TY - JOUR
T1 - Recovery from demand disruption
T2 - Two-stage financing strategy for a capital-constrained supply chain under uncertainty
AU - Zhao, Yujie
AU - Zhou, Hong
AU - Leus, Roel
N1 - Publisher Copyright:
© 2022 Elsevier B.V.
PY - 2022/12/1
Y1 - 2022/12/1
N2 - This paper addresses recovery strategies for supply chain enterprises under uncertain demand. Specifically, a bank or supplier is considered to provide financing for a capital-constrained retailer to reduce or even eliminate the negative impact of disruption. The problem is formulated with a bank-supplier-retailer game model. A robust optimization approach is used to obtain the retailer's minimax regret order quantity where only the upper and lower bound of demand are known. Four financing strategy combinations for two-stage financing before and after demand disruption are proposed, including bank-bank, supplier-supplier, bank-supplier, and supplier-bank. With respect to supply chain recovery, three strategies of mixed recovery, pure penalty, and pure investment are proposed, and their performances are examined. Furthermore, the impact of each financing combination and recovery strategy on the retailer's regret, bankruptcy risk, and profit are analyzed, which provides a basis for financing decisions. The relevant results show that the pure investment strategy can not only protect the bank and supplier from losing profit due to disruption, but also bring less bankruptcy risk to the retailer. On the other hand, penalty strategy can also mitigate the negative impact of disruption on the supplier, but it will lead the retailer to facing higher risk of bankruptcy. For the retailer, the bank-bank and bank-supplier financing combination is superior to the others because they are less likely to result in bankruptcy. Finally, as an extension, the proposed models are applied to some other financing schemes which are commonly employed in practice, and some managerial implications are drawn.
AB - This paper addresses recovery strategies for supply chain enterprises under uncertain demand. Specifically, a bank or supplier is considered to provide financing for a capital-constrained retailer to reduce or even eliminate the negative impact of disruption. The problem is formulated with a bank-supplier-retailer game model. A robust optimization approach is used to obtain the retailer's minimax regret order quantity where only the upper and lower bound of demand are known. Four financing strategy combinations for two-stage financing before and after demand disruption are proposed, including bank-bank, supplier-supplier, bank-supplier, and supplier-bank. With respect to supply chain recovery, three strategies of mixed recovery, pure penalty, and pure investment are proposed, and their performances are examined. Furthermore, the impact of each financing combination and recovery strategy on the retailer's regret, bankruptcy risk, and profit are analyzed, which provides a basis for financing decisions. The relevant results show that the pure investment strategy can not only protect the bank and supplier from losing profit due to disruption, but also bring less bankruptcy risk to the retailer. On the other hand, penalty strategy can also mitigate the negative impact of disruption on the supplier, but it will lead the retailer to facing higher risk of bankruptcy. For the retailer, the bank-bank and bank-supplier financing combination is superior to the others because they are less likely to result in bankruptcy. Finally, as an extension, the proposed models are applied to some other financing schemes which are commonly employed in practice, and some managerial implications are drawn.
KW - Demand disruption
KW - Minimax regret criterion
KW - Recovery strategy
KW - Supply chain financing
KW - Supply chain management
UR - https://www.scopus.com/pages/publications/85127313944
U2 - 10.1016/j.ejor.2022.03.009
DO - 10.1016/j.ejor.2022.03.009
M3 - 文章
AN - SCOPUS:85127313944
SN - 0377-2217
VL - 303
SP - 699
EP - 718
JO - European Journal of Operational Research
JF - European Journal of Operational Research
IS - 2
ER -