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Dinçer H, Yüksel S, Eti S, Gökalp Y, Mikhaylov A, Karpyn Z. Effective waste management in service industry: Fuzzy-based modelling approach for strategic decision-making. WASTE MANAGEMENT & RESEARCH : THE JOURNAL OF THE INTERNATIONAL SOLID WASTES AND PUBLIC CLEANSING ASSOCIATION, ISWA 2025; 43:438-451. [PMID: 38581268 PMCID: PMC11874516 DOI: 10.1177/0734242x241242682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Accepted: 03/13/2024] [Indexed: 04/08/2024]
Abstract
Hospitals need to identify issues of greater importance on waste management because the implementation of many different strategies may lead to an unconscious increase in costs. Accordingly, the purpose of this study is to define the most effective waste management strategies in the service industry. For this purpose, a novel fuzzy decision-making model is proposed that has two different stages. In this context, six JCI-based indicators are weighted by using sine trigonometric fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) methodology. Additionally, a comparative evaluation has also been conducted with sine trigonometric fuzzy Criteria Importance Through Intercriteria Correlation (CRITIC) technique to check the reliability of the findings. On the other hand, five different strategy alternatives are selected by considering the principles of the integrated waste management hierarchy approach. These items are evaluated by considering sine trigonometric fuzzy Technique for Order Preference by Similarity (TOPSIS). On the other side, these factors are also ranked with the help of sine trigonometric fuzzy Additive Ratio Assessment (ARAS) to test the consistency of the results. The main contribution is that prior strategies can be presented to the hospitals to have appropriate waste management process by defining the most important factors. Criteria weighting and alternative ranking results are the same in all combinations. Therefore, it is seen that the proposed model creates coherent and consistent results. It is defined that efficient storage of waste is the key issue to have effective waste management process. Moreover, 'reduce' is found as the most critical stage of this process.
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Affiliation(s)
- Hasan Dinçer
- The School of Business, İstanbul Medipol University, İstanbul, Turkey
| | - Serhat Yüksel
- The School of Business, İstanbul Medipol University, İstanbul, Turkey
- Adnan Kassar School of Business, Lebanese American University, Beirut, Lebanon
| | - Serkan Eti
- IMU Vocational School, İstanbul Medipol University, İstanbul, Turkey
| | - Yaşar Gökalp
- The School of Health Science, İstanbul Medipol University, İstanbul, Turkey
| | - Alexey Mikhaylov
- Financial University under the Government of the Russian Federation, Russia
| | - Zuleima Karpyn
- Pennsylvania State University – Allentown Campus, Center Valley, USA
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Huang X, Zhuang Z, Liu J, Shi W, Xu X, Wang L, Li Q, Wang H. Research on the impact mechanism of changes in the production of medical solid waste in China before and after COVID-19. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:37717-37731. [PMID: 38789708 DOI: 10.1007/s11356-024-33755-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 05/17/2024] [Indexed: 05/26/2024]
Abstract
The changes of medical solid waste (MSW) output in recent years have had a significant impact on the spread of the virus. There is a high-risk transmission of MSW in various stages such as storage, transportation, and treatment during the COVID-19. To cope with the risks brought by the epidemic, normalized prevention consumes a large amount of protective clothing, medical masks, goggles, packaging bags, and other related medical supplies. There is a significant uncertainty in the amount of MSW output that poses a risk of COVID-19 infection in the event of an emergency, which increases the difficulty of collecting and handling epidemic prevention MSW. The analysis of MSW data from 2000 to 2022 found a stable growth trend before 2019. However, the MSW data was a sudden increase trend from 2020 to 2022, and the COVID-19 in China was characterized by an initial stage, an outbreak stage, and a stable growth stage. The range of MSW output during the epidemic was (1.19-1.75) × 106 t a-1. The amount of MSW was approximately 1.19 × 106 t a-1 during the normalized epidemic period, and its treatment cost was as high as 3.57 × 109 yuan (RMB)·a-1. The distribution of MSW output was uneven due to factors such as climate conditions, population data, and local economy. This study has important reference value for epidemic medical material reserves and MSW treatment.
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Affiliation(s)
- Xinyi Huang
- Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions/Heilongjiang Province Collaborative Innovation Center of Cold Region Ecological Safety/School of Geographical Sciences, Harbin Normal University, Harbin, 150025, China
| | - Ziqi Zhuang
- Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions/Heilongjiang Province Collaborative Innovation Center of Cold Region Ecological Safety/School of Geographical Sciences, Harbin Normal University, Harbin, 150025, China
| | - Jiajun Liu
- Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions/Heilongjiang Province Collaborative Innovation Center of Cold Region Ecological Safety/School of Geographical Sciences, Harbin Normal University, Harbin, 150025, China
| | - Wen Shi
- Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions/Heilongjiang Province Collaborative Innovation Center of Cold Region Ecological Safety/School of Geographical Sciences, Harbin Normal University, Harbin, 150025, China
| | - Xiangdong Xu
- Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions/Heilongjiang Province Collaborative Innovation Center of Cold Region Ecological Safety/School of Geographical Sciences, Harbin Normal University, Harbin, 150025, China
| | - Lingyan Wang
- Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions/Heilongjiang Province Collaborative Innovation Center of Cold Region Ecological Safety/School of Geographical Sciences, Harbin Normal University, Harbin, 150025, China
| | - Qi Li
- School of Environmental Science & Engineering, Yancheng Institute of Technology, Yancheng, 224051, China
| | - Hanxi Wang
- Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions/Heilongjiang Province Collaborative Innovation Center of Cold Region Ecological Safety/School of Geographical Sciences, Harbin Normal University, Harbin, 150025, China.
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