During the last decade, to identify and mitigate supply disruptions is a topic that receives substantial management attention. Both diversifying supply sourcing including dual-sourcing and adding a backup supplier are logic ways to manage the risk of supply disruptions. There are two options execution modes. One is N mode that pushes ordering patterns, which means that the retailer orders from the backup supplier in advance under uncertain demand circumstances, the other is Y mode, push & pull ordering patterns, which means that the retailer doesn't order from backup suppliers until he knows the demand circumstance. It's successfully proved that the model is a convex programming through two options implementation strategy adopted by the retailer, and using Karush-Kuhn-Tucker conditions, a predetermined amount of backup suppliers, the closed expressions of optimal order quantity and profit expression can also be obtained. The threshold of using a backup supplier is given. By theorems and further numerical example, it can be concluded:Optimal profits is larger than primary supplier's while primary supplier has larger order quantities under N mode, under Y mode, backup supplier's capabilities predetermined amount. The impacts of model parameters on the ordering quantity from primary supplier are a little different based on the relative size of ce and c because of the execution of options. The capacity utilization of backup suppliers is highest when ce<c but lowest when ce>c under N mode, and it is in the middle level under Y mode. The retailer can obtain more profits under Y mode relative to under N mode as g, c and ce increase, or s and γ decrease.
LI Xin-jun, WANG Jian-jun, DA Qing-li
. Decision Analysis of Backup Supplier for Supply Disruptions with Stochastic Demand[J]. Chinese Journal of Management Science, 2016
, 24(7)
: 63
-71
.
DOI: 10.16381/j.cnki.issn1003-207x.2016.07.008
[1] Yu Gang, Qi Xiangtong. Disruption management:Framework, models and application[M].Fitchburg, MA:World Scientific Publishing Company, 2004.
[2] 傅克俊, 胡祥培, 王旭坪. 供应链系统中的应急策略与模型[J]. 中国软科学, 2007(5):119-124.
[3] 姚杰, 计雷, 池宏. 突发事件应急管理中的动态博弈分析[J]. 管理评论, 2005,17(3):46-51.
[4] 刘德海, 于倩, 马晓南. 基于最小偏差组合权重的突发事件应急能力评价模型[J]. 中国管理科学, 2014,22(11):79-86.
[5] 萧海东, 陈宁. 基于知识库的应急领域脆弱性指标体系研究[J]. 中国管理科学, 2014, 22(7):76-81.
[6] Tomlin B. On the value of mitigation and contingency strategies for managing supply chain disruption risks[J]. Management Science, 2006, 52(5):639-657.
[7] 李新军,季建华,王淑云. 供应中断情况下基于双源采购的供应链协调与优化[J]. 管理工程学报, 2014,28(3):141-147.
[8] Tang S Y, Gurnani H, Gupta D. Managing disruption in decentralized supply chains with endogenous supply processreliability[J]. Production and Operations Management, 2014, 23(7):1198-1211.
[9] Kim S H,Tomlin B. Strategic failure prevention and recovery capacity investments[J]. Management Science, 2013, 59(7):1631-1649.
[10] Sting F J, Huchzermeier A. Ensuring responsive capacity:How to contract with backup suppliers[J]. European Journal of Operational Research, 2010, 207(2):725-735.
[11] 盛方正,季建华. 最优期权合同组合的充要条件及采购方法[J]. 系统管理学报, 2008,17(3):307-311.
[12] 赵金实, 王浣尘, 郑晓涛. 期权定价市场化情况下逆向主导型供应链协调机制研究[J].管理工程学报2009,23(2):111-115.
[13] Cachon G P, Zhang Fuqiang. Procuring fast delivery:Sole sourcing with information asymmetry[J]. Management Science, 2006, 52(6):881-896.
[14] Kleindorfer P R, Wu D J. Integrating long and short term contracting via business to business exchange for capital intensive industries[J]. Management Science, 2003, 49(11):1597-1615.
[15] Victor M, David S. A portfolio approach to procurement contracts[J]. Production and Operation Management, 2005, 14(1):90-114.
[16] Wu D J, Kleindorfer P, Zhang J E. Optimal bidding and contracting strategies for capital intensive goods[J]. European Journal of Operational Research, 2002, 137(3):657-676.
[17] 丁斌, 桂斌. 基于合作博弈的预付条件下应急物资库存策略[J]. 运筹与管理, 2011,20(3):60-65.
[18] 田军, 葛永玲, 侯丛丛. 政府主导的基于实物期权契约的应急物资采购模型, 系统工程理论与实践, 2014,34(10):2582-2590.
