Combining artificial neural networks and fuzzy analytic network process for holistic sustainable performance evaluation in the Moroccan mining industry

Abstract

This article delves into the evaluation of sustainable performance in the mining industry, employing the Fuzzy Analytic Network Process (FANP) method. It specifically concentrates on examining five pivotal dimensions of sustainable development: economic, social, environmental, operational, and stakeholders. Through the application of the FANP method, a meticulous prioritized ranking is established, not only for these dimensions but also for the specific fields within each of them. This holistic approach provides a comprehensive, well-balanced assessment of sustainable performance, offering a wealth of valuable insights that can guide decision-making processes. Moreover, the method's utility extends beyond the mining sector; it is generalized into a versatile model that can be applied across different industries and research domains. This adaptability is achieved by incorporating a machine learning algorithm, with a primary focus on a multilayer perceptron. This model enables the precise determination of a company's overall multidimensional performance by quantifying various facets of performance, among other considerations. The research presented in this article serves to bridge an existing gap in integrated studies specific to the Moroccan mining industry. It provides actionable insights that can significantly enhance management practices and foster sustainable development, making it a valuable contribution to both the industry and the broader research community.