Naidoo, Shalin2025-02-262024Naidoo, Shalin. (2024). The Adoption of Big Data Analytics in the South African Mining Industry[Master’s dissertation, University of the Witwatersrand, Johannesburg].WireDSpace.https://hdl.handle.net/10539/43973A research report submitted in partial fulfilment of the requirements for the degree of Master of Management in the field of Digital Business to the Faculty of Commerce, Law, and Management, Wits Business School, University of the Witwatersrand, Johannesburg, 2024This study investigated big data analytics adoption in South Africa's mining industry, focusing on technological, organisational, and human factors using the Technology Acceptance Model 3(TAM3). Data from various industry professionals was gathered and analysed quantitatively, revealing strong links between factors like computer self-efficacy, management support, and peer influence in technology adoption. The key findings indicate strong relationships between computer self-efficacy, management support, and peer influence on technology adoption. This emphasises the crucial importance of organisational support and infrastructure.. The study highlights a multidimensional approach, integrating technology with human and organisational elements, offering insights and practical recommendations for industry adoption of big data analytics.en© 2024 University of the Witwatersrand, Johannesburg. All rights reserved. The copyright in this work vests in the University of the Witwatersrand, Johannesburg. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of University of the Witwatersrand, Johannesburg.Technology Adoption in MiningDigital Transformation in MiningBig Data AnalyticsSouth African Mining IndustryData-Driven Decision Making in MiningUCTDSDG-7: Affordable and clean energyDissertationUniversity of the Witwatersrand, Johannesburg