Effective waste management in service industry: Fuzzy-based modelling approach for strategic decision-making

Hasan Dinçer, Serhat Yüksel, Serkan Eti, Yaşar Gökalp, Alexey Mikhaylov, Zuleima Karpyn

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
JournalWaste Management and Research
DOIs
StateAccepted/In press - 2024

All Science Journal Classification (ASJC) codes

  • Environmental Engineering
  • Waste Management and Disposal
  • Pollution

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