简介：为随机的系统的噪音顺序的加权的和的顺序被在概率使用限制理论估计。然后，鞅差别顺序的噪音驾驶的不稳定的ARsystem的状态的分叉率被建立。

简介：Inthispaper,weconsideranewsvendormodelinwhicharisk-aversemanagerfacesastochasticprice-dependentdemandineitheranadditiveoramultiplicativeform.Anemergencypurchaseoptionisallowedaftertherealizationofdemandtosatisfytheunitsthatareshort.Byadoptingconditionalvalue-at-risk(CVaR)asthedecisioncriterion,weaimtoinvestigatetheoptimalpricingandorderingdecisions,andtheeffectsofparameterchangesinsuchasetting.Weprovidesufficientconditionsfortheuniquenessoftheoptimalpolicyforbothdemandmodels.Weperformcomparativestaticsanalysistoshowhowtheoptimalpricingandorderingdecisionbehaveswhenchangingparameters.WealsocompareourresultswiththoseofthenewsvendorwithageneralutilityfunctionandwithCVaRcriterionunderlostsalesassumption.Ourkeyresultsinclude:(i)Forbothdemandmodels,theoptimalsellingpriceisdecreasinginriskaversion.Hence,theoptimalpriceofarisk-aversenewsvendorisnotgreaterthantheoptimalpriceofarisk-neutralnewsvendor.(ii)Incontrarytothelostsalescase,forthemultiplicativedemandmodel,theoptimalorderquantitymaynotbemonotonicinriskaversion.Consequently,theoptimalrisk-averseorderquantitymaybelowerorhigherthantheoptimalrisk-neutralcounterpart.(iii)Fortheadditivemodel,theoptimalorderquantityisstrictlyincreasingintheemergencypurchaseprice,whileforthemultiplicativemodeltheoptimalorderquantityhasnosuchamonotonicproperty.Somenumericalexamplesareconductedtoverifyourclaimsandgainmoreinsightsabouttherisk-aversedecision-makingbehaviors.

简介：论文摘要本文初步论述了当前网络购物在商品呈现上存在的局限性，并在网络购物中引入AR、VR技术来解决当前商品在网络购物平台上的呈现问题，提高使用者的观感效果，同时以AR、VR为基础，尝试构建全新的网络购物模式。