Open Access
Open access
Data and Information Management, volume 5, issue 1, pages 195-207

Research on Influencing Factors of Personal Information Disclosure Intention of Social Media in China

Publication typeJournal Article
Publication date2021-01-01
scimago Q2
SJR0.432
CiteScore3.7
Impact factor
ISSN25439251
Water Science and Technology
Geology
Ocean Engineering
Abstract
The disclosure of personal information by users is very important for social media, in order to balance privacy protection and personalized service. This article probes into the factors influencing users’ disclosure intention. Based on the privacy calculus theory and theory of planned behavior, the study constructs an influencing factor model of social media personal information disclosure intention. Then an extensive survey of social media users is conducted through questionnaire, and the hypothetical model is verified using structural equation model, and finally the relationship between various influencing factors and personal information disclosure intentions is obtained. The results show that the perceived benefits and subjective norm are related to personal information disclosure intentions, and privacy view is associated with perceived risk. Finally, the study provides new ideas for social media services and user privacy protection, such as creating a secure social media environment, increasing valuable social services, reducing users’ risk perception and making information processing open and transparent.
Anic I., Budak J., Rajh E., Recher V., Skare V., Skrinjaric B.
Online Information Review scimago Q1 wos Q1
2019-09-09 citations by CoLab: 22 Abstract  
PurposeThe purpose of this paper is to investigate the relationship between individual and societal determinants of online privacy concern (OPC) and behavioral intention of internet users. The study also aims to assess the degree of reciprocity between consumers’ perceived benefits of using the internet and their OPC in the context of their decision-making process in the online environment.Design/methodology/approachThe study proposes comprehensive model for analysis of antecedents and consequences of OPC. Empirical analysis is performed using the PLS–SEM approach on a representative sample of 2,060 internet users.FindingsThe findings show that computer anxiety and perceived quality of regulatory framework are significant antecedents of OPC, while traditional values and inclinations toward security, family and social order; and social trust are not. Furthermore, the study reveals that perceived benefits of using the internet are the predominant factor explaining the intention to share personal information and adopt new technologies, while OPC dominates in explanation of protective behavior.Research limitations/implicationsAlthough the authors tested an extended model, there might be other individual characteristics driving the level of OPC. This research covers just one country and further replications should be conducted to confirm findings in diverse socio-economic contexts. It is impossible to capture the real behavior with survey data, and experimental studies may be needed to verify the research model.Practical implicationsManagers should work toward maximizing perceived benefits of consumers’ online interaction with the company, while at the same time being transparent about the gathered data and their intended purpose. Considering the latter, companies should clearly communicate their compliance with the emerging new data protection regulation.Originality/valueNew extended model is developed and empirically tested, consolidating current different streams of research into one conceptual model.
Al-Jabri I.M., Eid M.I., Abed A.
2019-08-26 citations by CoLab: 15 Abstract  
Purpose Customer privacy and security are major concerns. Online firms worldwide collect customer data for various reasons. This study aims to investigate factors that motivate and hinder a customer’s willingness to disclose personal information (WTD) to online firms on e-commerce websites. Design/methodology/approach Based on an extensive literature review, three sets of factors have been identified. These sets of factors are privacy concern, perceived disclosure benefits and privacy assurances. It is hypothesized that privacy concerns negatively affect the disclosure of personal information, while the perceived benefits of disclosure have positive effects. Privacy assurances would positively affect information disclosure and attenuate the negative effect of privacy concerns on the disclosure of personal information. The authors gathered data from 253 online customers in Saudi Arabia. Findings The results indicate that perceived disclosure benefits and privacy concerns have a significant positive and negative relationship, respectively, with WTD online. Privacy assurances had neither a direct nor a moderating effect on information disclosure. Research limitations/implications The findings will inform online firms about the factors that prevent or motivate customers to disclose personal information. Originality/value The effect of privacy concerns and benefits on personal information disclosure are not fully understood in Saudi Arabia. This study reveals more insights into the specific factors that make online customers reluctant or motivated to disclose their personal information.
Bergström A.
Computers in Human Behavior scimago Q1 wos Q1
2015-12-01 citations by CoLab: 101 Abstract  
Privacy concerns are diverse and depend on the applications in question.Privacy concerns are more common when payments are involved than for emailing or information searching.Trust in other people has the strongest explanatory power for privacy concerns. Questions regarding personal privacy are becoming increasingly relevant, and the discussion continuously arises regarding what digital tracks we leave. Intrusive use and manipulation of personal information not only affect people's behaviour, but also they could have important implications for political and civic society. Previous research has relied on convenience samples and has often focused on one or only a few areas of use. The presented study, based on a probability sample, gives an overall picture of how privacy concerns are perceived in different online contexts and how socio-demography, internet experience, trust, and political orientation contribute to the understanding of privacy concerns in different settings. The results clearly point to privacy concerns as being very diverse and dependent on the applications in question. All dimensions that are used to explain privacy concerns are partly supported in the study. But their explanatory powers differ and not all areas of concern are affected by the same explanatory factors. Trust in other people is the single most important factor explaining privacy concerns when using digital media and applications. The more people trust others, the less concern they have for misuse of personal information.
Kock N.
2015-07-01 citations by CoLab: 4277 Abstract  
The author discusses common method bias in the context of structural equation modeling employing the partial least squares method (PLS-SEM). Two datasets were created through a Monte Carlo simulation to illustrate the discussion: one contaminated by common method bias, and the other not contaminated. A practical approach is presented for the identification of common method bias based on variance inflation factors generated via a full collinearity test. The author's discussion builds on an illustrative model in the field of e-collaboration, with outputs generated by the software WarpPLS. They demonstrate that the full collinearity test is successful in the identification of common method bias with a model that nevertheless passes standard convergent and discriminant validity assessment criteria based on a confirmation factor analysis.
Nemec Zlatolas L., Welzer T., Heričko M., Hölbl M.
Computers in Human Behavior scimago Q1 wos Q1
2015-04-01 citations by CoLab: 156 Abstract  
Social networking sites privacy issues and self-disclosure are examined.A research model of privacy issues and self-disclosure is built.Structural equations modeling is used to assess the model fit.Path analysis is done to analyze hypothesis whereas 11 out of 14 are accepted.Final model shows privacy and its shaping of self-disclosure in Facebook. In recent years, social networking sites have spread rapidly, raising new issues in terms of privacy and self-disclosure online. For a better understanding of how privacy issues determine self-disclosure, a model which includes privacy awareness, privacy social norms, privacy policy, privacy control, privacy value, privacy concerns and self-disclosure was built. A total of 661 respondents participated in an online survey and a structural equation modeling was used to evaluate the model. The findings indicated a significant relationship between privacy value/privacy concerns and self-disclosure, privacy awareness and privacy concerns/self-disclosure, privacy social norms and privacy value/self-disclosure, privacy policy and privacy value/privacy concerns/self-disclosure, privacy control and privacy value/privacy concerns. The model from the study should contribute new knowledge concerning privacy issues and their shaping of self-disclosure on social networking sites. It could also help networking sites service providers understand how to encourage users to disclose more information.
Varnali K., Toker A.
Social Behavior and Personality scimago Q3 wos Q4
2015-02-07 citations by CoLab: 41 Abstract  
Our aim was to contribute to the understanding of self-disclosure behavior on social networking sites (SNS). Participants (N = 1,294) completed online surveys comprising measures of willingness to disclose personal information on SNS, self-esteem, SNS affinity, self-disclosure, honesty of self-disclosure, subjective norm, self-monitoring skills, and public self-consciousness. Our findings suggest that self-disclosure mediates the impact of communication-based personality characteristics on the use of SNS, and that subjective norm and SNS affinity also have significant independent effects.
Sharma S., Crossler R.E.
2014-09-01 citations by CoLab: 126 Abstract  
The buying and selling of goods and services are no longer limited to a general website or a physical store as social networks, such as Facebook or Pinterest, are heavily focusing on social commerce. Prior studies have analyzed impact of trust and culture on social commerce, design and interface aspects of it, and intention to use social commerce by general people. Our study is informed by the literature on information disclosure intention, and Communication Privacy Management theory and is motivated by the fundamental premise that intention to self-disclose in social commerce is affected by perceived ownership of information, privacy apathy, the risks and benefits of disclosure and fairness of information exchange. We analyzed data collected from 252 samples using the scenario method. The results show that shoppers’ information disclosure intention is driven by the fairness of information exchange, privacy benefits and privacy apathy.
Hollenbaugh E.E., Ferris A.L.
Computers in Human Behavior scimago Q1 wos Q1
2014-01-01 citations by CoLab: 265 Abstract  
• We surveyed 301 Facebook users to explore predictors of self-disclosive behavior. • Uses and gratifications theory was a useful model to explain self-disclosure. • Motives and Big Five personality traits predicted disclosive behaviors. • Facebookers who seek attention, and existing and new relationships were disclosive. • Surprisingly, women and men did not differ in self-disclosive behavior. Facebook has been shown to be the most popular social network in the United States. Facebook not only has implications in the online world, but face-to-face connections are also affected by this medium. This study explores the uses of Facebook for self-disclosure behavior utilizing the uses and gratifications perspective. Using a convenience sample of Facebook users, this study examines individual and sociological factors as well as Facebook motives to discover the impact on depth, breadth, and amount of user self-disclosure. Path analyses showed that the Big Five personality factors, self-esteem, social cohesion, and motives contribute to self-disclosure dimensions. However, demographic variables did not impact disclosiveness. Limitations are discussed and directions for future research are proposed.
Zhang R., Chen J.Q., Lee C.J.
2013-06-01 citations by CoLab: 52 Abstract  
M-commerce (mobile commerce) has been gaining popularity as the smartphones proliferated and the high speed mobile data networks become increasingly ubiquitous in the recent years. This study attempts to identify the unique marketing context and features of m-commerce as compared to e-commerce, and to explore how consumers' demographic differences may affect their concerns for information privacy (CFIP) in the context of m-commerce. The APCO model (Antecedents → Privacy Concerns → Outcomes) is used as a framework to help derive our research model. Two perspectives about m-commerce are explored. The m-commerce consumers' demographic differences and their concerns over privacy are analyzed, based on a survey of 278 mobile phone users in U.S. It has been found that the consumers' demographic differences have varying degrees of impact on their concerns for information privacy in the context of m-commerce. These varying degrees of privacy concerns need to be addressed to ensure the healthy growth in m-commerce.
Liu C., Ang R.P., Lwin M.O.
Journal of Adolescence scimago Q1 wos Q2
2013-05-14 citations by CoLab: 74 Abstract  
The current study aims to understand the factors that influence adolescents' disclosure of personally identifiable information (PII) on social networking sites (SNSs). A survey was conducted among 780 adolescent participants (between 13 and 18) who were Facebook users. Structural equation modeling was used for analyzing the data and obtaining an overarching model that include cognitive, personality, and social factors that influence adolescents' PII disclosure. Results showed privacy concern as the cognitive factor reduces adolescents' PII disclosure and it serves as a potential mediator for personality and social factors. Amongst personality factors, narcissism was found to directly increase PII disclosure, and social anxiety indirectly decreases PII disclosure by increasing privacy concern. Amongst social factors, active parental mediation decreases PII disclosure directly and indirectly by increasing privacy concern. Restrictive parental mediation decreases PII disclosure only indirectly by increasing privacy concern. Implications of the findings to parents, educators, and policy makers were discussed.
Xu F., Michael K., Chen X.
Electronic Commerce Research scimago Q1 wos Q2
2013-03-26 citations by CoLab: 129 Abstract  
The self-disclosure of personal information by users on social network sites (SNSs) play a vital role in the self-sustainability of online social networking service provider platforms. However, people’s levels of privacy concern increases as a direct result of unauthorized procurement and exploitation of personal information from the use of social networks which in turn discourages users from disclosing their information or encourages users to submit fake information online. After a review of the Theory of Planned Behavior (TPB) and the privacy calculus model, an integrated model is proposed to explain privacy disclosure behaviors on social network sites. Thus, the aim of this paper is to find the key factors affecting users’ self-disclosure of personal information. Using privacy calculus, the perceived benefit was combined into the Theory of Planned Behavior, and after some modifications, an integrated model was prescribed specifically for the context of social network sites. The constructs of information sensitivity and perceived benefit were redefined after reviewing the literature. Through a study on the constructs of privacy concern and self-disclosure, this article aims at reducing the levels of privacy concern, while sustaining online transactions and further stimulating the development of social network sites.
Shiau W., Luo M.M.
Computers in Human Behavior scimago Q1 wos Q1
2012-11-01 citations by CoLab: 302 Abstract  
► We model the use experience of online group buying users. ► We examine the applicability of social exchange theory (SET) in online context. ► The results suggest reciprocity, trust, satisfaction, and vendor creativity predict online group buying intention. ► Consumer satisfaction with online group buying was predicted by trust and reciprocity. ► The applicability of SET is attested in online context. This study investigates factors that affect consumer continuous use intention toward online group buying and the degree that reciprocity and reputation of social exchange, trust, and vendor creativity affect consumer satisfaction and intention toward online purchasing. Data from 215 valid samples was obtained using an online survey. The research model is assessed using partial least squares (PLS) analysis. The results show that the intention to engage in online group buying is predicted collectively by consumer satisfaction, trust, and seller creativity. Consumer satisfaction with online group buying is predicted primarily by trust, followed by consumer reciprocity. The proposed research model explains 67.7% of variance for satisfaction and 39.7% of variance for intention to engage in online group buying. The results suggest that reciprocity, trust, satisfaction, and seller creativity provide considerable explanatory power for intention to engage in online group buying behavior.
Heirman W., Walrave M., Ponnet K.
2012-10-31 citations by CoLab: 51 Abstract  
This study adopts a global theoretical framework to predict adolescents' disclosure of personal information in exchange for incentives offered by commercial Websites. The study postulates and tests the validity of a model based on the theory of planned behavior (TPB), including antecedent factors of attitude and perceived behavioral control (PBC). A survey was conducted among 1,042 respondents. Results from SEM analyses show that the hypothesized model fits the empirical data well. The model accounts for 61.9 percent of the variance in adolescents' intention to disclose and 43.7 percent of the variance in self-reported disclosure. Perceived social pressure exerted by significant others (subjective norm) is the most important TPB factor in predicting intention to disclose personal information in exchange for incentives. This finding suggests that in discussions of adolescents' information privacy, the importance of social factors outweighs the individually oriented TPB factors of attitude and PBC. Moreover, privacy concern and trust propensity are significant predictors of respondents' attitudes toward online disclosure in exchange for commercial incentives, whereas the frequency of Internet use significantly affects their level of PBC.
Zhao L., Lu Y., Gupta S.
2012-07-06 citations by CoLab: 176 Abstract  
Although location-based social network (LBSN) services have developed rapidly in recent years, the reasons why people disclose location-related information under this environment have not been adequately investigated. This study builds a privacy calculus model to investigate the factors that influence LBSN users' intention to disclose location-related information in China. In addition, this study applies justice theory to investigate the role of privacy intervention approaches used by LBSN Web sites in enhancing users' perception of justice, including incentives provision, interaction promotion, privacy control, and privacy policy. Model testing using structural equation modeling reveals that perceived cost (users' privacy concerns) and perceived benefits (personalization and connectedness) influence intention to disclose location-related information. Meanwhile, providing incentives and promoting interaction enhance, respectively, personalization and connectedness. Privacy control and privacy policies both help in reducing privacy concerns. We also find that individuals' awareness of Internet privacy legislation negatively influences privacy concerns, whereas previous privacy invasions do not. Finally, we find that personal innovativeness significantly influences intention to disclose location-related information. This study not only extends the privacy research on social networking sites under mobile environments but also provides practical implications for service providers and policy makers to develop better LBSNs.
Guo B., Sun X., Jiang Z., Xu Y.
2024-09-25 citations by CoLab: 0 Abstract  
PurposeAmidst the growing emphasis on privacy protection, this study aims to investigate how online interaction introduced in Lead Generation Ads (LGAs) affects consumers' Self-Disclosure Intention (SDI), particularly in the context of the Chinese advertising market.Design/methodology/approachThis research employs two scenario-based online surveys to analyse in depth the impact of LGAs on consumers' SDI. The first study collects valid feedback from 220 consumers through an online questionnaire to assess the direct effect of perceived interactivity on SDI. The second study, using an experimental design with a sample of 265 participants, further explores the mediating roles of perceived control and perceived vulnerability in the relationship between perceived interactivity and SDI and examines the moderating effect of privacy invasion experience (PIE).FindingsThis study reveals the significant and positive influence of perceived interactivity on SDI, with perceived control acting as a mediator that enhances this effect. Conversely, perceived vulnerability weakens the positive impact of perceived interactivity on SDI. Additionally, we explore the moderating role of PIE and find that it significantly influences the relationship between perceived interactivity and SDI. These findings underscore the importance of considering consumer privacy sensitivity, particularly in the design of interactive marketing strategies and within highly interactive advertising environments.Research limitations/implicationsOur research uncovers consumer privacy attitudes and behaviours in the Chinese market, providing insights into its unique dynamics of privacy and information disclosure. However, the geographical and cultural specificity of our study may limit its generalizability. Future studies should expand into various cultural and market contexts, considering the impact of digital technologies on consumer interactions and information disclosure, thereby enhancing the depth and applicability of global marketing strategies.Practical implicationsAdvertising platforms should explore online interactive communication methods to enhance consumers' perceived interactions and alleviate privacy concerns. Also, platforms should be designed with system security in mind to prevent the leakage and misuse of consumer data, thus increasing consumers' SDI.Social implicationsThe study provides insights for marketers on designing more effective and privacy-sensitive online advertising strategies in the Chinese market. Understanding the factors influencing consumers’ willingness to share personal information can lead to more effective engagement in digital marketing campaigns.Originality/valueBy integrating interactivity theory with privacy computing theory, this research provides a new perspective on the role of online interaction in consumer privacy protection and information disclosure decisions. The findings not only enrich the theoretical frameworks of interactive marketing and privacy protection but also offer empirical support for marketing practitioners in regard to designing interactive advertising strategies, especially balancing consumer privacy protection with the enhancement of shopping intentions.
Kante M., Michel B.
2023-05-01 citations by CoLab: 6 Abstract  
Structural equation modelling (SEM) is a statistical technique used in the field of Information Systems amongst others. The technique has been paid attention thanks to its flexibility and predictive power. However, there is a paucity of guidelines in the application of the technique in the field of Behavioural Information Security. Hence, this paper aims to provide a comprehensive guide of using PLS-SEM in disclosure and privacy studies on Social Network Sites (SNSs). Data has been gathered using papers (n=21) published between 2006 and 2022 from scholarly databases such as Google Scholar, Association for Information Systems eLibrary (AISeL), IEEE Xplore and Science Direct. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA 2020) was used to analyse and synthesize the status of the field. Our systematic review covers data characteristics, reasons for using PLS-SEM, the evaluation of measurement models, the evaluation of the structural model and reporting best practices. The review proposed guidelines for the use of PLS-SEM in the discipline of Behavioural Information Security with a focus on disclosure and privacy on SNSs studies and other fields as well.
Van Binh T., Minh D.T., Linh L.T., Van Nhan T.
2023-03-27 citations by CoLab: 3 Abstract  
Along with the development of social networking sites, sharing location is becoming mainstream, offering many opportunities and promoting sustainable business performance of firm. Based on a survey of 433 Facebook users and the application of quantitative method, the paper found that the privacy concern substantially influences the perceived risk of location sharing. In addition, tendency is witnessed on trust in the social networking site providers and members. Also, impression management and incentive provision are strongly involved in the perceived benefits of location information disclosure intention. Both perceived risks and perceived benefits illustrate distinctive effects on sharing users’ location. The impact of subjective norms on sharing information related to a users’ location and observing the potential influence of culture, played as moderator. The finding also confirms subjective norms positively impact location information disclosure intention, while the moderating of culture does not play a contribution role.
Shabaz M., Zhang Y., Beram S.M.
2023-03-01 citations by CoLab: 1 Abstract  
Aim: In order to explore the study on information leakage tracking algorithms in online social networks, solve the problem of information leakage in the current online social network. a deterministic leaker tracking algorithm based on digital fingerprints is proposed Background: : First, the basic working principle of the algorithm is that the platform uses plug-ins to embed a unique user-identifying information before users try to obtain digital media such as images and videos shared by others on the platform. Objective: Secondly, because the scale of users in social networks is extremely large and dynamic, while ensuring the uniqueness of digital fingerprints, it is also necessary to ensure the coding efficiency and scalability of digital fingerprint code words. Methods: Simulation experiments show that: 10 experiments are performed on 10,000 to 100,000 nodes, the Hamming distance threshold d is set to be 3, and the length of the hash code and the binary random sequence code are both 64 bits. Results: Compared with the traditional linear search, the proposed digital fingerprint fast detection scheme has better performance Conclusion: It is proved that an index table based on hash code and user ID is established and combines with community structure, to improve the detection efficiency of digital fingerprints
Zheng J., Chen J.
Complexity scimago Q1 wos Q2 Open Access
2021-12-15 citations by CoLab: 16 PDF Abstract  
To solve the current privacy leakage problems of cloud storage services, research on users’ payment intention for cloud storage services with privacy protection is extremely important for improving the sustainable development of cloud storage services. An evolutionary game model between cloud storage users and providers that considers privacy is constructed. Then, the model’s evolutionary stability strategies via solving the replication dynamic equations are analyzed. Finally, simulation experiments are carried out for verifying and demonstrating the influence of model parameters. The results show that the evolutionary stable strategies are mainly affected by the privacy protection profit growth coefficient of both parties, input costs, free-riding gains, and other factors. If the profit growth coefficient is very small, users will not choose to pay and providers will not choose to actively protect user information. As the profit growth coefficient increases, both parties will promote the development of privacy protection with a higher probability. The results are beneficial for cloud storage providers to increase the number of paid users and thus to achieve the sustainable development of cloud storage service.

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