Crabbe, Mackenzie2023-10-052023-10-052023-10-052023-09-21http://hdl.handle.net/10012/20026The mining sector is currently experiencing a period of disruption where technological innovations such as electric vehicles, artificial intelligence, and drones are transforming how the industry operates. Little is known, however, about the factors that drive, enable, and impede technology adoption in the mining sector, particularly in the context of Canada. To address this gap, this research explores the drivers, enablers, and barriers to technology adoption in Canada's mineral mining sector through an online survey, structured by the technology-organization-environment (TOE) framework, with insights from similar research in the context of Australia. The findings of this research suggest that the top three technologies being adopted by mining companies in Canada are battery electric vehicles (BEV's), sensors, and autonomous equipment. In the Canadian context, the technology adoption process for mining companies is influenced by a complex interplay of factors determined by the three commonly cited dimensions of sustainability (economic, social, environmental). While economic considerations, such as productivity and efficiency, to reduce operating costs and competitive pressures underpin technology adoption decisions, mining companies are also motivated to adopt technologies by social factors such as improvements to health and safety for workers, and environmental factors such as to reduce diesel emissions. Economic factors, such as costs of the technology, implementation costs, limited internal capital, and the capital intensive nature of the sector, underpin the barriers to technology adoption for mining companies with operations in Canada. This research concludes with suggestions for future research, and key theoretical contributions.entechnology adoptionmining sectordriversenablersbarriersorganizationssustainabilityExploring Technology Adoption in Canada’s Mineral Mining Sector: Navigating Through an Interplay of FactorsMaster Thesis