Exploring disruptive innovation, economic incentives, and e-waste management within South Africa's private security industry: A focus on Gauteng

Abstract

Very few studies have been done on electronic waste in the private security industry around the world and in South Africa. This study was groundbreaking in this area of research. This study explored disruptive innovation, economic incentives, and e-waste management within South Africa's private security industry. Twelve executives from private security companies in Gauteng Province took part in the study, which employed an exploratory qualitative mono-method approach to examine current practices and perceptions related to e-waste management among private security companies. The Incentive theory was used to understand the role of economic incentives in promoting sustainable e-waste management amongst private security companies within the private security industry. Five themes emerged from the data obtained from the participants using semi-structured interviews: awareness and adoption of sustainable e-waste management, economic incentives for e-waste management in the private security industry, barriers to sustainable e-waste management in the private security industry, leveraging theoretical frameworks for structured e-waste management model and lastly challenges and opportunities for disruptive innovation in e-waste management. The findings reveal a significant gap in awareness and implementation of sustainable e-waste management practices, attributed primarily to limited understanding of existing regulations and economic incentives. Recommendations include enhancing educational initiatives to raise awareness and optimising incentive structures to promote sustainable practices within the industry. Future research should focus on longitudinal studies assessing the long-term impacts of economic incentives on e-waste management behaviours and the role of disruptive technologies in facilitating sustainable practices. This study's limitations include a limited sample size and potential biases in self-reported data, which suggest caution in generalising the findings across the broader industry.