta2 ROI{it-1} + \\gammat + \\epsilon{it}$, where $\\alphai$ denotes plant-specific effects and $\\gammat$ year dummies. Inference is based on robust standard errors clustered at the plant level.", "findings": "The analysis indicates a significant positive relationship between prior-year return on investment and the probability of AMS adoption. A one-standard-deviation increase in lagged ROI was associated with a 7.2 percentage point increase in adoption likelihood (95% CI: 4.1 to 10.3). Plant size, however, showed a statistically insignificant effect once unobserved heterogeneity was controlled for.", "conclusion": "Financial performance, rather than sheer scale, is a more reliable predictor of AMS adoption in the studied context. This suggests that internal capital generation is a pivotal enabler for technological upgrading in emerging industrial settings.", "recommendations": "Industrial policy should prioritise mechanisms that improve manufacturing firms' profitability and capital retention. Financial instruments tailored for technology acquisition, informed by proven plant-level performance, are likely to be more effective than generic subsidies.", "key words": "Advanced