How digital natives make their self-disclosure decisions: a cross-cultural comparison

2019 ◽  
Vol 32 (3) ◽  
pp. 538-558 ◽  
Author(s):  
Zilong Liu ◽  
Xuequn Wang ◽  
Jun Liu
Keyword(s):  
Personal Information ◽  
Digital Natives ◽  
Self Disclosure ◽  
Content Type ◽  
Privacy Concerns ◽  
Cross Cultural Comparison ◽  
Disclosure Decisions ◽  
Different Types ◽  
The Usa ◽  
Social Rewards

Purpose Digital natives have become significant users of social network sites (SNSs); therefore, their disclosed personal information can be misused by SNS providers and/or other users. The purpose of this paper is to understand how digital natives make their self-disclosure decisions on SNSs, as well as whether the concept of culture can still be relevant to digital natives. Design/methodology/approach The hypotheses were tested with survey data collected from the USA and China. Findings The results show that trust in SNSs and trust in SNS users are positively related to social rewards. Social rewards are positively related to intention to self-disclose, while privacy risk is positively related to privacy concerns. Further, culture significantly moderates the relationship between trust and social rewards. Research limitations/implications The study clarifies the effects of different types of trust on privacy in the context of SNSs. Further, the study shows the effects of culture when digital natives make self-disclosure decisions. Practical implications SNS providers also need to focus on different types of trust when operating in different cultural contexts. Further, SNS providers expanding their markets should emphasize social rewards to increase the likelihood of self-disclosure. Originality/value The results show that while culture can still be helpful to explain digital natives’ trust beliefs, digital natives have started to converge regarding their perceptions about privacy concerns and self-disclosure.

Modeling guests’ intentions to use mobile apps in hotels

2016 ◽  
Vol 28 (9) ◽  
pp. 1968-1991 ◽  
Author(s):  
Cristian Morosan ◽  
Agnes DeFranco
Keyword(s):  
Information Systems ◽  
Structural Model ◽  
Personal Information ◽  
Mobile Apps ◽  
Theoretical Perspective ◽  
Critical Factor ◽  
Structural Equations ◽  
Content Type ◽  
Privacy Concerns ◽  
The Usa

Purpose The unprecedented development of hotel-branded mobile applications (apps) has been instrumental in facilitating the rich guest–hotel interactions, thus contributing to a high personalization of services. For true personalization, guests need to provide personal information via apps. Yet, no study to date has addressed how guests develop intentions to use such apps given the current personalization and privacy challenges. Therefore, this study aims to investigate hotel guests’ intentions to use hotel apps to access personalized services. Design/methodology/approach Drawing from personalization-privacy theory, this study conceptualized perceived personalization and privacy concerns as distinct constructs while recognizing two different privacy concerns constructs: general and app-specific privacy concerns. To build a comprehensive structural model that is appropriate for explicating intentions to use hotel apps, this study incorporates consumer psychology and information systems theoretical streams that provide constructs that unequivocally capture the unique set of consumer–app interactions in highly experiential settings such as hotels (e.g. innovativeness and involvement). Using a nation-wide sample of hotel guests from the USA, the model was validated using confirmatory factor analysis and structural equations modeling. Findings The predictors explained 79 per cent of the variability in the intentions to use hotel apps to personalize hotel services. The strongest predictor of intentions was involvement, followed by app-related privacy concerns and perceived personalization. Research limitations/implications First, this study’s extended theoretical framework was well supported, as it captures relevant elements of the mobile commerce ecosystem (e.g. personalization and privacy), thus extending the classic paradigmatic approach to information systems adoption beyond system beliefs. Second, this study clarifies the distinct roles of personalization and privacy in the context of hotel apps, which has not been examined in the context of m-commerce in hospitality. Third, the study clarifies the role of involvement as the most critical factor that can influence guests’ intentions to use hotel apps when personalization options and privacy concerns exist. Practical implications This study offers hotel decision-makers a mapping of the factors, leading to use of hotel apps for purchasing personalized hotel services. Originality/value This study provides a first theoretical perspective on the hotel app utilization behaviors that have not been studied so far, but carry a strong strategic and financial significance for the hotel industry (direct distribution, brand consolidation and extensive contact with guests).

Laziness as an explanation for the privacy paradox: a longitudinal empirical investigation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jakob Wirth ◽  
Christian Maier ◽  
Sven Laumer ◽  
Tim Weitzel
Keyword(s):  
Private Information ◽  
Structural Equation ◽  
Personal Information ◽  
Past Research ◽  
Equation Modeling ◽  
Smart Devices ◽  
Self Disclosure ◽  
Content Type ◽  
Privacy Concerns ◽  
Privacy Paradox

Purpose“Smart devices think you're “too lazy” to opt out of privacy defaults” was the headline of a recent news report indicating that individuals might be too lazy to stop disclosing their private information and therefore to protect their information privacy. In current privacy research, privacy concerns and self-disclosure are central constructs regarding protecting privacy. One might assume that being concerned about protecting privacy would lead individuals to disclose less personal information. However, past research has shown that individuals continue to disclose personal information despite high privacy concerns, which is commonly referred to as the privacy paradox. This study introduces laziness as a personality trait in the privacy context, asking to what degree individual laziness influences privacy issues.Design/methodology/approachAfter conceptualizing, defining and operationalizing laziness, the authors analyzed information collected in a longitudinal empirical study and evaluated the results through structural equation modeling.FindingsThe findings show that the privacy paradox holds true, yet the level of laziness influences it. In particular, the privacy paradox applies to very lazy individuals but not to less lazy individuals.Research limitations/implicationsWith these results one can better explain the privacy paradox and self-disclosure behavior.Practical implicationsThe state might want to introduce laws that not only bring organizations to handle information in a private manner but also make it as easy as possible for individuals to protect their privacy.Originality/valueBased on a literature review, a clear research gap has been identified, filled by this research study.

AI and privacy concerns: a smart meter case study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jillian Carmody ◽  
Samir Shringarpure ◽  
Gerhard Van de Venter
Keyword(s):  
Private Information ◽  
Personal Information ◽  
Consumer Information ◽  
Data Sets ◽  
Smart Meter ◽  
Smart Meters ◽  
Content Type ◽  
Privacy Concerns ◽  
Privacy Legislation

Purpose The purpose of this paper is to demonstrate privacy concerns arising from the rapidly increasing advancements and use of artificial intelligence (AI) technology and the challenges of existing privacy regimes to ensure the on-going protection of an individual’s sensitive private information. The authors illustrate this through a case study of energy smart meters and suggest a novel combination of four solutions to strengthen privacy protection. Design/methodology/approach The authors illustrate how, through smart meter obtained energy data, home energy providers can use AI to reveal private consumer information such as households’ electrical appliances, their time and frequency of usage, including number and model of appliance. The authors show how this data can further be combined with other data to infer sensitive personal information such as lifestyle and household income due to advances in AI technologies. Findings The authors highlight data protection and privacy concerns which are not immediately obvious to consumers due to the capabilities of advanced AI technology and its ability to extract sensitive personal information when applied to large overlapping granular data sets. Social implications The authors question the adequacy of existing privacy legislation to protect sensitive inferred consumer data from AI-driven technology. To address this, the authors suggest alternative solutions. Originality/value The original value of this paper is that it illustrates new privacy issues brought about by advances in AI, failings in current privacy legislation and implementation and opens the dialog between stakeholders to protect vulnerable consumers.

Using social distancing technology in hotels: a social exchange perspective

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Cristian Morosan ◽  
Agnes DeFranco
Keyword(s):  
Social Exchange ◽  
Health Risks ◽  
Social Exchange Theory ◽  
Structural Model ◽  
Content Type ◽  
Privacy Concerns ◽  
Social Distancing ◽  
Using Data ◽  
Social Rewards

Purpose As social distancing procedures can be facilitated by various hotel technologies, the purpose of this paper is to investigate the extent to which consumers develop perceptions of value regarding the use of certain hotel technologies for social distancing in hotels. Design/methodology/approach Drawing from the social exchange theory, this study conceptualized the benefits of using technologies for social distancing, health risks, social rewards and privacy concerns as antecedents of value of using technologies for social distancing in hotels. The structural model was validated by using data from more than 1,000 nationwide US consumers. Findings Benefits and consumers’ privacy concerns of using technologies for social distancing in hotels were the strongest predictors of value. Social rewards also had a significant but relatively lower effect on value. Health risks was found to have no influence on value. Originality/value The study is the first to examine the role of technologies in mitigating the effects of coronavirus. Thus, it extends the information technology and hospitality literature by examining the role of these technologies in safeguarding individual and public health.

Prior Negative Experience, Online Privacy Concerns and Intent to Disclose Personal Information in Chinese Social Media

2015 ◽  
pp. 1053-1075
Author(s):  
Hongwei “Chris” Yang
Keyword(s):  
Social Media ◽  
Perceived Risk ◽  
Personal Information ◽  
Online Privacy ◽  
Online Information ◽  
Sensitive Information ◽  
Negative Experience ◽  
Self Disclosure ◽  
Chinese College Students ◽  
Privacy Concerns

A paper survey of 489 Chinese college students was conducted in spring, 2012 to test a conceptual model of online information disclosure in social media. It shows that young Chinese SNS users' prior negative experience of online disclosure significantly increased their online privacy concerns and their perceived risk. Their online privacy concerns undermined their trust of online companies, marketers and laws to protect privacy and elevated their perceived risk. Their trust strongly predicted their intent to disclose the lifestyle and sensitive information. Their online privacy concerns only inhibited them from disclosing sensitive information in social media. However, their prior negative experience did not directly predict their intent of self-disclosure on SNS. Implications for academia and industry are discussed.

The influence of personality traits and social networks on the self-disclosure behavior of social network site users

2016 ◽  
Vol 26 (3) ◽  
pp. 566-586 ◽  
Author(s):  
Xi Chen ◽  
Yin Pan ◽  
Bin Guo
Keyword(s):  
Social Capital ◽  
Social Networks ◽  
Social Network ◽  
Personality Traits ◽  
Personal Information ◽  
The Self ◽  
Social Network Site ◽  
Self Disclosure ◽  
Content Type ◽  
Network Site

Purpose – The purpose of this paper is to determine the influence and interaction of social networks and personality traits on the self-disclosure behavior of social network site (SNS) users. According to social capital theory and the Big Five personality model, the authors hypothesized that social capital factors would affect the accuracy and amount of self-disclosure behavior and that personality traits would moderate this effect. Design/methodology/approach – A survey was conducted to collect data from 207 SNS users. The questionnaire was administered in university classrooms and libraries and via e-mail. The measurement model and structural model were examined by using LISREL 8.8 and SmartPLS 2.0. Findings – Based on the path analysis, the authors identified several interesting patterns to explain self-disclosure behavior on SNSs. First, the centrality of SNS users has a positive effect on their amount of self-disclosure. Moreover, people who are more extroverted disclose personal information that is more accurate with the level of the cognitive dimension held constant and disclose a greater amount of personal information with the level of the structural dimension held constant. From a practical perspective, the results may provide useful insight for companies operating SNSs. Originality/value – This study analyzed the influence of social capital factors on SNS users’ self-disclosure, as well as the interactions between personality and social capital factors. Specifically, the authors examined six important variables of social capital divided into three dimensions. This research complements current research on SNSs by focusing on SNS users’ motivation to disclose self-related information in addition to information sharing.

Why people need privacy? The role of privacy fatigue in app users' intention to disclose privacy: based on personality traits

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jie Tang ◽  
Umair Akram ◽  
Wenjing Shi
Keyword(s):  
Personality Traits ◽  
Information Disclosure ◽  
Personal Information ◽  
Mobile Apps ◽  
Equation Modeling ◽  
Content Type ◽  
Privacy Concerns ◽  
Positive Effects ◽  
Novel Concept ◽  
The Impact

PurposeMobile Applications (App) privacy has become a prominent social problem. Compared with privacy concerns, this study examines a relatively novel concept of privacy fatigue and explores its effect on the users’ intention to disclose their personal information via mobile Apps. In addition, the personality traits are proposed as antecedents that will induce the personal perception of privacy fatigue and privacy concerns differently.Design/methodology/approachData were collected from 426 respondents. Structure equation modeling was used to test the hypotheses.FindingsThe findings describe that App users’ intention toward personal information disclosure is determined by privacy fatigue and privacy concerns, but the former has a greater impact. With minor exceptions, the two factors are also influenced by different personality traits. Specifically, neuroticism has positive effects on privacy fatigue, but agreeableness and extraversion have presented the opposite results on the two variables.Practical implicationsThis research is very scarce to examine the joint effects of privacy fatigue, privacy concerns and personality traits on App users’ disclosing intention. In doing so, these results will be of benefit to App providers and platform managers and can be the basis for a variety of follow-up studies.Originality/valueWhile previous research just focuses on privacy concerns, this study explores the critical roles of privacy fatigue and opens up a new avenue of emotion-attitude analysis that can further increase the specificity and richness of users’ privacy research. Additionally, implications for personality traits as antecedents in the impact of App users’ privacy emotions and attitudes are discussed.

scholarly journals Self-disclosure in social networking sites

2015 ◽  
Vol 25 (2) ◽  
pp. 279-299 ◽  
Author(s):  
Christy Cheung ◽  
Zach W. Y. Lee ◽  
Tommy K. H. Chan
Keyword(s):  
Social Influence ◽  
Social Networking ◽  
Social Exchange ◽  
Social Networking Sites ◽  
Service Providers ◽  
Personal Information ◽  
Integrated Model ◽  
Perceived Benefits ◽  
Self Disclosure ◽  
Content Type

Purpose – The purpose of this paper is to examine the relative impacts of perceived cost, perceived benefits, and social influence on self-disclosure behaviors in social networking sites under an integrated theoretical framework. Design/methodology/approach – Building upon social exchange theory and privacy calculus theory, an integrated model was developed. The model was tested empirically using a sample of 405 social networking site’s users. Users were required to complete a survey regarding self-disclosure behaviors in Facebook. Findings – The results indicate that social influence is the factor which exhibits the strongest effect on self-disclosure in social networking sites, followed by perceived benefits. Surprisingly, perceived privacy risk does not have any significant impact on self-disclosure. Research limitations/implications – The results inform researchers about the importance to incorporate social influence factors and cultural factors into future online self-disclosure study. Practical implications – The results suggest that users focus on the benefits as well as social influence when they decide to reveal personal information in social networking sites, but pay less attention to the potential privacy risks. Educators are advised to launch educational programs to raise students’ awareness to the potential risks of self-disclosure in social networking sites. Service providers of social networking sites are encouraged to provide intuitive privacy indices showing users the levels of privacy protection. Originality/value – This paper is one of the first to develop and empirically tests an integrated model of self-disclosure in social networking sites.

Mobile payments adoption by US consumers: an extended TAM

2017 ◽  
Vol 45 (6) ◽  
pp. 626-640 ◽  
Author(s):  
Ainsworth Anthony Bailey ◽  
Iryna Pentina ◽  
Aditya Shankar Mishra ◽  
Mohammed Slim Ben Mimoun
Keyword(s):  
Self Efficacy ◽  
Online Survey ◽  
New Technology ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Convenience Sample ◽  
Content Type ◽  
Privacy Concerns ◽  
The Usa ◽  
Technology Anxiety

Purpose The purpose of this paper is to incorporate mobile payment (MP) self-efficacy, new technology anxiety, and MP privacy concerns into the basic TAM to explore MP adoption, particularly tap-and-go payment, among US consumers. Design/methodology/approach Data were collected through an online survey conducted among students at a Midwestern University in the USA. A total of 254 participants provided 240 useable responses. Findings MP self-efficacy significantly impacts perceived ease of use (PEOUMP) and perceived usefulness of MP (PUMP). These in turn impact MP attitude, which affects intention to use MP. Privacy concerns also impact attitude towards MP and MP use intention. New technology anxiety impacts PEOUMP, but not PUMP. Research limitations/implications The study uses a convenience sample of young US consumers, which could limit the generalisability of the results. The study is also limited to tap-and-go payment. Practical implications US retailers have information on some of the factors that encourage MP adoption. Retailers need to address self-efficacy concerns, MP privacy concerns, and consumers’ perceptions of usefulness of the technology. Originality/value There has been little research on factors impacting tap-and-go payment adoption in the USA. The study highlights the roles of self-efficacy and privacy concerns. It focusses on tap-and-go payment, since this technology can enhance consumers’ retail experience.

What drives internet users’ willingness to provide personal information?

2018 ◽  
Vol 42 (6) ◽  
pp. 923-939 ◽  
Author(s):  
Ching-Hsuan Yeh ◽  
Yi-Shun Wang ◽  
Shin-Jeng Lin ◽  
Timmy H. Tseng ◽  
Hsin-Hui Lin ◽  
...  
Keyword(s):  
Risk Taking ◽  
Personal Information ◽  
Information Privacy ◽  
Extrinsic Rewards ◽  
Content Type ◽  
Privacy Concerns ◽  
Internet Users ◽  
Information Privacy Concerns ◽  
The Relationship ◽  
Least Squares Approach

Purpose Considering that users’ information privacy concerns may affect the development of e-commerce, the purpose of this paper is to explore what drives internet users’ willingness to provide personal information; further, the paper examines how extrinsic rewards moderate the relationship between users’ information privacy concerns and willingness to provide personal information. Design/methodology/approach Data collected from 345 valid internet users in the context of electronic commerce were analyzed using the partial least squares approach. Findings The result showed that agreeableness, risk-taking propensity and experience of privacy invasion were three main antecedents of information privacy concerns among the seven individual factors. Additionally, information privacy concerns did not significantly affect users’ willingness to provide personal information in the privacy calculation mechanism; however, extrinsic rewards directly affected users’ disclosure intention. The authors found that extrinsic rewards had not moderated the relationship between users’ information privacy concerns and their willingness to provide personal information. Originality/value This study is an exploratory effort to develop and validate a model for explaining why internet users were willing to provide personal information. The results of this study are helpful to researchers in developing theories of information privacy concerns and to practitioners in promoting internet users’ willingness to provide personal information in an e-commerce context.

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