Research On The Construction Of Evaluation Index Sysyem Of E-commerce Information Recommendation Service Quality Based On User Perception

In recent years,e-commerce has developed rapidly with the support of Internet information technology.Taobao,JD.com and other mainstream e-commerce platforms are actively discussing e-commerce information recommendation services in order to better meet user information needs and realize thousands of people.The e-commerce platform analyzes the characteristics of users' consumption behaviors and actively pushes product information to users to reduce the users' retrieval time,improve users' shopping experience,and increase users' shopping efficiency.In this context,e-commerce information recommendation has gradually become the focus of attention.Most of the existing literatures have explored ways to improve the quality of information recommendation services from the aspects of information recommendation systems and information recommendation models.There is a lack of research on analyzing the quality of e-commerce information recommendation services from the perspective of user perception.In view of this,this paper builds an e-commerce information recommendation service quality evaluation index system based on user perception to identify the key factors affecting the quality of e-commerce information recommendation services and understand the users' evaluation status od e-commerce platform information recommendation service quality sucn as Taobao.This study enriches the research content of information service quality evaluation,and has certain guiding significance for the improvement of e-commerce and the improvement of information recommendation service quality.This article first uses the literature survey method to sort out relevant literature on information recommendation,e-commerce information recommendation,information service quality evaluation,etc.,and uses the interview method to explore and evaluate the elements of e-commerce information recommendation service quality,and determine 11 evaluation factors,such as usefulness,novelty,and reliability.After literature search and expert discussion,15 evalution indicators were determined,and an initial evalution indicator system for the quality of e-commerce information recommendation service was constructed.Then,using the questionnaire survey method,the rationality verification and correction of the initial evaluation index system of the e-commerce information recommendation service is performed.Select e-commerce platform(APP)users as the survey objects and collect data through the network and social media software.This article uses SPSS24.0 software to analyze the questionnaire data.The data analysis results show that the questionnaire has good reliability and validity.This paper uses factor analysis to perform dimensionality reduction clustering analysis on evaluation indicators,and clusters 15 secondary evaluation indicators into 3primary index dimensions,which are personalized information recommendation,intelligent information recommendation,and recommended information quality.The principal component analysis method determines the weight of each index,and revises and determines the final evaluation index system for the quality of e-commerce information recommendation services.Finally,using the e-commerce information recommendation service quality evaluation index system constructed in this paper,an empirical analysis of the e-commerce information recommendation service quality on the platforms of Taobao,JD.com and Vipshop.The empirical results show that the information recommendation services of the three platforms have their own advantages and disadvantages,but they all do better in terms of stability,novelty and usefulness.In the subsequent information recommendation process,the information recommendation system can be better maintained stable,Provide more useful information and continue to recommend information that conforms to social trends for users;but all have deficiencies in reliability,feedback,and pertinence.