Financial distress of an enterprise in a supply chain will pass on to others by quantity of goods etc., which may lead to a distress of the whole supply chain. In a supply chain with single manufacturer and retailer, on the condition that demand is random and influenced by business effort level(e), taking costs of efforts(g(e)) into account, how the financial distress of different level goes from the retailer to the manufacturer is described, and then decisions are made according to the value of financial distress(D). The result shows: When the distress is in different levels, there will be three kinds of decision groups: (max∏m(Q,e),max∏r(Q,e)), (max∏m(Q,e),max∏r(Q,e)), (max∏r(Q,e),max{Rm(Q,e)+Rr(Q,e)}); As the distress is lighter, the supply chain has a certain ability to repair itself; On the contrary, enterprises should change their decisions to protect themselves from the financial distress. At last, a numerical example verifies the conclusion: when D is less than 576, the distress will not be transferred; and when D ranges from 576 to 1871, the distress will be controlled a little; and when D is over 1871, the distress will be passed to the manufacturer. So the financial distress cannot be totally controlled under Decentralized decision-making. In this study, a new perception and a valuable guidance are provided to the supply chain coordination.
LI Li-jun, LIU Jie, SUN Shi-min
. Study on the Propagation and Control of Financial Distress on the Perception of Supply Chain[J]. Chinese Journal of Management Science, 2016
, 24(6)
: 46
-51
.
DOI: 10.16381/j.cnki.issn1003-207x.2016.06.006
[1] Lau A H L.A five state financial distress prediction mode[J].Journal of Accounting Research, 1987,25(1):127-138.
[2] Chen Yibing, Zhang Lingling, Zhang Liang. Financial distress prediction for Chinese listed manufacturing companies[J]. Procedia Computer Science, 2013,17:678-686.
[3] Tinoco M H, Wilson N. Financial distress and bankruptcy prediction among listed companies using accounting, market and macroeconomic variables[J]. International Review of Financial Analysis, 2013, 30:394-419.
[4] 鲍新中,杨宜.基于聚类-粗糙集-神经网络的企业财务危机预警[J].系统管理学报,2013,3(5):358-365.
[5] Tsai C F. Combining cluster analysis with classier ensembles to predict financial distress[J]. Information Fusion, 2014, 16:46-58.
[6] Sun Jie, Li Hui. Financial distress prediction using support vector machines:Ensemble vs. individual[J]. Applied Soft Computing, 2012, 12(8):2254-2265.
[7] Chen J H. Developing SFNN models to predict financial distress of construction companies[J]. Expert Systems with Applications,2012, 39(1):23-827.
[8] Lin Fengyi. Novel feature selection methods to financial distress prediction[J]. Expert Systems with Applications, 2014, 41(5):2472-2483.
[9] Redouane Elk.The cost and timing of financial distress[J].Journal of Financial Economics, 2012, 105(2):62-81.
[10] 徐晓燕,孙艳红.供应链企业财务困境的传递过程研究[J].中国管理科学,2008, 8(16):132-139.
[11] 徐晓燕,李桃,陈华.考虑投入产出效率的中小企业财务困境预测方法[J].中国管理科学,2009,2(17):113-118.
[12] 孙燕红.供应网络中的企业破产风险、传递机制及其控制策略[D].合肥:中国科学技术大学,2010.
[13] 丁胡送.协作方式对供应链财务困境形成及传递影响分析[J].预测,2013,32(1):52-56.
[14] 谷祺,刘淑莲.财务危机企业投资行为分析与对策[J].会计研究,1999,(10):28-31.
[15] 林强,李苗.保兑仓融资模式下收益共享契约的参数设计[J].系统科学与数学,2013,33(4):430-444.
[16] 张维迎.博弈论与信息经济学[M].上海:上海人民出版社,2004.
[17] Yao L. Supply chain modeling:Pricing, contracts and coordination[D]. Hong Kong:Chinese University of Hong kong, 2002.
[18] 刚号,唐小我.基于制造商"努力"的供应链最优策略选择[J].中国管理科学,2014,22(4):36-40.
[19] 庞庆华.需求受努力因素影响的供应链收益共享契约模型[J].系统管理学报,2013,22(3):371-378.