Research On The Influence Of Different Quality Signals On Knowledge Product Purchase Decision

With the continuous development of Internet business form,online transactions are not limited to the sale of ordinary commodities.The rise of the sharing economy makes many service products enter into online transactions.As a new product form,knowledge products are gradually changing from free sharing to user payment.In online transactions,there are often problems of information asymmetry.And information asymmetry always leads to uncertainty of product quality.Unlike ordinary products,knowledge products have unique characteristics of non-material,difficult to test and high degree of non-standardization.These characteristics make the quality uncertainty of knowledge products more prominent and increase the difficulty for consumers to judge the quality of knowledge products.According to Spence’s(1972)signal theory,signals can be used to solve the information asymmetry in transactions,so as to improve consumers’ perception of product quality.But in the Internet,the quality signals of knowledge products can come from many aspects,such as the introduction of knowledge products themselves,the personal description of knowledge providers,the consumers’ reviews on knowledge products,and so on.What kind of quality signals can promote consumers’ decision-making,how can these quality signals act on consumers? And in different periods of knowledge products,which quality signals should be used to attract consumers to improve product returns is not clear.Therefore,on the basis of quality signal theory and ELM theory,according to different stages of knowledge products,this paper will study the influence of different quality signals on consumers’ purchase decisions and the interaction between different quality signals in the transaction of knowledge products.In this study,Python are used to capture the relevant data of knowledge products in the two stages before and after live broadcasting on “Zhihu Live”.Through data cleaning and screening,536 data samples are finally left.Through multiple regression analysis of data in different stages,the effects of quality signals in different product stages on consumers’ purchase decisions are tested,and the interaction between quality signals at different stages is also discussed.The results show that in the first stage,the knowledge product and knowledge provider’s description information,knowledge product audition signal of the central path quality signals and the knowledge provider’s reputation signal of the edge path quality signals all have significant positive effects on consumers’ purchase decisions.In the second stage,only the quality signals of the edge path-knowledge provider’s reputation signal and online score have significant positive effects on consumers’ purchase decisions.Besides,online scoring can enhance the impact of reputation signals of knowledge providers on consumer decision-making.In addition,according to the two stages’ model test results,online score and reputation signals have greater impact on purchasing decisions than the descriptive information of knowledge products and knowledge providers in the central path.This study has certain theoretical and practical significance.In theory,The research on the quality signal of knowledge providers is extended,and different quality signals are also distinguished from multiple dimensions.In addition,combined with the knowledge payment scenario,this study describes the impact model of different quality signals on the knowledge products’ purchase decision,enriches the research on the impact of different quality signals on consumers’ purchase decision in the service product field,and combs and verifies the purchase decision mechanism of knowledge products rigorously.In practice,this paper takes the knowledge payment platform--“Zhihu Live” as the research object,through real and objective data analysis,the results have practical guiding significance for both knowledge providers and platforms.For example,knowledge providers can reduce consumers’ uncertainty of product quality and promote purchasing through detailed information description of themselves and the products and open the audition functions;at the same time,knowledge providers should also actively interact with other users in the knowledge community to obtain high reputation value,so as to increase potential consumers’ trust and ability recognition through the recognition of existing consumer groups,and then improve consumers’ perception of their knowledge products’ quality,thus enhance the sales of knowledge products.From the platform’s side,it should also actively improve the signal display function and improve the evaluation system,so as to promote knowledge product trading and improve the performance of the platform.