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Big Data-Enabled Solutions Framework to Overcoming the Barriers to Circular Economy Initiatives in Healthcare Sector.
Kazançoglu, Yigit; Sagnak, Muhittin; Lafci, Çisem; Luthra, Sunil; Kumar, Anil; Taçoglu, Caner.
  • Kazançoglu Y; Department of International Logistics Management, Faculty of Business, Yasar University, Izmir 35100, Turkey.
  • Sagnak M; Department of Information Management, Izmir Katip Celebi University, Izmir 35620, Turkey.
  • Lafci Ç; Department of International Logistics Management, Faculty of Business, Yasar University, Izmir 35100, Turkey.
  • Luthra S; Department of Mechanical Engineering, Ch. Ranbir Singh State Institute of Engineering and Technology, Jhajjar-124103, India.
  • Kumar A; Guildhall School of Business and Law, London Metropolitan University, London N7 8DB, UK.
  • Taçoglu C; Department of Industrial Engineering, Faculty of Engineering, Izmir University of Economics, Izmir 35330, Turkey.
Int J Environ Res Public Health ; 18(14)2021 07 14.
Article in English | MEDLINE | ID: covidwho-1323237
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Health Care Sector / Big Data Type of study: Prognostic study Limits: Humans Language: English Year: 2021 Document Type: Article Affiliation country: Ijerph18147513

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Health Care Sector / Big Data Type of study: Prognostic study Limits: Humans Language: English Year: 2021 Document Type: Article Affiliation country: Ijerph18147513