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

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.

Authors

Institutions

Publication Details

Journal
OICC Press Journals
Published
2025-07-25
DOI
https://doi.org/10.57647/ijm2c.2026.1603.16
Primary Topic
Mining Techniques and Economics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Mahdi Eyni, Ali Omidi, Jafar Pourmahmoud
OICC Press Journals
Mining Techniques and Economics
article

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

Mahdi Eyni, Ali Omidi, Jafar Pourmahmoud
article en

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.

OICC Press Journals
Azarbaijan Shahid Madani University (IR), Payame Noor University (IR)
Industry, innovation and infrastructure
Openalex Percentile: Top 37%
Mining Techniques and Economics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Assessing Digitalization Progress and Adaptation in the Mining Industry Using Uncertain DEA — Mahdi Eyni, Ali Omidi, et al. · OICC Press Journals (2025) | TGRS Research Map | TGRS