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Optimizing a Sustainable Supply Chain Inventory Model for Controllable Deterioration and Emission Rates in a Greenhouse Farm

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  • Umakanta Mishra

    (Department of Business Administration, Soochow University, 56 Section 1, Kuei-Yang Street, Taipei 10048, Taiwan
    Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore 632014, India)

  • Abu Hashan Md Mashud

    (Department of Mathematics, Hajee Mohammad Danesh Science and Technology University, Dinajpur 5200, Bangladesh)

  • Ming-Lang Tseng

    (Institute of Innovation and Circular Economy, Asia University, Taichung City 41354, Taiwan
    Department of Medical Research, China Medical University Hospital, China Medical University, Taichung City 40402, Taiwan
    Faculty of Economic and Management, University Kebangsaan Malaysia, Bangi 43600, Malaysia)

  • Jei-Zheng Wu

    (Department of Business Administration, Soochow University, 56 Section 1, Kuei-Yang Street, Taipei 10048, Taiwan)

Abstract

This study investigated how greenhouse managers should invest in preservation and green technologies and introduce trade credit to increase their profits. We propose a supply chain inventory model with controllable deterioration and emission rates under payment schemes for shortage and surplus, where demand depends on price and trade credit. Carbon emissions and deterioration are factors affecting global warming, and many greenhouse managers have focused on reducing carbon emissions. Carbon caps and tax-based incentives have been used in many greenhouses to achieve such reduction. Because of the importance of reducing carbon emissions for developing a green supply chain, various studies have investigated how firms deal with carbon emission constraints. In this continuation, we have used green technology to curb the excessive emissions from the environment or make it clean from CO 2 . In a seller–buyer relationship, the seller can offer a trade credit period to the buyer to manage stock and stimulate demand. Deterioration may become a challenge for most firms as they are under time constraints control, and preservation technology could help. This study proposes three novel inventory strategies for a sustainable supply chain (full backorder, partial backorder, and no backorder), linking all these important issues. The solution optimizes total annual profit for inventory shortage or surplus. We conducted a numerical study with three examples to evaluate the model’s authenticity and effectiveness and demonstrate the solution technique. The deterioration and emission rates can be included in a trade credit policy to increase greenhouse profits. The results suggest that greenhouse managers could apply the proposed model to manage real-world situations.

Suggested Citation

  • Umakanta Mishra & Abu Hashan Md Mashud & Ming-Lang Tseng & Jei-Zheng Wu, 2021. "Optimizing a Sustainable Supply Chain Inventory Model for Controllable Deterioration and Emission Rates in a Greenhouse Farm," Mathematics, MDPI, vol. 9(5), pages 1-23, February.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:5:p:495-:d:507575
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    References listed on IDEAS

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    1. Gao Xiang Lou & Hai Yang Xia & Jie Qiong Zhang & Ti Jun Fan, 2015. "Investment Strategy of Emission-Reduction Technology in a Supply Chain," Sustainability, MDPI, vol. 7(8), pages 1-25, August.
    2. Juanjuan Qin & Xiaojian Bai & Liangjie Xia, 2015. "Sustainable Trade Credit and Replenishment Policies under the Cap-And-Trade and Carbon Tax Regulations," Sustainability, MDPI, vol. 7(12), pages 1-22, December.
    3. Liang Lu & Thomas Reardon & David Zilberman, 2016. "Supply Chain Design and Adoption of Indivisible Technology," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(5), pages 1419-1431.
    4. Chen, Sheng-Chih & Teng, Jinn-Tsair, 2015. "Inventory and credit decisions for time-varying deteriorating items with up-stream and down-stream trade credit financing by discounted cash flow analysis," European Journal of Operational Research, Elsevier, vol. 243(2), pages 566-575.
    5. Xiaoxue Du & Liang Lu & Thomas Reardon & David Zilberman, 2016. "Economics of Agricultural Supply Chain Design: A Portfolio Selection Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(5), pages 1377-1388.
    6. Johari, Maryam & Hosseini-Motlagh, Seyyed-Mahdi & Nematollahi, Mohammadreza & Goh, Mark & Ignatius, Joshua, 2018. "Bi-level credit period coordination for periodic review inventory system with price-credit dependent demand under time value of money," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 270-291.
    7. Ata Allah Taleizadeh & Shayan Tavakoli & Luis Augusto San-José, 2018. "A lot sizing model with advance payment and planned backordering," Annals of Operations Research, Springer, vol. 271(2), pages 1001-1022, December.
    8. Shayan Tavakoli & Ata Allah Taleizadeh, 2017. "An EOQ model for decaying item with full advanced payment and conditional discount," Annals of Operations Research, Springer, vol. 259(1), pages 415-436, December.
    9. Dye, Chung-Yuan & Yang, Chih-Te, 2015. "Sustainable trade credit and replenishment decisions with credit-linked demand under carbon emission constraints," European Journal of Operational Research, Elsevier, vol. 244(1), pages 187-200.
    10. B.C. Giri & T. Maiti, 2013. "Supply chain model with price- and trade credit-sensitive demand under two-level permissible delay in payments," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(5), pages 937-948.
    11. Zilberman, David & Lu, Liang & Reardon, Thomas, 2019. "Innovation-induced food supply chain design," Food Policy, Elsevier, vol. 83(C), pages 289-297.
    12. Pourmohammad Zia, Nadia & Taleizadeh, Ata Allah, 2015. "A lot-sizing model with backordering under hybrid linked-to-order multiple advance payments and delayed payment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 82(C), pages 19-37.
    13. Bakker, Monique & Riezebos, Jan & Teunter, Ruud H., 2012. "Review of inventory systems with deterioration since 2001," European Journal of Operational Research, Elsevier, vol. 221(2), pages 275-284.
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