| With the development of Internet technology,online trading is playing more and more important role in market economy.When it brings a lot of convenience to traders,however,some new problems loom out.Because of the physical distance between buyers and sellers,unlike traditional market,the information asymmetry problem in online market is more significant.Reputation system and assurance mechanism,as the common methods to solve information asymmetry in online trading platform,have been investigated by many researchers.Past researches usually singly take reputation or assurance into account,few of them made discussion about the interaction between the two.This dissertation analyzes both reputation system and assurance mechanism simultaneously to study the relationship between them.Thus make the platform get more accurate performance of the two and then to better optimize relative mechanisms.Firstly,this dissertation discusses the information asymmetry problem in online trading and educes the two main object in this research-reputation system and assurance mechanism.After generalizing past researches,it points out the conclusions and divergences.Secondly,on the basis of Spence’s signaling game model,this research builds the signaling game model of online buyers and sellers.With the comparative static analysis of the model which considers both reputation and assurance,it educes some propositions and discusses their realistic meaning.The conclusion shows that the reputation of a seller can promote his revenue,and only when his reputation is low enough,the signaling effect of assurance shows up.Using the mobile phone transaction data from Taobao,this dissertation makes threshold regression to empirically verify the above propositions and draws some extra conclusions.Finally,taking into account the above conclusions,this research provides some advices to platforms or supervisors,in the aspect of both reputation system and assurance mechanism. |
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