The role of perceived information practices on consumers’ intention to authorise secondary use of personal data

We are living in an era where data lead to opportunities, especially customer data. According to privacy laws, however, without customers’ authorisation, organisations face many limitations in using identifiable information for secondary purposes. Consequently, organisations are missing out on many potential business opportunities to capitalise on customer data. Privacy concerns have become the biggest roadblock to gain customer consent because of the potential risks associated with the use of personal information. This situation underscores the importance of devising effective information practices and strategies in dealing with the use of customer data. Privacy literature suggests that information practices may influence individuals’ intentions to participate in situations requiring the collection and use of personal data. Yet, existing research has not systematically analysed the role of these strategies in influencing intention. Also, previous studies focus primarily on the disclosure of personal data. Issues surrounding ‘authorisation of personal data for secondary use’ remain unexplored. The purpose of our study is to examine the role of information practices on intention to authorise secondary use of personal data. The results show that privacy concerns and trusting beliefs significantly affect individual perceptions of information practices. Perception of information practices in turn exerts significant effect on intention to authorise secondary use of personal data. Both theoretical and managerial implications of the results are discussed.     

The Impact of Privacy Seal on Users’ Perception in Network Transactions

In the age of big data, the issue of online privacy has attracted much attention from all sectors. The introduction and establishment of an evaluation system for the privacy agreement based on a third party, together with the establishment of a safer internet transaction environment, can help to establish mutual trust between users and the platform. With the research background links to the online trading platform, this article investigates how the privacy seal which is provided by the third-party evaluation organization influences and addresses trust-awareness and privacy concerns of users, as well as exposing information and purchasing data. According to this investigation, the application of a privacy seal not only increases the trust-awareness of the users, but can also encourage the intention to disclose information and engage in a transaction. However, it might not totally alleviate the users’ privacy concerns. The results of our research and practical application indicate that the promotion and guarantee of the independence and expertise of the third-party evaluating organization, the effective supervision of privacy policy implementation by the online trading platform, and measures that protect the privacy of the users, all play a vital role in establishing an effective privacy agreement evaluation system.     

Interplay between trust,information privacy concerns and behavioural intention of users on online social networks

Trust and privacy features of websites have evolved as an important concern for any businesses or interactions, particularly in online networks. The study investigates the relationship between trust, privacy concerns and behavioural intention of users on the social network. The behavioural intention of users on the online social network (OSN) is captured by intention to disclose information and intention to interact with others in OSN. The study was conducted on a sample of 457 active users from one of the major social networking website, Facebook. Partial least squares based structural equation modelling was used for analysing the results. The findings of the study reveal that intention to disclose information mediates the relationship between trust in the website and the intention to interact with others. Another important finding of the study indicates that prior positive experience with the website significantly impacts the trust in website, and the trust in website also plays a crucial role while determining the information privacy concerns in the OSN.     

Privacy Preserving Visualization: A Study on Event Sequence Data

The inconceivable ability and common practice to collect personal data as well as the power of data‐driven approaches to businesses, services and security nowadays also introduce significant privacy issues. There have been extensive studies on addressing privacy preserving problems in the data mining community but relatively few have provided supervised control over the anonymization process. Preserving both the value and privacy of the data is largely a non‐trivial task. We present the design and evaluation of a visual interface that assists users in employing commonly used data anonymization techniques for making privacy preserving visualizations. Specifically, we focus on event sequence data due to its vulnerability to privacy concerns. Our interface is designed for data owners to examine potential privacy issues, obfuscate information as suggested by the algorithm and fine‐tune the results per their discretion. Multiple use case scenarios demonstrate the utility of our design. A user study similarly investigates the effectiveness of the privacy preserving strategies. Our results show that using a visual‐based interface is effective for identifying potential privacy issues, for revealing underlying anonymization processes, and for allowing users to balance between data utility and privacy.     

Can privacy concerns for insurance of connected cars be compensated?

Internet-of-things technologies enable service providers such as insurance companies to collect vast amounts of privacy-sensitive data on car drivers. This paper studies whether and how privacy concerns of car owners can be compensated by offering monetary benefits. We study the case of usage based car insurance services for which the insurance fee is adapted to measured mileage and driving behaviour. A conjoint experiment shows that consumers prefer their current insurance products to usage based car insurance. However, when offered a minor financial compensation, they are willing to give up their privacy to car insurers. Consumers find privacy of behaviour and action more valuable than privacy of location and space. The study is a first to compare different forms of privacy in the acceptance of connected car services. Hereby, we contribute to more fine-grained understanding of privacy concerns in the acceptance of digital services, which will become more important in the upcoming Internet-of-things era.     

Health information privacy concerns,antecedents, and information disclosure intention in online health communities

This study explores the antecedents and consequences of health information privacy concerns in online health communities by integrating the dual calculus and protection motivation theories. On the basis of survey data from 337 users, health information privacy concerns, together with informational and emotional support, significantly influence personal health information (PHI) disclosure intention. Privacy concerns are negatively influenced by two coping appraisals (i.e., response efficacy and self-efficacy) and positively affected by two threat appraisals (i.e., perceived vulnerability and perceived severity). The perceived health status differentially moderates the effects of privacy concerns and informational support on the PHI disclosure intention.     

Privacy in targeted advertising on mobile devices: a survey

Targeted advertising has transformed the marketing landscape for a wide variety of businesses, by creating new opportunities for advertisers to reach prospective customers by delivering personalised ads, using an infrastructure of a number of intermediary entities and technologies. The advertising and analytics companies collect, aggregate, process, and trade a vast amount of users’ personal data, which has prompted serious privacy concerns among both individuals and organisations. This article presents a comprehensive survey of the privacy risks and proposed solutions for targeted advertising in a mobile environment. We outline details of the information flow between the advertising platform and ad/analytics networks, the profiling process, the measurement analysis of targeted advertising based on user’s interests and profiling context, and the ads delivery process, for both in-app and in-browser targeted ads; we also include an overview of data sharing and tracking technologies. We discuss challenges in preserving the mobile user’s privacy that include threats related to private information extraction and exchange among various advertising entities, privacy threats from third-party tracking, re-identification of private information and associated privacy risks. Subsequently, we present various techniques for preserving user privacy and a comprehensive analysis of the proposals based on such techniques; we compare the proposals based on the underlying architectures, privacy mechanisms, and deployment scenarios. Finally, we discuss the potential research challenges and open research issues.

     

The influence of user affect in online information disclosure

Personal consumer data is the fuel for information driven programs that may differentiate a firm from its competitors and create strategic advantages. However, a tension exists between the user’s desire to protect personal information and the needs of online businesses for consumer data that drive customer relationship and business intelligence applications. This study explores the roles of positive and negative affect on users’ trust and privacy beliefs that relate to the online disclosure of personal information. A model is tested using the responses of 301 Internet users who visited one of two commercial websites. The results indicate that positive affect has a significant effect on users’ website trust and privacy beliefs that motivate online information disclosure and this effect is more pronounced for users with high Internet security concerns. The idea that positive mood-inducing website features can motivate user behavior has the potential to guide the development of websites for effective information disclosure and data collection.     

Online self-disclosure: The privacy paradox explained as a temporally discounted balance between concerns and rewards

Technological innovations are increasingly helping people expand their social capital through online networks by offering new opportunities for sharing personal information. Online social networks are perceived to provide individuals new benefits and have led to a surge of personal data uploaded, stored, and shared. While privacy concerns are a major issue for many users of social networking sites, studies have shown that their information disclosing behavior does not align with their concerns. This gap between behavior and concern is called the privacy paradox. Several theories have been explored to explain this, but with inconsistent and incomplete results. This study investigates the paradox using a construal level theory lens. We show how a privacy breach, not yet experienced and psychologically distant, has less weight in everyday choices than more concrete and psychologically-near social networking activities and discuss the implications for research and practice.     

CONTROLLING THE THREAT TO PERSONAL PRIVACY Corporate Policies Must Be Created

Information technology makes it easier than ever to collect, store, and disseminate personal information, then use it to carry out business and political decisions. Federal legislation limits corporate and government manipulation of personal data, and private companies are finding that they must do the same or risk lawsuits from irate customers, clients, and rejected prospects. This article explores the concept of privacy, describes the major computer threats to personal privacy and the changing legal environment, and recommends how organizations can establish internal privacy codes for their own protection.     

Consumers’ Perceptions of Using Health Information Exchanges (HIEs) for Research Purposes

Health Information Exchanges (HIEs) help various organizations to use aggregated clinical data for research purposes. Consumers may concern that private companies could access their personal information and such information could be misused for other purposes. This study attempts to extend the application of privacy calculus theory in the HIE domain by developing a model centered on the perceived benefits, perceived risks, their dimensions and antecedents to predict consumers’ opt-in intention toward HIE use for research purposes.     

The effect of online privacy policy on consumer privacy concern and trust

This study aims to investigate trust and privacy concerns related to the willingness to provide personal information online under the influence of cross-cultural effects. This study investigated the relationships among the content of online privacy statements, consumer trust, privacy concerns, and the moderating effect of different cultural backgrounds of the respondents. In specific, this study developed a proposed model based on Privacy–Trust–Behavioral Intention model. Further, a total of 500 participants participated in the survey, including 250 from Russia and 250 from Taiwan. The findings indicate a significant relationship between the content of privacy policies and privacy concern/trust; willingness to provide personal information and privacy concern/trust; privacy concern and trust. The cross-cultural effect on the relationships between the content of privacy policies and privacy concern/trust was also found significant.     

AIoT-enabled smart surveillance for personal data digitalization: Contextual personalization-privacy paradox in smart home

Artificial intelligence of things technology provides smart surveillance capability for personal data digitalization. It will invade individuals’ information, physical, and social spaces and raise contextual privacy concerns while providing personalized services, which has not been explored in previous research. We theorize three types of smart surveillance and identify three subdimensions of contextual personalization and privacy concerns. Grounded in surveillance theory and personalization-privacy paradox, we examined the different trade-offs of contextual personalization and privacy concerns underlying the three types of smart surveillance on users’ behavioral intention in smart home context. The results also indicated that transparency can lessen the trade-off effects.     

面向移动社交网络的位置隐私保护方法

移动社交网络为人们的生活带来了极大的便利,但用户在享受这些服务带来便利的同时,个人位置隐私受到了严重威胁。首先对用户位置隐私保护需求进行了形式化描述,继而针对用户的敏感兴趣点泄露问题,提出了一种情景感知的隐私保护方法。该方法将位置信息、社交关系、个人信息引入到知识构建算法中以计算兴趣点间的相关性,并利用该相关性及时空情景实时判断发布当前位置是否会泄露用户隐私,进而实现了隐私保护与服务可用性间的平衡。最后通过仿真实验验证了该方法的有效性。     

Dealing with digital traces: Understanding protective behaviors on mobile devices

With increasingly digitization, more and more information is collected from individuals and organizations, leading to several privacy concerns. These risks are further heightened in the mobile realm as data collection can occur continuously and ubiquitously. When individuals use their own devices in work settings, these issues become concerns for organization as well. The question then is how to ensure individuals perform proper information protection behaviors on mobile devices. In this research, we develop a model of mobile information protection based on an integration of the Theory of Planned Behavior and the information privacy literature to explore the antecedents of the attitude of individuals towards sharing information on their mobile devices, their intentions to use protective settings, and their actual practices. The model is tested with data from 228 iPhone users. The results indicate that mobile information protection intention leads to actual privacy settings practice, and that attitude towards information sharing and mobile privacy protection self-efficacy affect this intention. Determinants of attitude towards information sharing include mobile privacy concern and trust of the mobile platform. Finally, prior invasion experience is related to privacy concern. These findings provide insights into factors that can be targeted to enhance individuals’ protective actions to limit the amount of digital information they share via their smartphones.     

Evaluation of users' privacy concerns by checking of their WhatsApp status

WhatsApp Messenger is a popular instant messenger among Iranian users. The WhatsApp status feature provides the possibility of posting desired content without restrictions in terms of type with the capability of being managed by users. Status can be considered as a potential place to express users' feelings, opinions, and thoughts. However, special attention should be paid to the privacy of users and the information published in this manner because access to the content of a user's status by unauthorized friends and interpretations of the user's status content may violate his/her privacy. This study investigates the privacy issues associated with information shared through status. The data of this study were gathered via access to the status content of 4000 Iranian users and via telephone interviews conducted with 350 of them. In this study, a combination of quantitative and qualitative methods has been used to analyze the data. This study focuses on the extraction of patterns in users' status content, determination of their polarity, and examination of the factors affecting users' privacy concerns. During the research, 10 general themes were extracted from users' content. The results showed that user privacy concerns influenced the type of theme selected. In addition, the theme selected under different circumstances may include a type of feeling that, in this study, is called polarity. Polarity is affected by the users' privacy concerns. Moreover, the demographic characteristics of users (age and gender) have a significant relationship with the type of theme used and their privacy concerns.     

The ‘Privacy Paradox’ in the Social Web: The Impact of Privacy Concerns,Individual Characteristics,and the Perceived Social Relevance on Different Forms of Self‐Disclosure

Given the diffusion of the Social Web and increased disclosure of personal information online, the ‘privacy paradox’ suggests that while Internet users are concerned about privacy, their behaviors do not mirror those concerns. This study investigates the potential influence of privacy concerns, psychological traits, attitudes to the Social Web and age on self‐disclosure. Using an online survey of a representative sample of German Internet users (n = 2, 739), the variety and quality of self‐disclosure as well as access were measured. The findings indicate that privacy concerns hardly impact self‐disclosure, but different variables moderate this relation. Perceived social relevance and the number of applications used proved important. Users' general willingness to disclose is most important when providing sensitive information.     

Flamingos on a slackline: Companies' challenges of balancing the competing demands of handling customer information and privacy

Providers of online services are under increasing pressure to leverage the value inherent in customer data to remain competitive. At the same time, however, Internet users' privacy has become more and more subject to public debate, and companies must protect this privacy if they want to attract and retain customers. It seems that companies struggle to satisfy these competing demands, and neglecting either could have detrimental effects on their success. Different streams of research underline the importance of either privacy protection or the collection and use of customer information. But they remain largely silent about the resulting challenges that companies face. In this study, we address this gap by exploring how companies perceive and handle the tensions between their organizational information needs that necessitate some degree of privacy intrusion and their need to attract and retain customers, which requires privacy protection. We develop a grounded theory that explains how companies balance these opposing demands from an organizational perspective. More specifically, we identify four challenging tensions that define the conditions under which companies must operate. We find that companies try to achieve and maintain a state of balance in the presence of these tensions, and we discover three categories of tactics that help companies in their balancing acts. Our research contributes to a provider‐centric perspective on information privacy and uncovers the management of customer information and privacy as a new but important context in which organizational ambidexterity is required. We offer a detailed perspective on the specific challenges that companies face with respect to customer information and privacy, and our results can guide managers who have to deal with these challenges.     

Trading privacy with incentives in mobile commerce: A game theoretic approach

In mobile commerce, companies provide location based services to mobile users, who report their locations with a certain level of granularity to maintain a degree of anonymity. This level of granularity depends on their perceived risk as well as the incentives they receive in the form of monetary benefits or improved mobile services. This paper formulates a quantitative model in which information theoretic metrics such as entropy, quantify the anonymity level of mobile users. The individual perceived risks of users and the benefits they obtain are defined as functions of their chosen location information granularity. The interaction between the mobile commerce company and its users is investigated using mechanism design techniques as a privacy game. The user best responses and optimal strategies for the company are derived under budgetary constraints on incentives, which are provided to users in order to convince them to share their private information at the desired level of granularity. Information limitations in the system are analyzed to capture more realistic scenarios where the companies do not have access to user utility functions. Iterative distributed algorithm and regression learning methods are investigated to design mechanisms that overcome these limitations. The results obtained are demonstrated with a numerical example and simulations based on real GPS data.     

Privacy leakage on the Web: Diffusion and countermeasures

Protecting privacy on the Web is becoming increasingly complicated because of the considerable amount of personal and sensitive information left by users in many locations during their Web browsing and the silent actions of third party sites that collect data, aggregate information and build personal profiles of Internet users in order to provide free and personalized services. On the other hand, most of people are unaware that their information may be collected online, and that, after their aggregation from multiple sources, could be used for secondary purposes, such as linked to allow identification, without user’s notice.