Study Of APP Privacy Information Collection Strategy Based On Conjoint Analysis

In the era of digital economy,it is normal for APPs to collect private information.Users can disclose private information to APP in exchange for better service and personalized experience.Enterprises can mine data value through user privacy information.By improving the quality of precise,personalized and customized services,enterprises can bridge the gap with other competitors.This is a win-win situation.However,companies generally adopt over-collection strategies,which often cause companies to over-collect user data and abuse user data,and even more so,privacy leaks.This not only has a very bad impact on the enterprise itself,but also makes the user suffer the secondary damage caused by the leakage of private information,resulting in the user’s privacy protection behavior.If the enterprise is too conservative and cautious in its collection strategy,the collected private information cannot generate application value,and the APP may fail to meet user service needs,resulting in user churn,which will have an adverse impact on the enterprise.Therefore,it is necessary for enterprises to adopt practical privacy information collection strategies for different types of privacy information based on their product characteristics,and find a reasonable balance in the conflict between enterprise information needs and user privacy protection.Based on the perspective of the enterprise platform,this article studies the APP privacy information collection strategy and explores the influencing factors and internal mechanisms that affect users’ privacy disclosure behavior.First,this paper summarizes the initial framework of user privacy disclosure mechanism through literature analysis,and then designs a research model of user privacy information disclosure in APP based on the privacy calculation model.Afterwards,the data was collected through questionnaire surveys,and the structural equation method was used to obtain factors that significantly affected the privacy disclosure behavior of the users,which provided data support for the determination of the attributes of the conjoint analysis method.Finally,the simulated product portfolio is used to detect the user’s preference for privacy disclosure of different attributes.The whole book consists of six chapters,each chapter is as follows:Chapter 1 is the introduction.It describes the contradiction between the current corporate privacy information needs and the protection of user privacy information,and proposes research significance,research methods,innovations and contributions.Chapter 2 is the literature review part.This chapter provides theoretical basis for research and indicates the research direction.It also summarizes the research status of privacy disclosure and conjoint analysis.Chapter 3 is the part of the research model construction and hypothesis,based on privacy computing theory to build a research framework of privacy information disclosure behavior.Based on the framework of the research model,this study uses the literature analysis method to extract the influencing factors and relationship hypotheses of privacy disclosure behaviors,and constructs the relationship hypothesis model of this study.Chapter 4 is the part of experimental design and model verification.This chapter describes the selection of empirical methods,selection of survey samples,data collection process,experimental plan design,experimental process,questionnaire measurement scale,etc.Subsequently,the reliability and aggregation validity analysis and path analysis of the sample data were performed by SPSS and Smart PLS 3.0 to verify the relationship hypothesis between the study variables.Chapter 5 is the experimental design and verification part of the conjoint analysis.This paper determines the attributes and attribute levels of the conjoint analysis method based on the verified hypothesis,and then obtains the relative importance and validity of each attribute according to the data analysis,and further studies the differential preferences of the subdivided groups.Chapter 6 is the research conclusions and future prospects,discussing the practical significance and academic value of this research,especially how companies formulate effective privacy information collection strategies based on their product characteristics and target customers.At the end,it summarizes the shortcomings of this article and points out what is worth digging and exploring in this field.