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دسته بندی:
زنجیره تامین - supply chain
سال انتشار:
2021
عنوان انگلیسی مقاله:
Modeling and identification of suitable motivational mechanism in the collection system of municipal solid waste supply chain
ترجمه فارسی عنوان مقاله:
مدل سازی و شناسایی سازوکار انگیزشی مناسب در سیستم جمع آوری زنجیره تأمین پسماند جامد شهری
منبع:
Sciencedirect - Elsevier - Waste Management, 129 (2021) 76-84: doi:10:1016/j:wasman:2021:05:011
نویسنده:
Pradeep Rathore
چکیده انگلیسی:
Many studies have identified that incentive, subsidy, and reward-penalty mechanisms improve the col- lection rate of recyclables and end of life products. But there is a lack of studies mathematical models and analysis of these mechanisms in the context of municipal solid waste supply chain. Therefore, in this study, models have been formulated for municipal solid waste supply chain (profit) considering government and collectors’ profit under incentive, subsidy, and reward-penalty mechanisms. The study has analysed the models against the non-separation and separation scenario of waste. A numerical analysis is performed and observed that: (i) separation of waste at source along with incentive, subsidy, and reward-penalty mechanisms scenario improve the collection rate by 17%, 23%, 30%, and 45% compared to non-separated MSW. (ii) Incentive, subsidy, and reward-penalty mechanisms increases the total sup- ply chain profit by around 9%, —36% and 18%. (iii) reward-penalty mechanism performs better than incentive and subsidy mechanism by providing the high supply chain profit (18% and 85%) and collection rate (22% and 15%) comparatively. Further, sensitivity analysis carried out to understand the behaviour of the models against the key parameters. The study also develops interesting propositions and proved for a better understanding of the models. From results, some key managerial insights have been drawn and a few future scopes of the study are presented.© 2021 Elsevier Ltd. All rights reserved.
Keywords: Solid waste supply chain | Circular economy | Incentive | Subsidy | Reward-penalty
قیمت: رایگان
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