The Impact Of E-commerce Platforms’ Artificial Intelligence Technology On Return Intention

The rapid development of artificial intelligence technology has brought people new technical experience and application value.In the field of e-commerce,intelligent tools based on AI technology are widely used for businesses and users,which brings new opportunities.At present,there are two key problems in the field of e-commerce:one is a large number of consumer returns,the other is the problem of product perception uncertainty.The problem of returns not only brings pollution to the environment,but also brings cost to enterprises and consumers.And the product uncertainty is the antecedent of consumer returns.In practice,exploring the relationship among AI technology of e-commerce and perceived uncertainty of product and return intention will help e-commerce platform to understand the impact of AI technology on return intention,and then use AI technology to restrain return intention.It also made a theoretical supplement to the factors and mechanism that affect the perceived uncertainty and return intention of product.On the basis of literature review and Theoretical Review,this study selected three e-commerce AI technologies which are widely used in our country nowadays:personalized recommendation,intelligent customer service and intelligent search.In this study,Personalized recommendation,intelligent customer service and intelligent search were independent variables.The two dimensions of product perceived uncertainty: the product fit uncertainty and the product quality uncertainty were used as mediating variable.And the return intention were used as dependent variables.On this basis,this study proposes research hypothesis and built a structural equation model to do empirical analysis and hypothesis testing.A total of 599 valid questionnaires were collected through the questionnaire survey.After testing the validity and Reliability of the measurement tools.This study use Amos23.0 to construct a structural equation model for the relationships among personalized recommendation,intelligent customer service,intelligent search and product fit uncertainty,product quality uncertainty,and return intention.Their path coefficients and mediating effects are analyzed.The study found some conclusions.Firstly,personalized recommendation,intelligent customer service and intelligent search all have significant negative effects on return intention,and the direct effect of intelligent customer service is the strongest.Secondly,personalized recommendation and intelligent search have significant negative effects on both dimensions of product perceived uncertainty,while intelligent customer service only has significant negative effects on product fit uncertainty,the two dimensions of perceived uncertainty have positive effects on return intention.Thirdly,personalized recommendation,intelligent customer service and intelligent search have significant negative indirect effects on return intention.Among them,the product fit uncertainty and the product quality uncertainty partially mediated the relationship between personalized recommendation,intelligent search and return intention Only the product fit uncertainty plays a partial mediator effect between intelligent customer service and return wish.Fourth,the mediating effect of perceived quality uncertainty is stronger than that of product fit uncertainty between personalized recommendation,intelligent search and return intention.Based on the conclusion,the following suggestions are put forward.First,the platform should increase the use rate and Intelligence degree of personalized recommendation,intelligent customer service and intelligent search.Secondly,the platform should establish a perfect and detailed user label system and product quality evaluation indicators,and bring them into the personalized recommendation algorithm.In terms of presentation,the platform should pay attention to display the content that matches with the consumer and release the signal of high quality.Thirdly,the platform should enhance the intelligent customer service answer content and personal relevance and the speed of reply.In the pre-purchase phase,Intelligent Customer Service can take the initiative to provide consumers with recommendations and personalized advice.Fourth,the platform should give more weight to personal match and product quality in the algorithm,and increase the description of product and personal match and release positive quality signal when presenting information.On the whole,the conclusion of this study can help e-commerce platform improve AI technology from the perspective of consumer perception and behavior and then use AI technology to reduce returns effectively,which do great benefits to the sustainable development of e-commerce platform.