An indicator-based framework for sustainable mining using fuzzy AHP

The mineral extraction industry is vital for nations’ economic growth, as it provides raw materials for various industries. Implementing sustainable mining practices in this sector can contribute to its long-term growth and stability. However, Pakistan lacks a well-defined sustainability assessment framework for mining, leaving a critical gap in research and practice. Existing internationally developed frameworks are not directly applicable, as they were designed for contexts where the mining industry predominantly uses mechanized operations. In contrast, Pakistan’s extraction process relies heavily on manual methods, making it necessary to develop a context-specific framework. A fuzzy analytical hierarchy process (AHP) was employed to prioritize these indicators and sub-indicators for the sustainability assessment of Pakistan’s mineral industry. The findings of this study highlight that the environmental dimension ranks as the highest priority, followed by social and economic dimensions. Among the environmental indicators, pollution and smart technologies each received a weight of 0.40, which was also the case for the social indicator of discrimination and nepotism, as well as the economic indicators of GDP growth and wealth creation. Furthermore, the results suggest that the extensive use of smart technologies for pollution control is a key factor in fostering environmental sustainability.