OICC Press International Journal of Mathematical Modelling & Computations 2228-6233 16 3 2026 09 30 Assessing Digitalization Progress and Adaptation in the Mining Industry Using Uncertain DEA 207 216 10.57647/ijm2c.2026.1603.16 EN Jafar Pourmahmoud Department of Applied Mathematics, Azarbaijan Shahid Madani University, Tabriz, Iran Ali Omidi Department of Applied Mathematics, Azarbaijan Shahid Madani University, Tabriz, Iran Mahdi Eyni Department of Mathematics, Payame Noor University, Tehran, Iran Journal Article 2026 09 30 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.