A comprehensive model for socially responsible rehabilitation of mining sites using Q-rung orthopair fuzzy sets and combinative distance-based assessment
File(s)Manuscript_R1.docx (926.03 KB)
Accepted version
Author(s)
Deveci, Muhammet
Gokasar, Ilgin
Brito-Parada, Pablo R
Type
Journal Article
Abstract
Mining companies play a critical role in developing mineral wealth across the globe. Interacting effectively with local communities is yet another potential source of long-term profitability, because of the opportunities that are not accessible if community engagement is not achieved. The financial advantages of a positive company image can be linked to attracting and retaining employees, as well as sustaining or even enhancing the capacity to do business with local suppliers. The socially responsible rehabilitation of a site after mine closure can facilitate access to new or former jobs for the mine workers. This study focuses on how to identify the best rehabilitation strategy after the closure of a mining site. In particular, a q-rung orthopair fuzzy sets (q-ROFSs) based CODAS (COmbinative Distance-based ASsessment) model is developed to support the evaluation of socially responsible rehabilitation activities in mining sites. To test and validate the model, the proposed methodology is compared to the ARAS (Additive Ratio Assessment) method. The results show that rehabilitation and social transition subsidy is the best alternative among those considered. Implementation of this alternative benefits the mining companies and also brings social benefits to the mine workers and the wider communities within the mining site.
Date Issued
2022-08
Date Acceptance
2022-03-30
Citation
Expert Systems with Applications, 2022, 200, pp.117155-117155
ISSN
0957-4174
Publisher
Elsevier BV
Start Page
117155
End Page
117155
Journal / Book Title
Expert Systems with Applications
Volume
200
Copyright Statement
© 2022 Elsevier Ltd. All rights reserved
Identifier
https://www.sciencedirect.com/science/article/pii/S0957417422005474?via%3Dihub
Subjects
01 Mathematical Sciences
08 Information and Computing Sciences
09 Engineering
Artificial Intelligence & Image Processing
Publication Status
Published online
Article Number
117155
Date Publish Online
2022-04-02