| Title |
Big Data-Enabled Solutions Framework to Overcoming the Barriers to Circular Economy Initiatives in Healthcare Sector |
| ID_Doc |
4482 |
| Authors |
Kazançoglu, Y; Sagnak, M; Lafci, Ç; Luthra, S; Kumar, A; Taçoglu, C |
| Title |
Big Data-Enabled Solutions Framework to Overcoming the Barriers to Circular Economy Initiatives in Healthcare Sector |
| Year |
2021 |
| Published |
International Journal Of Environmental Research And Public Health, 18, 14 |
| DOI |
10.3390/ijerph18147513 |
| Abstract |
Ever-changing conditions and emerging new challenges affect the ability of the healthcare sector to survive with the current system, and to maintain its processes effectively. In the healthcare sector, the conservation of the natural resources is being obstructed by insufficient infrastructure for managing residual waste resulting from single-use medical materials, increased energy use, and its environmental burden. In this context, circularity and sustainability concepts have become essential in healthcare to meliorate the sector's negative impacts on the environment. The main aim of this study is to identify the barriers related to circular economy (CE) in the healthcare sector, apply big data analytics in healthcare, and provide solutions to these barriers. The contribution of this research is the detailed examination of the current healthcare literature about CE adaptation, and a proposal for a big data-enabled solutions framework to barriers to circularity, using fuzzy best-worst Method (BWM) and fuzzy VIKOR. Based on the findings, managerial, policy, and theoretical implementations are recommended to support sustainable development initiatives in the healthcare sector. |
| Author Keywords |
circular economy; sustainable development; healthcare sector; big data tools; barriers; fuzzy best-worst; fuzzy VIKOR; waste issues |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000676753200001 |
| WoS Category |
Environmental Sciences; Public, Environmental & Occupational Health |
| Research Area |
Environmental Sciences & Ecology; Public, Environmental & Occupational Health |
| PDF |
https://www.mdpi.com/1660-4601/18/14/7513/pdf?version=1626766717
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