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Big Data-Enabled Solutions Framework to Overcoming the Barriers to Circular Economy Initiatives in Healthcare Sector

机译:支持大数据的解决方案框架以克服医疗保健部门循环经济倡议的障碍

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摘要

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.
机译:不断变化的条件和新兴的新挑战会影响医疗保健部门与现有系统生存的能力,并有效地保持其流程。在医疗保健部门,保护自然资源的基础设施不足,用于管理单用医疗材料增加,能源使用增加,以及环境负担。在这种情况下,循环和可持续性概念在医疗保健方面变得必不可少,以使该部门对环境的负面影响。本研究的主要目的是确定医疗部门的循环经济(CE)的障碍,在医疗保健中应用大数据分析,并为这些障碍提供解决方案。该研究的贡献是对CE适应当前医疗文学的详细审查,以及利用模糊最坏情况(BWM)和模糊Vikor的循环性障碍的大数据解决方案框架的提案。根据调查结果,建议管理,政策和理论实施,以支持医疗保健部门的可持续发展举措。

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