供应链外包的DEA与风险价值模型概述

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1、Click to edit Master title style,Click to edit Master text styles,Second level,Third level,Fourth level,Fifth level,*,*,Click to edit Master title style,Click to edit Master text styles,Second level,Third level,Fourth level,Fifth level,*,*,Supply Chain Outsourcing in,Enterprise Risk Management:,A,DE

2、A VaR Model,Desheng Dash Wu,University of Toronto,Reykjavik University,RiskLab,dashrisklab.ca,Extracted from,Olson D.L.and Wu D.,Enterprise Risk Management,.World Scientific Publisher.2007 Wu D.and Olson D.L.,A Comparison of Stochastic Dominance and Stochastic DEA for,Vendor Evaluation,.Int J of Pro

3、duction Research.2007(1).,Nov,2008,Callfor paper,Outline,Introduction,EnterpriseRiskManagement(ERM,全面风险管,理,理,),Supply Chain Outsourcing,Vendor Evaluation,Contribution:,ERM stepsin SupplyChainOutsourcing Risk,Dataenvelopment analysis,(DEA)+,Valueat Risk,(VaR):Intuition,Conclusions and,Future Research

4、,(,银行链,金融危机,),Review ofRiskManagementTools,风险管理工,具,具介绍,RiskManagementtools,mean-variance framework of portfolio theory i.e.,selectionand diversification(Markowitz1952),Capital Asset Pricing Model(Sharpe1964;Lintner1965;Mossin 1966),ArbitragePricing Theory(Ross,1976),Option pricingtheory(Black 1972;B

5、lack1973),Valueat Risk(VaR),RiskMetrics(Jorion1997),Prob 1 day Loss VaR=1-,Min,VaRP(VaR),EnterpriseRiskManagement,Professional organization,Consultant,Ratingagency,Academics,31%adopted ERMin Canadian risk&insuranceKleffner2003,Why ERM?Toyota,Review ofRiskManagementTools,(cont.),Various Risks:$Measur

6、ement,Definitionof ERM,Systematic,integrated approach,Manage allrisks facing organization,External,Economic(market-price,demand change),Financial(insurance,currencyexchange),Political/Legal,Technological,Internal,Humanerror,Fraud,Systems failure,Disruptedproduction,StochasticOR ModelsforRiskManageme

7、nt(Beneda 2005,Dash&Kajiji2005),Multiple criteria analysis,Subjective,Simulation,Probabilistic;Can be subjective(systemdynamics),Dataenvelopment analysis(DEA),Optimization,Objective,subjective,probabilistic,ERM Research and Steps,Step1,:,Determinethe corporation,s,objectives,Step2,:,Identify,the ris

8、k factors,exposures,Step3,:,Quantify,the factors,exposures,Assess the,impact,Step4,:,Examine alternativeriskmanagement,tools,Step5,:,Select,appropriate risk management approach,Step6,:,Implement,and,monitor,program,More than 80 frameworks:problem-oriented,descriptive,frameworks,Specific ERM:SupplyCh

9、ain Outsourcing Risk,Supplier,Manufacturer,Retailer,End customer,Warehouse,A Supply ChainModel,SupplyChain Vendor Selection,SupplyChain Vendor Selection,go,o,ds,input,bads,(risk,uncertainty?)(risk,uncertainty?),Efficiency,=output/input,Supplier,P,erformance,Data Envelopment Analysis(DEA)-Determinist

10、ic,Charnes,Cooper,Rhodes,n Vendors(DMUs)to beevaluated.,m different inputs Xij,sdifferent outputs Yrj.,The,deterministicDEA,model,DEA efficiencyfor,DMUj:,Deterministic,DEA,(cont.),CCR Multiplierform,DEA VaR-Stochasticmodel,j,:,aspiration level,;,j:,risk criterion;,0,j,j,1,Intuition:1)At what confide

11、ncelevel,it isefficient to select the?thVendor?,2)At what confidencelevel,it isenoughto reduce the?th cost in order tomake the?th Vendor efficient?,(1),Stochastic DEA,Assuming multivariatenormaldistribution:,(2),Equivalent linear programming,:,(3),Metricsin Vendor Selection,Olson&Wu,Criteria,Number

12、of studies using,Price/cost,12,Acceptance/quality,12,On-time response/logistics,12,R&D in technology/innovation/design,7,Production facilities/assets,6,Flexibility/agility,6,Service,4,Management&organization,2,Data Set,Moskowitz,Tang&Lam,2000,Decision Sciences,31,327-360,9 vendors,V,j,Mean,Standard

13、deviation,Normally distributed,12 Criteria each with weight,W,i,Quality personnel,Quality procedure,Concern for quality,Company history,Price-quality,Actual price,Financial ability,Technical performance,Delivery history,Technical assistance,Production capability,Manufacturing equipment,Sampledata de

14、monstration,Criteria,V1,V2,V3,V4,V5,V6,V7,V8,V9,1 Quality personnel,85,(5.2),82,(4.2),90,(3.1),78,(12.8),95,(1.5),75,(2.9),90,(1.7),70,(12.2),75,(2.8),2 Quality procedure,80,(3.3),88,(4.2),85,(5.1),90,(4.2),75,(5.6),82,(2.2),82,(4.2),90,(33),78,(3.8),3 Delivery history,80,(4.7),83,(5.5),70,(5.5),75,

15、(14.3),85,(5.8),85,(1.9),75,(5.9),90,(2.4),90,(1.1),4 Company history,90,(5.5),88,(4.5),75,(7.0),85,(5.6),70,(5.6),80,(4.1),80,(4.6),85,(4.5),82,(3.7),Simulated weights andParameter Sensitivity,Equal weights,Usefulto identify dominatedsolutions,V,2,0.03,V,4,0.08,V,6,0.36,V,8,0.53,Ordinalweights,Refl

16、ectdecision maker preference,More useful tomake decision:select nondominatedsolutions,Used centroidweightsOlson&Dorai,V,2,0.71,V,4,0.22,V,6,0.07,V,8,0,Adjusted risk criterion0,j,1,Adjusted RHSs with,j,DEA efficiency scores:equalweight,%,V1,V2,V3,V4,V5,V6,V7,V8,V9,Average,V1,95.40,94.33,93.58,94.62,75.11,95.33,95.16,94.32,89.72,91.95,V2,93.56,95.60,94.63,95.02,79.37,93.93,94.53,92.15,90.02,92.09,V3,94.98,85.17,95.37,92.27,94.83,88.55,92.96,94.71,92.25,92.34,V4,89.61,90.28,95.93,98.11,89.23,93.88,