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Artificial intelligence an enabler for sustainable engineering decision-making in uncertain environment: a review and future propositions

斯科普斯 有可能 独创性 管理科学 领域(数学) 包裹体(矿物) 计算机科学 知识管理 价值(数学) 工作(物理) 可持续发展 工程伦理学 社会学 政治学 工程类 社会科学 定性研究 心理学 纯数学 法学 心理治疗师 机器学习 机械工程 数学 梅德林
作者
Vishal Ashok Wankhede,Rohit Agrawal,Anil Kumar,Sunil Luthra,Dragan Pamučar,Željko Stević
出处
期刊:Journal of global operations and strategic sourcing [Emerald Publishing Limited]
卷期号:17 (2): 384-401 被引量:14
标识
DOI:10.1108/jgoss-06-2022-0057
摘要

Purpose Sustainable 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/approach This 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. Findings Bibliometric 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/implications Research propositions corresponding to each research theme were presented for future research directions. Finally, the implications of the study were discussed. Originality/value This 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.
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