| Title | Artificial intelligence an enabler for sustainable engineering decision-making in uncertain environment: a review and future propositions |
|---|---|
| ID_Doc | 73554 |
| Authors | Wankhede, VA; Agrawal, R; Kumar, A; Luthra, S; Pamucar, D; Stevic, Z |
| Title | Artificial intelligence an enabler for sustainable engineering decision-making in uncertain environment: a review and future propositions |
| Year | 2024 |
| Published | Journal Of Global Operations And Strategic Sourcing, 17, 2 |
| Abstract | PurposeSustainable development goals (SDGs) are gaining significant importance in the current environment. Many businesses are keen to adopt SDGs to get a competitive edge. There are certain challenges in realigning the present working scenario for sustainable development, which is a primary concern for society. Various firms are adopting sustainable engineering (SE) practices to tackle such issues. Artificial intelligence (AI) is an emerging technology that can help the ineffective adoption of sustainable practices in an uncertain environment. In this regard, there is a need to review the current research practices in the field of SE in AI. The purpose of the present study is to comprehensive review the research trend in the field of SE in AI.Design/methodology/approachThis work presents a review of AI applications in SE for decision-making in an uncertain environment. SCOPUS database was considered for shortlisting the articles. Specific keywords on AI, SE and decision-making were given, and a total of 127 articles were shortlisted after implying inclusion and exclusion criteria.FindingsBibliometric study and network analyses were performed to analyse the current research trends and to see the research collaboration between researchers and countries. Emerging research themes were identified by using structural topic modelling (STM) and were discussed further.Research limitations/implicationsResearch propositions corresponding to each research theme were presented for future research directions. Finally, the implications of the study were discussed.Originality/valueThis work presents a systematic review of articles in the field of AI applications in SE with the help of bibliometric study, network analyses and STM. |
| https://repository.londonmet.ac.uk/7840/3/Artificial%20Intelligence_Manuscript.pdf |
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