10.57647/ijm2c.2026.1603.16

Assessing Digitalization Progress and Adaptation in the Mining Industry Using Uncertain DEA

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  • Jafar Pourmahmoud*1,
  • Ali Omidi1,
  • Mahdi Eyni2,
  1. Department of Applied Mathematics, Azarbaijan Shahid Madani University, Tabriz, Iran
  2. Department of Mathematics, Payame Noor University, Tehran, Iran

Received: 25-07-2025

Revised: 30-11-2025

Accepted: 11-12-2025

Published in Issue 30-09-2026

Published Online: 26-12-2025

Copyright (c) 2025 Jafar Pourmahmoud, Ali Omidi, Mahdi Eyni (Author)

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Pourmahmoud, J., Omidi, A., & Eyni, M. (2026). Assessing Digitalization Progress and Adaptation in the Mining Industry Using Uncertain DEA. International Journal of Mathematical Modelling & Computations, 16(3), 207-216. https://doi.org/10.57647/ijm2c.2026.1603.16
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Abstract

The mining industry is undergoing a profound transformation, marked by the widespread adoption of new technologies and evolving operational practices. While historically resistant to change, mining companies have increasingly recognized the imperative of embracing digitalization initiatives. Despite these efforts, the industry lags behind in fully harnessing the potential of Industry 4.0 principles, which hinge on extensive digital innovation and automation. This study endeavors to evaluate the efficacy of mining companies' digitalization efforts, focusing on the extent of their integration of new technologies into operational processes. Using Uncertain Data Envelopment Analysis (DEA) modeling, we present a comprehensive framework that considers both deterministic and stochastic variables in assessing company performance. Our analysis reveals a notable uptick in digitalization efforts among mining enterprises in recent years; however, the findings underscore a persistent gap between current practices and the anticipated level of adaptation. This research contributes to the discourse on digital transformation within the mining sector, highlighting areas for improvement and guiding strategic decision-making towards achieving greater efficiency and competitiveness.

Keywords

  • Efficiency,
  • Mining Industry,
  • Uncertainty,
  • Data Envelopment Analysis
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