Social Network Site (SNS) users’ disclosed personal information is beneficial for marketers, as targeted advertising can be provided accordingly. This study identifies the three privacy concepts of concerns, attitudes and intentions, along with culture (i.e. Hofstede’s masculinity) to be key drivers of users’ self-disclosure on SNSs. Hence, this study evaluates these antecedents and their potential effect on self-disclosure, considering Facebook as the SNS of choice. To account for potential cross-cultural differences, data has been gathered via two online questionnaires, resulting in one German and one Norwegian sample of respondents. Multiple regression analyses were carried to evaluate the antecedents of self-disclosure and one-way ANOVA to examine potential differences amongst Germans and Norwegians. Results indicate that privacy intention is the strongest predictor of self-disclosure on SNSs; whereas privacy concerns and attitudes only reveal an indirect effect on self-disclosure. In addition, significant differences have been found for all of the constructs, indicating that there exist fundamental differences between Germans and Norwegians with regards to their cognitive processing behind personal information disclosure on SNSs.

Digital technologies have a substantial impact on the tourism industry by affecting thetraveller's behaviour before, during and at the end of the trip and by transforming thetraditional travellers to the digital travellers and smart tourism. Data lies at the core ofall smart tourism activities and received considerable attention in the context of tourists'privacy concerns, precisely, location-based service (LBS). LBS is an example of smarttechnology to enhance travellers' experience and to provide significant benefits to users.Although, LBS become popular among tourists due to high information availability, easeof use, and cheapness, lack of location information protection make the users vulnerable.The latter is a great concern for users when they unintentionally allow the LBS providersto collect all information related to their location. Therefore, this study was conductedby focusing on the general concept of privacy to determine the issues related to the LBSusing in Småland tourism industry. The tourists' perceptions and understanding ofprivacy while using LBC were considered as a general concept of privacy.The study was performed through qualitative research by collecting data from thestructured-interview based on open-ended questions. The qualitative research presentedin this study was based on different viewpoints of interviewees. Thematic analysis wasused to obtain a comprehensive understanding of interviewees' privacy concerns to useLBS. The result indicated four major themes, such as personal information, privacybreach, hesitancy/conditionally and hedonic, that impact differently on tourists' intentionto use LBS. Furthermore, the personality of people, their perceptions and demands couldenhance their privacy concerns for using LBS. These concerns, however, might besuspended when the benefits of gaining information from LBS is considerable. Someother factors, such as the ease of use, user-friendly design, pleasant impression, alongwith providing useful information in the tourism destination, were also considered asessential for LBS adoption among tourists.

Purpose: The purpose of the study is to investigate how consumers reason about personalized online advertising. Research questions:  Do consumers perceive the risks and benefits of personalized online advertisements? How do consumers adapt their behavior based on the risks and benefits perceived by online personalized advertisements?   Methodology: This study is implemented using a qualitative research method and a deductive approach. The empirical data for the study was gathered through twenty individual semi-structured interviews. The researchers employed thematic text analysis to systematically process the acquired data, which was subsequently examined using behavioral-science theories.  Analysis & Conclusion: According to the findings, consumers believe that they receive more relevant ads as a result of advertisements being tailored to them and are willing to share their personal information in order to receive personalized ads. The risks of personalized advertisements stem from privacy issues. However, there is a difference in perceived risks between consumers, in that consumers who are more aware of how their personal information is used by companies see greater risks with personalization. Consumers' attitudes towards personalized ads from companies that they have never signed up for, interacted with or shopped from differ depending on the communication channel through which the ads are displayed. This is because personalized advertisements via e-mail, as opposed to advertisements on websites, are considered to include more personal information such as customer name and e-mail address. As a result, consumers perceive that it is more worrying to receive personalized emails without having supplied their name or email address to the email senders than seeing personalized advertising on websites with which they have never engaged before.

Smartwatches can collect health data, location data and other sensitive information about users, and privacy concerns arise. This thesis aimed to investigate how older people (50-80 years old) in Sweden behave when it comes to privacy and health data. The data were analyzed according to the privacy paradox, which describes the discrepancy between how people behave and how they intend to behave in relation to risk and trust. The research approach was qualitative, and twelve semi-structured interviews were conducted. The interviews were coded and thematized following the chosen theory. Among the twelve participants in the study, a majority did not see, understand, or behave consciously towards the risks of sharing health data. Instead, trust was related to both the disclosure behavior and the intentional behavior among several of the participants in this study. This study indicates that for some of the participants, there are also other factors that determine their behavior, and the privacy paradox alone is not complete. Four of the findings when it comes to participants' behavior towards their health data and privacy were: trust-based decisions, lack of knowledge, low value of personal data, and value benefits more than privacy. Among several of the participants in this study, when trust towards an actor increase, the participant’s risk awareness decreases. It can be discussed whether the participants in the study value the opportunities more than the risks, and this impacts their behavior. Most of the participants think that sharing location data infringes more on their privacy than sharing health data, and self-education might be a reason the behavior and the level of privacy differ among the participants.

Purpose: The purpose of this study is to contribute with a cross-country approach to the research about consumers’ online privacy concerns by investigating Greek and Swedish consumers’ privacy attitudes and behaviours in the digital marketplace. Theoretical framework: The study’s theoretical framework is based on the Power-Responsibility Equilibrium Theory (PRE) perspective and three of Hoftsede’s cultural dimensions; uncertainty avoidance, power distance, and individualism. Methodology: The study has a deductive approach with a quantitative research method. The data was collected by a questionnaire in each country which resulted in 232 answers in total. The answers were then analyzed in Microsoft Excel 16.41, SPSS 26.0, and SmartPLS 3.3.3. Findings: Findings indicate that the impact of power-holders on consumer privacy concerns, privacy empowerment and trust is more prominent for Swedish than for Greek consumers. Moreover, the impacts of privacy concerns, privacy empowerment and trust on consumers’ power-balancing strategies are more substantial for Greek than for Swedish consumers. Implications: The study contributes to the marketing field and academics studying consumers’ behaviour as it adds a cross-cultural approach to the investigation of consumers’attitudes on e-commerce from a PRE theory perspective. Additionally, they can have practical implications for marketers and policymakers in the e-commerce sector as they can gain some insight into how essential corporate privacy responsibility and regulations are to gain the trust of consumers and decrease their privacy concerns. Limitations: Since the study covers Greek and Swedish consumers, it is limited to countries with similar characteristics. Moreover, the majority of the respondents were under 35 years old and their opinions contradicted, not allowing most of the effects to be statistically significant enough to be considered. Originality/Value: Consumer privacy attitudes and behaviours on e-commerce have not been studied from both a power-responsibility equilibrium and a cultural dimensions perspective. This study adds a cross-country approach by studying Greek and Swedish consumers, while at the same time combining two theoretical perspectives.

The Internet of Things (IoT) is one of the most rapidly evolving technologies aroundthe globe that has changed the way people live due to the benefits that comes with itsadoption. However, they have been associated with privacy and security risks. Witha focus on technical mechanisms and a lack of attention to consumer concerns over along time, it is unsurprising that manufacturers lack an understanding of consumersecurity and privacy concerns. While there has been significant empirical researchwarranting consumer concerns, their perceptions remain afoot.The purpose of this study is to understand the consumer privacy and securityperceptions associated with adoption of IoT devices within a smart home. Without an understanding of the consumer perceptions on privacy and security issues, manu-facturers may not address these issues which may hinder the adoption of IoT. While a significant number of studies have shown the privacy and security issues surrounding IoT devices, they have only extended to technical issues, mostly from the manufac-turer’s perspective. Since security is a complex issue involving several stakeholders, these studies cannot be applied from a consumer perspective.In this study we adopt an interpretive philosophical orientation and a qualitativeapproach. In depth interviews are used to collect data from smart homeowners,investigating their perceptions of smart home privacy issues. We have identified threesignificant recurring themes that need to be addressed: ethical and regulatory issues,information control and ownership, and technology design issues.

Smart environments, particularly smart homes have become an increasingly popular topic for research and real world implementations. Despite the popularity of this topic, there is a lack of tools to enable inhabitants of smart environments to perceive which kind of data smart devices generate and to make inhabitants aware of who is accessing their personal information and the purpose for accessing this information. These issues have caused privacy concerns among inhabitants of smart environments – who would like to ensure their personal information is only utilized for their benefits, rather than being used for malicious purposes. Therefore, smart home environments motivate the need for privacy awareness tools to help inhabitants to better understand the privacy implications when their personal information is misused. To address this problem, this thesis suggests guidelines for the design of privacy awareness tools. A literature review evaluated instruments to conduct research about privacy concerns. The Internet Users’ Information Privacy Concerns (IUIPC) framework from Malhotra, Kim, and Agarwal was selected for the empirical part of this thesis project because it is one of the most reliable models developed to measure privacy concerns at the individual level. Quantitative data was gathered through a survey based on this framework. Data collected from 30 experts in the field of study was analyzed using linear regression analysis techniques and principal component analysis. These survey results lead to a set of guidelines that could guide designers and service providers as to what aspects of privacy concerns they should consider and what they should concentrate on when designing privacy awareness tools for ubiquitous computing systems, such as a smart home. / Intelligenta omgivningar och framförallt smarta hem har kommit att bli ett popular forskning samt impementationsområde. Trots ämnets popularitet är det en brist på verktyg som låter personer i dessa intelligenta omgivningar att förstå vilken typ av data som genereras av de smarta apparaterna, att de förstår vem som får tillgång till deras privatinformation och syftet till att informationen används. Dessa problem leder till påverkar användarintegriteten för personerna i de intelligenta omgivningarna. Personerna vill försäkra sig om att deras privatinformation används till deras fördel och inte missbrukas. Det finns ett behov av integretetsverktyg som kan hjälpa personerna att få en bättre förståelse över hur deras integritet påverkas när deras privatinformation missbrukas. Den här rapporten syftar till att behandla detta problem genom att ta fram riktlinjer baserade på användarnas oro kring deras integritet. En litteraturstudie genomfördes för att utvärderade metoder för att genomföra forskning på användarintegritet. Ramverket Internet Users’ Information Privacy Concerns (IUIPC) från Malhotra, Kim, och Agarwal valdes eftersom det var den en av de mest pålitliga modellen för att mäta den individuella oron kring integriteten hos användarna. Kvantitativ data samlades in genom ett formulär baserat på IUIPC ramverket. Datan samlades in under den empiriska fasen utav 30 experter inom forskningsområdet. Linjär regression och principalkomponentanalys användes för att analysera datan från undersökningen. Resultatet från undersökningen diskuterades med målet att tillhandahålla riktlinjer till utvecklare och tjänsteleverantörer, om vilka integritets aspecter vilket bör övervägas samt focusera på vid utveckling av integretetsverktyg för ubika datasystem.

Background: Digital loyalty programs collect extensive personal data, but literature has so far neglected the aspect of privacy concerns within the programs. The privacy paradox denotes the contradictory behavior amongst consumers stating privacy risk beliefs and actual behavior. Existing literature is calling for a dual perspective of the privacy paradox and digital loyalty programs to find the underlying reasons for the contradictory behavior. Purpose: The purpose of this study was to explore (1) if and when privacy concerns existed in digital loyalty programs and (2) why consumers overruled their privacy concerns in digital loyalty programs. Method: A qualitative method with 18 semi-structured interviews were conducted through a non-probability purposive sampling of consumers within digital loyalty programs. The findings were then analyzed through a thematic analysis to finally construct a model based upon the given research purpose.  Conclusion: The findings suggest that consumers experience privacy concerns in digital loyalty programs from external exposure to privacy breaches and when consumers felt their mental construct of terms and conditions were violated. Four themes were found to influence why consumers overrule their privacy concerns and share personal data with digital loyalty programs, relating to cognitive biases, value of rewards received, and digital trust for the program provider. The findings were synthesized into a model illustrating the consumer assessment of personal data sharing in digital loyalty programs and the interconnection between the influences.

The deployment of human-augmented machine learning (ML) systems has become a recommended organizational best practice. ML systems use algorithms that rely on training data labeled by human annotators. However, human involvement in reviewing and labeling consumers' voice data to train speech recognition systems for Amazon Alexa, Microsoft Cortana, and the like has raised privacy concerns among consumers and privacy advocates. We use the enhanced APCO model as the theoretical lens to investigate how the disclosure of human involvement during the supervised machine learning process affects consumers' privacy decision making. In a scenario-based experiment with 499 participants, we present various company privacy policies to participants to examine their trust and privacy considerations, then ask them to share reasons why they would or would not opt in to share their voice data to train a companies' voice recognition software. We find that the perception of human involvement in the ML training process significantly influences participants' privacy-related concerns, which thereby mediate their decisions to share their voice data. Furthermore, we manipulate four factors of a privacy policy to operationalize various cognitive biases actively present in the minds of consumers and find that default trust and salience biases significantly affect participants' privacy decision making. Our results provide a deeper contextualized understanding of privacy-related concerns that may arise in human-augmented ML system configurations and highlight the managerial importance of considering the role of human involvement in supervised machine learning settings. Importantly, we introduce perceived human involvement as a new construct to the information privacy discourse. Although ubiquitous data collection and increased privacy breaches have elevated the reported concerns of consumers, consumers' behaviors do not always match their stated privacy concerns. Researchers refer to this as the privacy paradox, and decades of information privacy research have identified a myriad of explanations why this paradox occurs. Yet the underlying crux of the explanations presumes privacy concern to be the appropriate proxy to measure privacy attitude and compare with actual privacy behavior. Often, privacy concerns are situational and can be elicited through the setup of boundary conditions and the framing of different privacy scenarios. Drawing on the cognitive model of empowerment and interest, we propose a multidimensional privacy interest construct that captures consumers' situational and dispositional attitudes toward privacy, which can serve as a more robust measure in conditions leading to the privacy paradox. We define privacy interest as a consumer's general feeling toward reengaging particular behaviors that increase their information privacy. This construct comprises four dimensions—impact, awareness, meaningfulness, and competence—and is conceptualized as a consumer's assessment of contextual factors affecting their privacy perceptions and their global predisposition to respond to those factors. Importantly, interest was originally included in the privacy calculus but is largely absent in privacy studies and theoretical conceptualizations. Following MacKenzie et al. (2011), we developed and empirically validated a privacy interest scale. This study contributes to privacy research and practice by reconceptualizing a construct in the original privacy calculus theory and offering a renewed theoretical lens through which to view consumers' privacy attitudes and behaviors. / Doctor of Philosophy / The deployment of human-augmented machine learning (ML) systems has become a recommended organizational best practice. ML systems use algorithms that rely on training data labeled by human annotators. However, human involvement in reviewing and labeling consumers' voice data to train speech recognition systems for Amazon Alexa, Microsoft Cortana, and the like has raised privacy concerns among consumers and privacy advocates. We investigate how the disclosure of human involvement during the supervised machine learning process affects consumers' privacy decision making and find that the perception of human involvement in the ML training process significantly influences participants' privacy-related concerns. This thereby influences their decisions to share their voice data. Our results highlight the importance of understanding consumers' willingness to contribute their data to generate complete and diverse data sets to help companies reduce algorithmic biases and systematic unfairness in the decisions and outputs rendered by ML systems. Although ubiquitous data collection and increased privacy breaches have elevated the reported concerns of consumers, consumers' behaviors do not always match their stated privacy concerns. This is referred to as the privacy paradox, and decades of information privacy research have identified a myriad of explanations why this paradox occurs. Yet the underlying crux of the explanations presumes privacy concern to be the appropriate proxy to measure privacy attitude and compare with actual privacy behavior. We propose privacy interest as an alternative to privacy concern and assert that it can serve as a more robust measure in conditions leading to the privacy paradox. We define privacy interest as a consumer's general feeling toward reengaging particular behaviors that increase their information privacy. We found that privacy interest was more effective than privacy concern in predicting consumers' mobilization behaviors, such as publicly complaining about privacy issues to companies and third-party organizations, requesting to remove their information from company databases, and reducing their self-disclosure behaviors. By contrast, privacy concern was more effective than privacy interest in predicting consumers' behaviors to misrepresent their identity. By developing and empirically validating the privacy interest scale, we offer interest in privacy as a renewed theoretical lens through which to view consumers' privacy attitudes and behaviors.

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