Research On The Impact Of Online Privacy Concerns On Users' Willingness To Continue To Use Online Precision Advertising

With the continuous development of data technology and the Internet,personalized network services are becoming more and more popular.As an extremely representative customized service,online precision advertising can significantly improve the commercial efficiency of buyers and sellers in online transactions.With the increasing dependence of online users on the Internet,the boundaries between individuals and the Internet have become increasingly blurred.Due to the emergence of Internet accidents in recent years,users have begun to reflect on the security of the Internet and pay more attention to their online privacy.To achieve more accurate matching,online precision advertising requires more user's personal information,but because different users pay different attention to their private information,the experience of using online precision advertising is different,so the willingness to continue to use will be affected.It can be seen that the purpose of online precision advertising is to increase the commercial efficiency of both parties,but consumers 'privacy concerns will hinder their long-term use of online precision advertising.In order to improve the commercial efficiency of both parties,it is necessary to pay attention to users' online privacy and study the impact of online privacy concerns on the willingness to continue to use precision advertising.This article uses a method combining theory and practice to study the impact of privacy concerns on the willingness to continue to use.First of all,the review of expectation confirmation theory,technology acceptance theory,perceived value theory and the research related to the concepts involved in this article provides the basis for the theoretical choice and definition of the concept of this article;second,This article absorb related research,construct the dimension of privacy concerns based on the Internet Users' Information Privacy Concerns(IUIPC)model and the privacy for information privacy(CFIP)model.Based on the theory of expectation confirmation,This paper proposes the hypothesis and model;third,through a pre-survey to rationally modify the dimensions,assumptions,and scales of this article;fourth,collect experimental data through questionnaire surveys,analyze and verify the path and assumptions of this article;fifth,this article summarize the results and make recommendations to relevant companies.Based on the results of data analysis and hypothesis testing,this paper mainly draws the following six conclusions:(1)Through the exploratory factor analysis of the pre-survey and the data verification of the formal survey,the privacy concerns variables can be divided into two dimensions,namely Control and Collection;(2)Privacy concerns will hinder the establishment of customer trust in online companies or online precision advertising,and the collection dimension will have a stronger impact on trust;(3)Privacy concerns will increase users 'perception of potential risks,and this impact from the control dimension;(4)Trust will positively affect perceived usefulness and expectation confirmation,and negatively affect perceived risk,and the impact of trust on expectation confirmation is much greater than that on perceived usefulness;(5)Perceived usefulness and expected confirmation will positively affect the will to continue to use.Unlike previous studies,the expected confirmation effect in this study is greater than the impact of perceived usefulness;(6)Perceived risk will negatively affect the will to continue to use.Based on the research conclusions,this article recommends that network data service providers: participate in the formulation of industry security standards and establish an enterprise image;improve the service level of both service efficiency and data security.This article also recommends that online precision advertising service providers: choose professional data service companies to cooperate;avoid sensitive information when pushing;establish and improve user feedback mechanisms;and clarify the operations and policies related to privacy collection.