Principal Component Analysis of Barriers to Smart Mining Technology Adoption in Hard-Rock Mining

The transition toward smart mining technologies (SMTs), spanning automation, artificial intelligence, robotics, the Internet of Things and digital twins, is reshaping safety, productivity and sustainability outcomes across the global extractive sector. Yet, their adoption within South Africa’s hard-rock mining industry remains slow, fragmented and empirically under-theorised. Drawing on diffusion of innovation and socio-technical systems perspectives as interpretive lenses, this exploratory study investigates the barriers to SMT adoption as perceived by mining professionals. A quantitative research design was adopted, using a structured questionnaire administered to 80 mining professionals across South Africa’s Northwest, Gauteng and Limpopo provinces. Data were analysed through a three-stage process comprising reliability and validity testing, descriptive statistics, and principal component analysis (PCA). PCA of the twenty-one barriers identified in the literature extracted four components that jointly explained 62.05% of the total variance. Nineteen barriers met the loading criteria for assignment to these components: Adoption Risk and Workforce Barriers; Organisational and Stakeholder Readiness Barriers; Technological Awareness and Change Barriers; and Institutional and Environmental Sustainability Barriers. The findings suggest that, as perceived by the respondents, barriers to SMT adoption extend beyond technological limitations to include regulatory ambiguity, financial constraints, workforce readiness and weak institutional support. Given the modest, non-probability sample, the component structure is exploratory and preliminary. It requires confirmatory testing in larger, independent samples before it is extended to other capital-intensive, safety-critical and regulation-heavy industries. The study concludes with practical, policy, and theoretical implications for mining firms, technology providers, regulators, and researchers seeking to accelerate safe, sustainable, and intelligent digital transformation.