| Title |
Evaluating Industry 4.0 technology and sustainable development goals - a social perspective |
| ID_Doc |
18073 |
| Authors |
Bai, CG; Zhou, H; Sarkis, J |
| Title |
Evaluating Industry 4.0 technology and sustainable development goals - a social perspective |
| Year |
2023 |
| Published |
International Journal Of Production Research, 61, 23 |
| DOI |
10.1080/00207543.2022.2164375 |
| Abstract |
Organisations are having difficulty in determining and integrating Industry 4.0 technologies (I4.0T) to improve social dimensions of sustainable performance. We address this issue by showing how to identify the impact degree and path of I4.0T using the United Nations sustainable development goals (SDGs). First, we identify the SDGs associated with I4.0 and establish an evaluation framework. Second, we introduce an evaluation method that integrates hesitant fuzzy sets, rough sets, decision-making, trial evaluation laboratory (DEMATEL) and interpretative structural modelling methods to identify the impact degree and path of I4.0T on SDGs. Third, we confirm the effectiveness of our framework and method using secondary case data from World Economic Forum reports. The case results show that I4.0T have varying direct and indirect influences on SDGs. Policy makers should consider that 'Big Data and Analytics' and 'Cloud Computing' are central I4.0T that link other technologies and SDGs. The prioritisation of I4.0T can lead to contributions to addressing 'Responsible consumption and production' and indirectly improve SDGs. The findings set an initial stage to help sequence investment in various technologies depending on SDGs. We identify sequential paths that can aid in planning for and investing in adopting I4.0T to better achieve SDGs. |
| Author Keywords |
Industry 4; 0; sustainable development goals; hesitant fuzzy sets; DEMATEL; technology adoption |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000913840100001 |
| WoS Category |
Engineering, Industrial; Engineering, Manufacturing; Operations Research & Management Science |
| Research Area |
Engineering; Operations Research & Management Science |
| PDF |
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