| Nowadays,information is essential to fostering the high-quality growth of the economy and society.It is also the "gold mine of resources"that big businesses are pursuing.The value of information,however,poses serious threats to the personal security of information sources,primarily users,as well as reshaping the social industrial ecology and altering the business paradigm of enterprises.In the era of mobile networks,mobile applications(APPs)are a crucial medium for information exchange and a"disaster area" that leads to privacy breaches.Security and compliance management issues are morphing into social issues.As the most significant"means of production," APP users are ecologically vulnerable in the long run,making it difficult to protect user security and well-being.Panic disorder with privacy codes will also force its dwindling information disclosure or falsified personal information,which in turn affects the level of liquidity and authenticity in society.This will substantially impede the societal advantages received from information resources as well as impair the ecological and healthy development of the APP industry,harming not only the precision marketing and service innovation of businesses.Therefore,it is crucial for businesses and industry authorities to understand the internal factors influencing users’ willingness to authorize the use of their personal information and to establish a constructive multiparty cooperation system.Additionally,the government and businesses play a significant role in the mobile APP ecosystem.Clarifying the mutual influence and correlation between users,APP providers,and the government is a crucial topic for the development research of the mobile APP industry.It is also important to explore the best way to realize information circulation and privacy protection.Based on the foregoing,this paper intends to begin by classifying the relevant concepts,theories,and current state of mobile APP privacy research,and then use structural equation modeling and evolutionary game theory as the primary methodologies to analyze the direct,indirect,and regulatory factors influencing APP users’ willingness to authorize personal information,and to depict the evolutionary path of strategies for users,APP supplying enterprises,and governments.The following are the main research findings:(1)In Chapter 3,the conceptual model of APP users’ information authorization intention based on the "personality-privacy" architecture is proposed and verified by combining the privacy calculus theory with the Big Five personality theory.This chapter investigates the impact of cost,benefit,and trust factors on APP users’ willingness to authorize personal information,as well as the role of five personality traits on APP users’perceived benefits,privacy concerns,and trust.Simultaneously,the connection between prior negative experiences and privacy concerns,as well as the final willingness to authorize,is revealed.Personal data from 455 users were collected via questionnaire in the empirical analysis section,and the partial least squares structural equation model(PLS-SEM)was used for data analysis and hypothesis testing.According to the findings,APP users’ perceived benefits and trust have a positive impact on their willingness to authorize private information,whereas privacy concern has a negative impact on their willingness to authorize.At the same time,trust has a positive and negative impact on perceived benefits and privacy concern as a mediating variable.Extraversion and agreeableness can lead to a stronger perception of benefits,whereas agreeableness,neuroticism,and conscientiousness are more likely to be disturbed by privacy concerns,and agreeableness and neuroticism have positive and negative effects on user trust,respectively.Furthermore,negative previous experiences can easily lead to privacy concerns,limiting their willingness to authorize personal information.These findings support the significance of extended privacy calculus theory on personal information decision-making intention and offer a plausible explanation for the association between personality traits and privacy perception elements among APP users.(2)The opening and closing of "boundaries" determine the dynamic process of constant adjustment that is privacy decision-making.The chapter 4 uses the Communication Privacy Management theory(CPM)as its main framework,proposes a privacy boundary management model,and uses four proxy privacy guarantee mechanisms as antecedent variables.This model views perceived privacy risk and perceived privacy control as the key components of privacy boundary formation.The effectiveness of privacy policy and privacy protection technology at the corporate level,as well as government legislation and industry self-regulation at the macro level,are all discussed in relation to the formation of privacy boundaries.In addition,two different information features of information sensitivity and information relevance are included as moderating factors.Finally,user information was gathered using a questionnaire survey,and 510 sample data were empirically examined using a structural equation model based on covariance(CB-SEM).The results demonstrate that industry self-regulation is less effective at promoting users’ positive perceptions than macro-level government legislation,which in turn encourages the establishment of privacy boundaries.Users’ perceptions of privacy risk and privacy control are significantly influenced by the effectiveness of privacy policies and privacy protection technologies offered by businesses.Risk and control perceptions of privacy are two important factors that significantly influence users’ willingness to authorize their personal information.Both information sensitivity and information relevance have significant impacts on users’privacy risk perceptions,and there are significant differences in the degree to which perceived privacy policy effectiveness has an impact on perceived privacy risks that are moderated by information sensitivity.(3)The fifth chapter constructs the authorization of the personal information under the background of an evolutionary game model,refines the influence decision-making key elements of the tripartite main body,studies the interaction between the tripartite main body and inner relations,analyzes the evolution path of users,business,and government,and uses a stable equilibrium strategy.This study examines the realistic route to achieving the ideal state of orderly flow of APP user data.It uses MATLAB simulation to quantitatively analyze the evolution of each equilibrium point toward gradual stability and the dynamic effects of initial strategy changes and changes to parameters like benefit,cost,and loss on the evolution process.The findings indicate that there is a strong coupling between the three agents’ strategic decisions,and that altering one agent’s choice will impact the course of the other two actors’ strategic growth.The three-party game’s development and outcomes will be influenced by the beginning approach.The ideal state of orderly circulation of personal information in the APP market and effective development of the information industry is easier to achieve the higher the initial probability that users choose authorized information,APP suppliers implement compliance claims,and the government adopts strict supervision.The main reasons influencing users’policy choices are privacy concerns related to APP function and service expectations as well as information authorization.Users’ decisions will be encouraged to evolve in different ways and at different rates depending on the degree of income expectations and privacy concerns.For APP suppliers,based on the assumption of fixed incremental revenue,the direction and timing of their strategy evolution is determined by the regulatory fines and reputational damage that will arise from non-compliance collection.For the government,the expense of regulation will affect its initiative to embrace stringent regulation policy.This paper comprehensively and methodically demonstrates the core elements that influence APP users’ willingness to authorize personal information,expands research on user privacy decisions and multi-agent strategy selection in the context of mobile APP,and provides a useful reference for APP suppliers to standardize their operation and privacy practices,as well as for government regulatory departments to take reasonable regulatory measures.It is of practical importance to direct the orderly flow and healthy development of information throughout the entire APP ecology,and to create an ideal pattern in which the development of the digital economy and the protection of personal privacy go hand in hand.The main innovation points are as follows:(1)To make the study of privacy decision making more understandable and methodical,a panoramic framework of the study of APP users’ willingness to authorize personal information is developed.The main line of this study is the two most mainstream privacy theories,and it analyzes the influencing factors of users’ privacy decisions in detail from the perspectives of "cost-benefit" calculation and "risk-control"management at the boundary,respectively.Simultaneously,we combine the theory of personality traits,which represents users’ own factors,and the theory of agency assurance,which reflects external factors,as antecedent factors affecting users’ privacy intention with two main privacy theories,forming a "1+2+4" research structure with one overall goal,two research models,four major theories,and seventeen predictive factors,which presents and analyzes multiple factors affecting APP users’ personal information authorization.The research also reveals the full extent of correlation,mediation,and moderation among the major privacy variables.(2)The combination of statistical analysis and evolutionary game is used to process the data,which makes the research conclusion more scientific and effective.This study combines statistical analysis methods and evolutionary game methods.On the one hand,it uses a questionnaire that has been rigorously designed in terms of structure and content to widely obtain user data,and conducts empirical analysis through structural equation model to comprehensively find out the core elements that affect APP users’ privacy perception and decision-making willingness.On the other hand,the game model is built and the mathematical analysis is done in accordance with the system relationships of the three parties.Quantitative simulation analysis is then used to confirm the veracity and authenticity of the reasoning results,and the strategy adjustment and interaction process of the three parties is dynamically presented.The two data analysis techniques can complement one another and each have their own benefits.The two methods are effectively combined to produce a more thorough and convincing research conclusion regarding APP users’intentions to authorize the use of their personal information as well as the three parties’ decision-making.(3)This study offers a "micro-meso-macro" interpenetrating logic that enables the vertical correlation and horizontal amplification of APP ecological subjects’ decision-making.Through users’ willingness to make privacy and security demands at the micro level,this paper infers the significance of enterprise management and macro regulation in ensuring the stability of the APP industry.From there,it builds a theoretical model that starts from micro demands and guides meso practices and macro decisions.This paper’s "cross-layer" research not only identifies the important variables influencing user,business,and government strategy decisions,but also organically combines the three,profoundly illuminating the interpenetration and mutual constraints in the decision-making of the three subjects with limited rationality,and offering workable and efficient solutions for maximizing social benefits in the context of APP information authorization.For maximizing societal advantages in the context of APP information permission,it offers a workable and efficient option. |
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