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The role of privacy fatigue in online privacy behavior
Abstract
The increasing difficulty in managing one's online personal data leads to individuals feeling a loss of control. Additionally, repeated consumer data breaches have given people a sense of futility, ultimately making them weary of having to think about online privacy. This phenomenon is called “privacy fatigue.” Although privacy fatigue is prevalent and has been discussed by scholars, there is little empirical research on the phenomenon. This study aimed not only to conceptualize privacy fatigue but also to examine its role in online privacy behavior. Based on literature on burnout, we developed measurement items for privacy fatigue, which has two key dimensions —emotional exhaustion and cynicism. Data analyzed from a survey of 324 Internet users showed that privacy fatigue has a stronger impact on privacy behavior than privacy concerns do, although the latter is widely regarded as the dominant factor in explaining online privacy behavior.
... The expansion of the information age has led to users' experiencing a feeling of losing control over personal data management, resulting in a sense of weariness toward privacy issues; this is referred to as privacy fatigue (Choi et al., 2018;Shao et al., 2022). The influence of privacy fatigue on users' disclosure intentions has been explored (Choi et al., 2018;Zhu et al., 2021;Shao et al., 2022), verifying that privacy fatigue affects users' disclosure intentions under different scenarios. ...
... The expansion of the information age has led to users' experiencing a feeling of losing control over personal data management, resulting in a sense of weariness toward privacy issues; this is referred to as privacy fatigue (Choi et al., 2018;Shao et al., 2022). The influence of privacy fatigue on users' disclosure intentions has been explored (Choi et al., 2018;Zhu et al., 2021;Shao et al., 2022), verifying that privacy fatigue affects users' disclosure intentions under different scenarios. ...
... As an increasing amount of personal information is being used for Internet services, the ability of users to control the disclosure of their personal information is gradually weakening. Privacy fatigue refers to an individual's feeling of losing control over personal data management and the weariness of thinking about privacy (Choi et al., 2018;Shao et al., 2022;Schyff et al., 2023). In contrast to social media fatigue, privacy fatigue emphasizes users' attitudes toward privacy and personal information, which is prevalent on SNSs. ...
With the development of the information age, people need to disclose personal information in exchange for socializing and related services. At the same time, people's privacy concerns are gradually increasing. Privacy paradox has become a normal phenomenon in social network sites (SNS). The loss of control of privacy might lead to privacy fatigue. Previous work has studied the mechanism of privacy paradox and explored the influence of specific factors on privacy paradox. However, the effect of privacy fatigue on privacy paradox among SNS users has not been studied. In this study, we use structural equation modeling (SEM) to explore the effect of privacy fatigue on personal information disclosure intentions and actual behaviors among WeChat users. Our results of 710 participants showed that privacy fatigue has a mediating role between privacy concern and privacy disclosure intention, and has a positive influence on privacy disclosure intention and disclosure behavior. Based on these results, we provide implications to reduce privacy fatigue and privacy paradox.
... It has been noticed that internet users adopt psychological distancing and maladaptive responses to deal with their privacy concerns, such as privacy cynicism, vis-à-vis the protection motivation (Hoffmann et al., 2016;Lutz et al., 2020;van Ooijen et al., 2022). Privacy cynicism is regarded as a form of MEFC, wherein disillusionment and apathy are used to regulate emotions and achieve self-preservation as internet users fail to address the root problem or threat when facing stressful privacy situations (Choi et al., 2018;. Cynical attitudes are considered a fundamental dimension of moral decision-making (Turner & Valentine, 2001) and a potential reason for the privacy paradox (Hoffmann et al., 2016;Lutz et al., 2020). ...
... Thus, we infer that internet users with privacy cynicism are not willing to spend time dealing with information privacy issues and are prone to adopt simpler and easier ways of dealing with threats. When weighing the option to disclose information, privacy cynics usually undertake a low level of cognitive effort (Choi et al., 2018), which means they do not think carefully about the consequences of disclosing personal information. To some extent, disclosing information without in-depth reflection can be regarded as a passive acceptance of the current privacy threats and an act of resignation. ...
... We adopted measures of privacy protection motivation from Posey et al., (2015). We measured privacy cynicism as an individual's self-assessed emotionfocused coping strategy, with items adapted from Choi et al., (2018). As it is difficult to obtain reliable data on observed actual behavior, we used self-reported behavior as a proxy for personal information disclosure behavior, which was measured with items adapted from Dienlin and Trepte (2015). ...
Dealing with privacy threats and adopting appropriate strategies to manage personal information have become crucial challenges for internet users. While adaptive problem-focused coping (APFC) has been extensively discussed in the literature on information privacy, little is known about maladaptive emotion-focused coping (MEFC). This paper proposes that individuals employ privacy protection motivation (a form of APFC) and privacy cynicism (a form of MEFC), according to their threat and coping appraisals. These two coping strategies will then influence their behaviour regarding the disclosure of personal information on the internet. Offering an empirical analysis of 346 samples of survey data from China, this paper reveals that privacy cynicism, which is mainly affected by deep concerns about privacy and high self-efficacy but low response efficacy, and inconsistency between users’ motivations for protecting their privacy and their actual disclosure behavior are the reasons for the privacy paradox. This study provides crucial theoretical support and practical guidance for the privacy management of internet users’ information.
... This complexity is exacerbated by the fact that privacy policies are often long and inaccessible [55], hindering users' ability to effectively manage their privacy. Thus, as users install more apps, the task of maintaining privacy settings becomes more burdensome, leading to users experiencing privacy fatigue [15]. Moreover, the variation in users' privacy literacy [7] and awareness about privacy settings introduces another layer of complexity to this issue, affecting their ability to navigate and manage their privacy effectively. ...
... This method has been employed in the previous work investigating location privacy behaviours of iOS users [26]. • Privacy Fatigue (Burnout general survey): A continuous variable assessed using six items on a 7-point Likert scale measuring the emotional exhaustion and cynicism users feel towards managing location privacy settings on smartphones [15,61]. ...
... Our study underscores the significant impact of several factors on the usage intention of location privacy controls. For instance, the continuous exposure to privacy-related decisions and information overload (i.e., privacy fatigue [15]) can lead to disengagement, posing a challenge for designers and policymakers. At the same time, the influence of interface usability also highlights the need for designing user-friendly privacy interfaces that can encourage engagement, particularly among less tech-savvy users. ...
As the number of applications installed on smartphones continues to grow, the task of effectively managing location privacy has become increasingly complex. In this paper, we explore the factors that influence users' privacy-preserving intentions and contrast them with their actual behaviours. In addition, we compare location privacy concerns across different apps investigating the impact of app-specific features on the willingness to disclose location information. Our findings highlight significant challenges in privacy management due to privacy fatigue and perceived usability. Furthermore, participants raised the importance of more uniform standards regarding location privacy settings across various applications, calling for more detailed and interactive well-informed consent processes that highlight the risks instead of the benefits of disclosing location information. This research contributes important insights towards the development of more effective privacy settings that can foster increased user engagement in managing location privacy on smartphones.
... The privacy calculus theory posits that users make decisions about data sharing by weighing the costs, primarily perceived risk of privacy loss, against the benefits, which may include financial rewards or enhanced convenience (Dinev and Hart, 2006;Li et al., 2023). However, incomplete information, cognitive biases, and the effort required to manage own privacy effectively often disrupt these rational assessments, contributing to feelings of "privacy fatigue" or disengagement (Choi et al., 2018;Hoffmann et al., 2016). Persuasion knowledgethe understanding of personalized marketing tacticsfurther influence these decisions, sometimes heightening users' concerns and other times diminishing them by fostering a sense of control (Ham et al., 2015;Jain and Purohit, 2022). ...
... For instance, users may overlook the potential costs of data sharing due to the disproportionately high effort required to learn about them (Gerber et al., 2018). Increased cognitive efforts required (and often not even sufficient) for satisfactory data management can lead to feelings of powerlessness referred to as "privacy cynicism" by Hoffmann et al. (2016) and particularly in the context of personalized ads by Chen et al. (2023), "privacy fatigue" by Choi et al. (2018), or "digital resignation" by Draper and Turow (2019), ultimately contributing to users' disengagement from effective data management. ...
This study explores stated preferences for privacy and advertising in the Video on Demand (VoD) context, focusing on Netflix subscribers in Poland. We investigate how privacy concerns, persuasion knowledge, and consumer experience affect these preferences. The study design involved a hypothetical regulatory scenario that mandated platforms to either guarantee minimal data usage or offer compensation for data sharing. Within a discrete choice experiment framework, study participants were presented with hypothetical scenarios and asked to choose between three types of subscription plans, varying in the extent of personal data sharing and ad support. Additionally, a treatment was introduced in which respondents interacted with a mock Netflix environment to enhance their recognition of data practices and increase familiarity with hypothetical outcomes through a simulated experience. Responses from 2,087 participants were analyzed using hybrid choice modeling. The results reveal that users are sensitive to the disclosure of personal information in the context of VoD, yet they are open to accepting monetary compensation for a certain degree of sharing. Users with greater persuasion knowledge are more willing to exchange data for discounts, provided the plans do not include personalized ads. Conversely, users with higher privacy concerns prefer plans with minimal data sharing, even when discounts are offered. We observe direct effects of the treatment on both privacy valuation and advertising preferences, particularly regarding time, with the treatment group being significantly more sensitive to ad length. In addition, the treatment group exhibits reduced privacy concerns and no significant difference in persuasion knowledge. Our findings suggest that VoD providers could enhance user control over their data and emphasize transparency, aligning with the increasing reliance on data-driven business models.
... We analyzed the annual privacy protection reports released by the Personal Information Protection Commission (2020,2021,2022); the survey data indicated that a high percentage of individuals demonstrated a passive attitude and took no action for redress following personal information leaks. This situation, characterized by a sense of passivity, leads to privacy fatigue, which refers to feelings of resignation and exhaustion regarding privacy issues (Choi et al., 2018). A certain degree of privacy fatigue may prevail among people, and undergraduate students are no exception to this. ...
... According to Choi et al. (2018), people who experience significant privacy fatigue are less inclined to deliberate on how and if they should share personal details, and they may consent to sharing their information without much thought. Despite the ongoing concerns raised about ChatGPT, individuals who consent to sharing their information without much consideration are likely to be indifferent to ChatGPT's privacy issues and have a higher intention to use ChatGPT. ...
OpenAI’s generative pre-trained transformer (ChatGPT) is rapidly transforming fields such as education and becoming an integral part of our daily lives. However, its rise has sparked intense privacy debates, raising concerns about the storage of personal information and attracting global regulatory scrutiny. ChatGPT is gaining popularity among undergraduate students owing to its personalized learning capabilities, leading many universities to provide guidelines and seminars on its use. Curiosity about the reasons for ChatGPT’s popularity inspired our research. Through a survey of 695 undergraduate students in South Korea, we found that “privacy fatigue”—a feeling of hopelessness and weariness regarding privacy—was associated with these students’ adoption of ChatGPT. The findings revealed that this fatigue reduces perceived privacy risks, enhances their expectations of the platform, and boosts their intention to use ChatGPT. By incorporating the concepts of privacy fatigue, perceived risk, and elements from the unified theory of acceptance and use of technology, we developed a novel model to understand this phenomenon. Interestingly, despite the potential risks, the intention to use ChatGPT was not significantly influenced by perceived risk. This study contributes to a better understanding of undergraduate students’ privacy perceptions when leveraging ChatGPT in education.
... Users are frequently prevented from using a specific technology if they do not agree to its privacy terms and conditions, which frequently include disclosing personal information to third parties (Nemmaoui et al., 2023). Thus, privacy issues bother them (Hong & Thong, 2013) and indeed, can influence SNS users behavior (Choi et al., 2018;Zulfahmi et al., 2023) in domains such as information disclosure (Ozdemir et al., 2017) and reduced use (Dhir et al., 2019). ...
... By doing so, our findings extend the prior research on the drivers of SNS use reduction. They highlight the need to focus on such aspects as privacy concerns as motivators of SNS use reduction, given the vast amount of data that is collected through SNS (Choi et al., 2018) and recent scandals and privacy breaches (Brown, 2020;Hinds et al., 2020). Ultimately, our findings points to a greater need to study SNS use reduction, and to include privacy concerns as a key motivator of user behavior change. ...
... Here, users accept data being collected in exchange for being able to use a service, c.f. Price of Convenience [36]. Additionally, today we see digital resignation [20,59] or privacy fatigue [15] as an overload or lack of control leads to resignation, i.e., users giving up dealing with privacy decisions. As such, users face a challenge with the fundamental concepts of permissions and the associated privacy. ...
... https://web.dev/progressive-web-apps/, last accessed 2024-[11][12][13][14][15][16][17] ...
Today, users are constrained by binary choices when configuring permissions. These binary choices contrast with the complex data collected, limiting user control and transparency. For instance, weather applications do not need exact user locations when merely inquiring about local weather conditions. We envision sliders to empower users to fine-tune permissions. First, we ran two online surveys (N=123 & N=109) and a workshop (N=5) to develop the initial design of Privacy Slider. After the implementation phase, we evaluated our functional prototype using a lab study (N=32). The results show that our slider design for permission control outperforms today's system concerning all measures, including control and transparency.
... In recent privacy research, a new perspective is emerging that centers on user agency-or the lack thereof-as a critical but under-examined aspect of privacy attitudes and behaviors. Independently and across different geographic, political, and social contexts, scholars have noted the manifestation of resigned attitudes towards threats to digital privacy, variably termed privacy apathy (Hargittai and Marwick, 2016), privacy cynicism (Hoffmann et al., 2016;Lutz et al., 2020;Ranzini et al., 2023), surveillance realism (Dencik and Cable, 2017), privacy fatigue (Choi et al., 2018), digital resignation (Turow et al., 2015;Draper and Turow, 2019), and privacy helplessness (Cho, 2022). Despite differences in terminology and empirical approaches, these works share the conclusion that a sizable share of individuals feels overwhelmed and disempowered when it comes to protecting their privacy from the threats posed by the digital infrastructures on which they rely for social, economic, and political inclusion. ...
... They point out that privacy resignation does not entirely preclude protective behavior, but note that efforts to interrupt corporate surveillance are sporadic and individualistic rather than sustained and collective. Choi et al. (2018) build on studies of burnout to develop the concept of "privacy fatigue." They argue that Internet users in South Korea frequently encounter privacy breaches (or reporting on such breaches), which leaves them increasingly emotionally exhausted and unwilling to address privacy concerns or protection behavior. ...
The growing trend of collecting data about individuals to track past actions and infer future attitudes and behaviors has fueled popular and scholarly interest in the erosion of privacy. Recent shifts in technologies around machine learning and artificial intelligence have intensified these concerns. This editorial introduces the articles in the special theme on digital resignation and privacy cynicism: concepts developed in the past decade to explain the growing powerlessness individuals feel in relation to their digital privacy even as they continue to experience consternation over the collection and use of their personal information. The papers in this special theme engage and extend existing research on these topics. The original articles and commentaries pose theoretical and practical questions related to the ways people confront the powerful institutional forces that increasingly shape many aspects of the information environment. They employ several methodologies and theoretical perspectives and extend the range of geographic, political, cultural, and institutional contexts in which privacy cynicism and digital resignation can be identified and examined. In addition to contextualizing these contributions, this editorial maps a range of related concepts including digital resignation, privacy cynicism, privacy apathy, surveillance realism, privacy fatigue, and privacy helplessness. It concludes by identifying key themes across the papers in this collection and provides directions for future research.
... Should this sensor be left on when you host friends? Consequently, the cognitive burden increases, leaving users in disarray, tired, and unable to decide in their best interests [17]. ...
To help users make privacy-related decisions, personalized privacy assistants based on AI technology have been developed in recent years. These AI-driven Personalized Privacy Assistants (AI-driven PPAs) can reap significant benefits for users, who may otherwise struggle to make decisions regarding their personal data in environments saturated with privacy-related decision requests. However, no study systematically inquired about the features of these AI-driven PPAs, their underlying technologies, or the accuracy of their decisions. To fill this gap, we present a Systematization of Knowledge (SoK) to map the existing solutions found in the scientific literature. We screened 1697 unique research papers over the last decade (2013-2023), constructing a classification from 39 included papers. As a result, this SoK reviews several aspects of existing research on AI-driven PPAs in terms of types of publications, contributions, methodological quality, and other quantitative insights. Furthermore, we provide a comprehensive classification for AI-driven PPAs, delving into their architectural choices, system contexts, types of AI used, data sources, types of decisions, and control over decisions, among other facets. Based on our SoK, we further underline the research gaps and challenges and formulate recommendations for the design and development of AI-driven PPAs as well as avenues for future research.
... Another issue is that IVAs are always listening: Even a single wake-word utterance or similar phrases immediately record potentially sensitive conversations, which are then sent to the provider's cloud (Edu, Such, & Suarez-Tangil, 2020). Many users are unaware of the extent of this data collection and how their data is used or shared (e.g., for advertising purposes), leading to a sense of losing privacy control (Abdi, Zhan, Ramokapane, & Such, 2021;Bonilla & Martin-Hammond, 2020;Choi, Park, & Jung, 2018;Malkin et al., 2019;Son & Kim, 2008;Tabassum et al., 2019). Users frequently perceive themselves as powerless in the face of privacy breaches due to a lack of privacy-related knowledge (Emami-Naeini, Dixon, Agarwal, & Cranor, 2019; Huang, Han, & Zhu, 2021;Jacobsson & Davidsson, 2015;Lau et al., 2018). ...
... Esta fatiga puede generar sentimientos de impotencia y falta de control sobre las decisiones relacionadas con la privacidad, lo que, en última instancia, influye en el comportamiento de privacidad en línea. De hecho, la fatiga por la index•comunicación | nº 15(1), 2025 | Monográfico 142 privacidad puede tener un impacto más significativo en el comportamiento en línea que las preocupaciones por la privacidad (Choi et al., 2018). ...
In 2023, European Instagram users faced a choice: subscribe to avoid advertisements or allow their data to be used for targeted advertising. This study examines how Generation Z engages with personalised advertising and their privacy concerns, focusing on Instagram's new subscription model. An online survey of 479 young people aged 14 to 24 revealed that only 12.5% would be willing to pay for a subscription. Despite many find advertising overwhelming and distracting and perceiving a considerable risk to data protection in social media use, neither advertising saturation nor privacy concerns appear to influence their willingness to subscribe. These findings reinforce the theory of the privacy paradox and underscore the need for new approaches to address data privacy concerns among younger users.
... Hargittai & Marwick's study summarized through interviews that users' spiritual alienation or cynicism toward privacy issues is an important reason for the disconnection between privacy concerns and privacy disclosure behavior 13 ; Zhu et al.'s latest research also shows that in e-commerce, social media, and other scenarios, users invest a considerable amount of time, money, and cognitive effort, resulting in very high sunk costs. In such situations, privacy fatigue as a coping mechanism promotes disclosure behavior 7 . ...
Privacy fatigue caused by privacy data disclose and the complexity of privacy control has become an important factor influencing people’s privacy decision-making behavior. At present, academia mainly studies privacy fatigue as a key determinant to explain the privacy paradox problem, but there is insufficient attention to its influencing factors and specific pathway of occurrence. Exploring the antecedents of privacy fatigue is of great significance for alleviating users’ subjective privacy detachment and promoting privacy protection. Based on the Stressor-Strain-Outcome (SSO) theoretical framework, this study aims to explore the antecedents of privacy fatigue through the qualitative comparative analysis method of fuzzy set (fsQCA). The results show that there are three patterns of pathways which lead to privacy fatigue, namely the rational pattern, emotional pattern, and strain pattern. This study not only provides theoretical reference for understanding the antecedents of privacy fatigue among users but also offers new practical solutions for user privacy management.
... Lack of usable privacy controls also contributes to a variety of privacy-related attitudes, such as privacy fatigue and privacy helplessness (Cho, 2021). Privacy fatigue is caused by the increasing difficulty in managing one's online personal data leading to an individual feeling a loss of control and making an individual weary of having to think 2024 International Conference on Intelligent and Innovative Computing Applications (ICONIC) 7th-9th November 2024, Pearle Beach Resort & Spa, Flic en Flac, Mauritius about online privacy (Choi et al., 2018). Privacy helplessness is the belief that something bad will happen and that nothing can be done to alter it; and it can be a major obstacle that prevents users from responding appropriately to privacy threats (Cho, 2021). ...
With the increasing use of mobile devices and the collection of personal data through mobile applications, protecting user privacy has become a critical concern. However, many privacy controls in mobile applications are difficult to use, leading users to either ignore them or disable them altogether. During the review of the selected articles, key overarching categories emerged, including usability and user experience, privacy control features, and user education and support. However, significant gaps persist in translating design principles into practical implementations, understanding the comprehensive user experience with different privacy control designs, considering the influence of contextual factors, addressing the implications of emerging technologies, and exploring the longitudinal aspects of user-privacy interactions. This review highlights the need for a framework that bridges these gaps to enhance user privacy and control in mobile applications. The findings of this review provide insights for researchers and practitioners to develop effective and user-centric privacy controls for mobile applications, ensuring a balance between usable privacy and protection.
... Consumers face a signi cant information gap compared to other entities responsible for implementing protection measures, as the speci c methods used to obtain their personal information and how that information is ultimately used are unclear. Consequently, two dimensions of privacy fatigue emerge-emotional exhaustion and cynicism-which lead to a reduction in individuals' decision-making efforts related to privacy protection (Choi et al. 2018). ...
Drawing on advertising avoidance theory, control agency theory and privacy calculus theory, this study develops a model of factors affecting personalized advertising avoidance, which include consumers’ perceptions of privacy, encompassing their internal views, perception of the external privacy environment, perceived personalization of personalized advertising, and personal experiences of privacy. The study conducts an online survey, collecting 502 valid questionnaires. Following verification through structural equation modeling analysis, the research reveals that privacy concerns, privacy fatigue, the perceived effectiveness of privacy-protective technology, the perceived effectiveness of laws, perceived personalization, and prior negative experiences directly impact precision advertising avoidance. Perceived risk, plays a mediating role between privacy concern and advertising avoidance, between the perceived effectiveness of industry self-regulation and advertising avoidance, and between prior negative experiences and advertising avoidance. Lastly, this research proposes suggestions aimed at establishing a more secure network privacy protection environment and enhancing the appeal of personalized advertising content to reduce consumers’ avoidance and promote its future development.
... One common issue is transparency in privacy policies [34] [35] [6] [36]. Policies tend to be long, written in inaccessible language, and users tend to struggle to understand their content, resulting in issues like consent fatigue [37]. Privacy policies can also use persuasive language [35] [38] to let the users trust a service that, for instance, claims all rights over users' data [39]. ...
The growing use of Machine Learning and Artificial Intelligence (AI), particularly Large Language Models (LLMs) like OpenAI's GPT series, leads to disruptive changes across organizations. At the same time, there is a growing concern about how organizations handle personal data. Thus, privacy policies are essential for transparency in data processing practices, enabling users to assess privacy risks. However, these policies are often long and complex. This might lead to user confusion and consent fatigue, where users accept data practices against their interests, and abusive or unfair practices might go unnoticed. LLMss can be used to assess privacy policies for users automatically. In this interdisciplinary work, we explore the challenges of this approach in three pillars, namely technical feasibility, ethical implications, and legal compatibility of using LLMs to assess privacy policies. Our findings aim to identify potential for future research, and to foster a discussion on the use of LLM technologies for enabling users to fulfil their important role as decision-makers in a constantly developing AI-driven digital economy.
... This agreeable behavior is made more likely by the onslaught of cookie consent interfaces across apps and web pages in Europe. Together, these interfaces contribute to 'privacy fatigue' (Choi et al., 2018), building a habitus so that every time someone clicks 'I agree' increases the chance they will do so next time (Portmann, 2022). This practice is also enabled by the fact that it is so common among apps it appears 'natural' to the user: "apparently, this is simply how digital media work" (ibid.). ...
As health systems increasingly adopt digital solutions, such as remote monitoring and telemedicine, the use of health apps is becoming increasingly widespread. Meanwhile, data protection regulations and digital transformation initiatives are making the individual responsible for protecting their health data. In this brief communication, we focus on how the consent interface in a health app can impact trust and inclusion in digital health for privacy-sensitive people. As the consent interface determines how an individual’s health data can be used in medical research, it represents a critical point between the citizen’s right to informational self-determination and the potential public benefit of advances in medical science. We find that app developers’ interests in controlling access to health data may influence the design of the consent interface and undermine an individual’s ability to understand what they are consenting to. We describe how a standardized consent interface applied to health apps could foster a trusting relationship between individuals and the digital transformation of healthcare.
... Fatigued individuals prefer to avoid the topic of privacy or rationalize that they have nothing to hide from third parties. This may also deter users from considering privacy-protective measures in the first place (Choi et al., 2018). Hence, it may be crucial for interventions to target individuals' privacy awareness first. ...
The use of privacy-enhancing technologies (PETs) to protect online privacy is a promising preventive measure. However, many users lack knowledge of their existence and application. This study reports the results of a pre-registered longitudinal experiment aimed at encouraging Internet users to install and use Tor, which enables anonymous browsing. The study compares two soft-paternalistic interventions: a social norm nudge and an educational boost, each with positive and negative framing. The data (NT1 = 1,450; NT2 = 1,171) were based on a sample representative of German online users. The study finds that targeting users’ literacy and framing Tor as a PET, rather than as a darknet technology, increases users’ motivation to install and use the browser. However, the effects are only observed in the short-term and do not translate into actual behavior. We discuss implications for theory and practice regarding the effectiveness of interventions encouraging PET adoption.
... However, the validity of the privacy paradox is highly debated in the literature, and its existence is questioned (Solove 2021). Lastly, this finding can be also explained with the concept of "privacy fatigue", which refers to the increasing difficulty individuals face in managing their online personal data, leading to weariness about having to constantly consider online privacy (Choi et al. 2018). ...
GitHub provides developers with a practical way to distribute source code and collaboratively work on common projects. To enhance account security and privacy, GitHub allows its users to manage access permissions, review audit logs, and enable two-factor authentication. However, despite the endless effort, the platform still faces various issues related to the privacy of its users. This paper presents an empirical study delving into the GitHub ecosystem. Our focus is on investigating the utilization of privacy settings on the platform and identifying various types of sensitive information disclosed by users. Leveraging a dataset comprising 6,132 developers, we report and analyze their activities by means of comments on pull requests. Our findings indicate an active engagement by users with the available privacy settings on GitHub. Notably, we observe the disclosure of different forms of private information within pull request comments. This observation has prompted our exploration into sensitivity detection using a large language model and BERT, to pave the way for a personalized privacy assistant. Our work provides insights into the utilization of existing privacy protection tools, such as privacy settings, along with their inherent limitations. Essentially, we aim to advance research in this field by providing both the motivation for creating such privacy protection tools and a proposed methodology for personalizing them.
... This behavior should not be misconstrued as an indication that users do not value their privacy (Solove, 2021). However, continuous exposure to privacy threats can lead to privacy fatigue, where individuals feel overwhelmed and resign themselves to the inevitability of privacy violations (Choi et al., 2018). Over-reliance on technology and trust in service providers further compounds the problem, leading individuals to overlook potential privacy risks (Taddei and Contena, 2013). ...
The integration of digital technologies into various aspects of life is not only transforming industries and economies but also fundamentally altering human interactions and societal dimensions, raising critical ethical and societal concerns, particularly regarding human agency and human rights. Current approaches for addressing these concerns, particularly in the case of digital privacy, are predominantly "individual-centric", placing an undue burden on individuals who often lack the necessary knowledge and resources to protect their digital rights. This article argues for a paradigm shift towards human-compatible approaches by providing individuals with cognitive, collective, and contextual supports to empower them. The article redefines "humans in the loop" as a collective practice and expands the ongoing debates from "data protection" to the broader discourse of "digital protection." It proposes the establishment of novel sociotechnical mechanisms, such as the "Advanced Data Protection Control (ADPC)", within internet infrastructures to facilitate effective communication between users and stakeholders. This approach addresses the shortcomings of current practices dominated by service providers and advocates for innovative policy-making and technical advancements. By integrating collective supports with automation and other cognitive and contextual supports, the goal is to foster a sustainable and accountable digital future that ensures pluralism, inclusion, and human agency in the continuous co-creation, evaluation, and improvement of digital technologies.
... However, the validity of the privacy paradox is highly debated in the literature, and its existence is questioned (Solove 2021). Lastly, this finding can be also explained with the concept of "privacy fatigue", which refers to the increasing difficulty individuals face in managing their online personal data, leading to weariness about having to constantly consider online privacy (Choi et al. 2018). ...
GitHub provides developers with a practical way to distribute source code and collaboratively work on common projects. To enhance account security and privacy, GitHub allows its users to manage access permissions, review audit logs, and enable two-factor authentication. However, despite the endless effort, the platform still faces various issues related to the privacy of its users. This paper presents an empirical study delving into the GitHub ecosystem. Our focus is on investigating the utilization of privacy settings on the platform and identifying various types of sensitive information disclosed by users. Leveraging a dataset comprising 6,132 developers, we report and analyze their activities by means of comments on pull requests. Our findings indicate an active engagement by users with the available privacy settings on GitHub. Notably, we observe the disclosure of different forms of private information within pull request comments. This observation has prompted our exploration into sensitivity detection using a large language model and BERT, to pave the way for a personalized privacy assistant. Our work provides insights into the utilization of existing privacy protection tools, such as privacy settings, along with their inherent limitations. Essentially, we aim to advance research in this field by providing both the motivation for creating such privacy protection tools and a proposed methodology for personalizing them.
... First, since smart buildings have countless IoT devices and sensors collecting data (e.g., energy sensors, lighting, temperature, air quality, etc.), it is possible that the number of notifications can overwhelm building occupants and visitors. This may lead to privacy fatigue [9] if users receive too many irrelevant privacy notices. Second, IoT devices and sensors in smart buildings lack traditional user interfaces (e.g., screens), so it is difficult to deliver privacy notifications through the most intuitive primary channels (i.e., IoT devices and sensors themselves). ...
Data collection through the Internet of Things (IoT) devices, or smart devices, in commercial buildings enables possibilities for increased convenience and energy efficiency. However, such benefits face a large perceptual challenge when being implemented in practice, due to the different ways occupants working in the buildings understand and trust in the data collection. The semi-public, pervasive, and multi-modal nature of data collection in smart buildings points to the need to study occupants' understanding of data collection and notification preferences. We conduct an online study with 492 participants in the US who report working in smart commercial buildings regarding: 1) awareness and perception of data collection in smart commercial buildings, 2) privacy notification preferences, and 3) potential factors for privacy notification preferences. We find that around half of the participants are not fully aware of the data collection and use practices of IoT even though they notice the presence of IoT devices and sensors. We also discover many misunderstandings around different data practices. The majority of participants want to be notified of data practices in smart buildings, and they prefer push notifications to passive ones such as websites or physical signs. Surprisingly, mobile app notification, despite being a popular channel for smart homes, is the least preferred method for smart commercial buildings.
... These findings resonate with previous research, highlighting the adverse effects of limited corporate privacy responsibilities and regulatory protection on consumer trust (Bandara et al. 2021;Choi et al. 2018). Thus, privacy plays a significant role in determining e-commerce platform security. ...
In the fast-paced, post-COVID digital world, e-commerce presents promising prospects for significant advancement. However, customers often feel uncertain due to persistent concerns about the robustness of security measures safeguarding e-commerce platforms. The primary objective of our study was to identify factors affecting the security of e-commerce platforms based on the perceptions of Sri Lankan customers. This research was conducted using data collected from Sri Lankan e-commerce users via both online and offline surveys. An ordered probit regression model was utilised, demonstrating that transaction security, privacy, vendor system security, and platform quality positively impact the perceived security of e-commerce. The e-commerce industry in Sri Lanka is expected to see growth and an increased user penetration rate. The findings of this study are anticipated to assist e-commerce business owners and policymakers in addressing critical security issues, namely vulnerabilities in transactional security, low privacy, inadequate system security, and poor e-commerce platform quality. These improvements are expected to build trust and credibility among consumers, maximising e-commerce success.
... This sense of helplessness extends across affective and cognitive dimensions. In this respect, several conceptual frameworks emerged in privacy research: privacy apathy [40,50], privacy cynicism [44], privacy fatigue [19], privacy helplessness [18], and resignation [24]. They denote feelings of powerlessness or resignation concerning personal data and individuals' control over data privacy and data practices involving those practices in data-driven technologies. ...
... A wide range of factors have been identified as influencing individuals' privacy concerns within the hospitality domain. Demographic characteristics, such as age, gender, and cultural background, have been found to play a role in shaping privacy concerns (Choi et al., 2018). Personality traits and personal dispositions have also been linked to privacy concerns. ...
Understanding privacy needs has become paramount in the evolving landscape of social robots in the hospitality industry. Traditional privacy concerns, dominated by transactional interactions, fail to encapsulate the complexities of human-social robot interaction on service frontlines. Drawing from the communication management theory and the media equation theory, this study conceptualized "Social Robot Privacy Concerns" (SRPC) and discovered its multidimensionality. The SRPC construct is characterized by three key dimensions: (1) Information Privacy Concern, addressing data management and collection; (2) Interpersonal Privacy Concern, focusing on the robot's physical presence; and (3) Environmental Privacy Concern, encompassing broader contexts of government regulations, media influence, and surveillance mechanisms. The findings unveil that these dimensions are pivotal in navigating the challenges posed by service robots implemented in the hospitality industry, necessitating a nuanced approach to understanding and addressing emergent privacy needs. This study also empirically validated the scale to measure the SRPC construct, providing a foundational tool for future research.
... While most studies seemingly confirm the existence of the paradox through extensive evidence of attitude-behavior divergence, a growing literature contents that individuals' privacy attitudes and behaviors may not, in fact, be misaligned (e.g. Choi et al., 2018;Hoffmann et al., 2016;Solove, 2020). Solove (2020) argues that paradox is a myth since attitudes and behaviors concern fundamentally different things. ...
... 36,37 Alternatively, stress may induce decision fatigue, hindering risk-benefit assessment and resulting in less privacy-conscious decisions and avoidance of effortful privacy decisions. [38][39][40] Future research could explore mediators elucidating how stress impacts privacy-related decisions. ...
Internet and Communication Technologies (ICTs) can foster efficient communication and knowledge acquisition, but there are also tradeoffs in terms of risks to one's privacy. Previous research, including work with the privacy calculus framework, indicates that factors such as perceived risks and benefits of using ICTs, ICT trust, and general privacy concerns can influence individuals' digital privacy-related decisions. One pervasive psychological factor that may potentially alter such privacy-related behaviors is acute stress. Acute stress can promote risk-seeking behaviors and a tendency to prefer immediate rewards over delayed, greater value rewards. However, the effect of acute stress in the applied context of privacy decision making is relatively unknown. Participants (N = 143) in this study were randomly assigned to either an acute stress task (socially evaluated cold pressor task) or an active control task (lukewarm water alone). Results revealed that acute stress condition increased information disclosure, as indexed by accepting more online cookies, sharing one's location more frequently, and revealing greater willingness to self-disclose personal information. In addition, the impact of individuals' levels of perceived risk and benefits, trust, and privacy concern on privacy decision making was examined. However, none of these constructs consistently influenced privacy decisions over and above the effect of stress. Overall, our findings suggest that acute stress has robust, independent influence on privacy decision making.
Purpose
After the changes in its privacy policies, WhatsApp has faced serious backlash from its users, with opinions and posts suggesting boycotts and a shift toward alternative applications becoming prominent. However, research on this reaction after the policy change might create in usage practices is quite limited. This study aims to investigate user decision-making in the dynamic landscape of mobile technologies, focusing on the factors influencing users’ choices between continuing with their current platform and migrating to alternatives.
Design/methodology/approach
Using migration theory and the push–pull mooring (PPM) model, the research identifies push factors (institutional privacy concerns), pull factors (relative privacy protection) and mooring factors (switching costs and exhaustion) as collectively shaping WhatsApp usage continuity.
Findings
Notably, the research highlights that institutional privacy concerns surprisingly do not significantly impact users’ intentions to persist with WhatsApp. Conversely, the relative privacy protection of an alternative platform emerges as a significant pull factor, influencing users’ intentions. Switching costs, particularly replacement and evaluation costs, exert a robust mooring effect, hindering migration and contributing to switching exhaustion. Results suggest that heightened exhaustion further strengthens the intention to persist with the current platform.
Originality/value
This research contributes to the literature by presenting findings that resonate with traditional migration approaches, offering a nuanced perspective on users’ decision-making processes. It delves into the impact of exhaustion on users’ intentions to continue using a platform, as well as the aftermath of policy changes, shedding light on switching dynamics and privacy concerns in reactive processes.
China enacted its first Personal Information Protection Law (PIPL) on 1 November 2021. However, there is a dearth of systematic research examining the implementation of new privacy policies exercised by digital platforms and user engagement with these policies. This study establishes a triple-layered comparative approach to explore the complexities and particularities of privacy policy practices in Chinese digital platforms. The methodology encompasses the analysis of privacy policies from representative platforms—WeChat, Taobao, and Douyin—alongside user experience garnered through a walkthrough method and insights from 28 interviews with platform users. Through critical discourse analysis, the research revealed that state-dominant policy discourses were ingrained in the formulation of platform privacy regulations to legitimize their authority over user data ownership. The users perceived a strong sense of passive protection, characterized by the rigid “agreement” discourse practices that underscore their vulnerability in everyday digital platform usage. The findings shed light on intricate power dynamics at play between platforms, their privacy policies, and users, which leads to polarized reactions from users toward privacy concerns. By examining the articulation of digital privacy policies as instruments of statecraft, we offer a nuanced view of describing non-Western experiences of privacy values and regulatory practices in the digital age.
Protecting online privacy requires users to engage with and comprehend website privacy policies, but many policies are difficult and tedious to read. We present PRISMe (Privacy Risk Information Scanner for Me), a novel Large Language Model (LLM)-driven privacy policy assessment tool, which helps users to understand the essence of a lengthy, complex privacy policy while browsing. The tool, a browser extension, integrates a dashboard and an LLM chat. One major contribution is the first rigorous evaluation of such a tool. In a mixed-methods user study (N=22), we evaluate PRISMe's efficiency, usability, understandability of the provided information, and impacts on awareness. While our tool improves privacy awareness by providing a comprehensible quick overview and a quality chat for in-depth discussion, users note issues with consistency and building trust in the tool. From our insights, we derive important design implications to guide future policy analysis tools.
Privacy research struggles with modelling how individuals value and enact privacy, and faces challenges in explaining apparent contradictions such as the privacy paradox and manifestations of privacy-related disempowerment. Such uncertainties arise from the use of unidimensional privacy constructs or through assumptions that privacy-related decisions are rational or intentional. Addressing these lacunae, we present and empirically test the Dimensionalised Privacy Behaviour (DPB) model, which simultaneously examines the relationships between privacy concerns and privacy-protecting behaviours (PPB) along privacy’s horizontal and vertical orientations, and introduces online privacy literacy and privacy self-efficacy as additional explanatory mechanisms in PPB modelling. Using data from a representative sample of 618 US social media users, we demonstrate that the privacy concerns/privacy behaviours dynamic is better understood along its vertically – and horizontally-oriented dimensions, and that each dimension interacts differently with explanatory elements. Furthermore, while affirming the established logic between privacy concerns and PPB, these results highlight privacy self-efficacy as a significant factor for explaining PPB, with differing effects in each dimension.
Research on user experiences with datafication, the transformation of social life into data, identifies “digital resignation” and “privacy cynicism” as rational responses to feeling overwhelmed and disempowered. But how, exactly, do shared feelings and emotions mediate relationships between datafication and disengaged responses – both individually and institutionally? We develop a relational analysis of datafication, deploying an infrastructural perspective and drawing on affect theory to develop the concept of data disaffection, which we define as the structural cultivation of accepting data accumulation as inevitable. Data disaffection is a structure of feeling that conditions processes across scales of analysis: it manifests in resignation and cynicism on an individual level while simultaneously structuring commercial practices. We illustrate how data disaffection highlights alternative sites and methods for understanding datafication, and we conclude by discussing the implications for understanding datafication as a cultural dynamic as well as a corporate practice.
Purpose
This study aims to examine young social media users’ differential acceptance of data-driven ad personalization depending on the types of personal data used, and to propose and test the Privacy and Trust Equilibrium (PATE) model, a new conceptual model developed to explain the intertwined nature of the competing influences of platform-related factors (privacy concern, trust, and privacy fatigue) on acceptance of ad personalization.
Design/methodology/approach
A survey of 440 Instagram users aged 18–24 in Australia was conducted to examine the relationships between the three factors of the PATE model and acceptance of ad personalization utilizing overt vs covert data collection methods.
Findings
This study shows the highest level of acceptance for personalization using overtly collected data and the lowest for covert data. The results also support the PATE model, revealing the competing dynamics of how the platform-related factors shape consumers’ acceptance of data-driven ad personalization. Privacy concern discourages Instagram users from accepting personalized ads, while trust encourages them. When the pushing influence of privacy concern and the pulling influence of trust form equilibrium, generating cognitive dissonance, privacy fatigue seems to play a significant role in resolving the dissonance, leading to increased acceptance.
Originality/value
This study advances the understanding of how concurrent push–pull-resigning factors affect young consumers’ acceptance of data-driven ad personalization practices, expanding the scope of research on data-driven personalized advertising and privacy.
Cybersecurity fatigue and burnout, driven by an overload of security demands, are pressing concerns in the industry. Research increasingly shows that fatigued employees are more likely to engage in unsafe cyber behaviours, making it essential for cybersecurity leaders to implement targeted mitigation strategies. However, the extent to which these leaders understand the causes of cybersecurity fatigue and can identify effective solutions remains unclear. There is concern that cybersecurity professionals and non-cyber employees may view each other as distinct groups, potentially leading to biased decision-making, where each group recommends different interventions for themselves versus others. This actor-observer bias could have significant implications for leadership decisions, yet it remains underexplored in this context. This study examines what cybersecurity professionals believe are the causes of cybersecurity fatigue in their workplaces and the strategies they would adopt to mitigate it. It compares these views with those of non-cybersecurity managers and regular employees. Using attribution theory, we developed a novel measure, CyFa (pronounced “cipher”), to assess mitigation strategy preferences and attribution styles. Data from 506 participants across these groups were analysed. The findings suggest that actor-observer bias is present in all groups, with cybersecurity professionals and managers being no better at avoiding this bias than others. Differences between the groups often reflected a tendency to avoid responsibility rather than superior decision-making. Additionally, cybersecurity professionals were found to rely heavily on certain strategies, like employee awareness training, while neglecting others, such as organisational system changes.
This study aims to investigate the effect of teachers’ digital citizenship behaviour on their online privacy anxiety levels. The sample of the study consists of 7,465 volunteer teachers randomly selected from among teachers in different branches working in public and private schools in eighty-one provinces affiliated to the Ministry of National Education of the Republic of Turkey. The data were collected using the sociodemographic characteristics information form, the digital citizenship behaviour scale (DCBS) and the online privacy anxiety level scale (OPCAS). Teachers were selected by the quota sampling method and descriptive analysis, t test, ANOVA, Pearson correlation analysis as well as multiple regression analysis methods which were used for the data analysis. There was a low level positive relationship between the teachers’ digital citizenship and their online privacy anxiety levels. The teachers’ online privacy anxiety and their digital citizenship levels are at a medium level. The online privacy anxiety levels of the preschool teachers are lower than those of the high school teachers. The digital citizenship levels of the preschool teachers are higher than those of the high school teachers. As the age of teachers increases, their online privacy anxiety levels increase. Digital citizenship levels of the female teachers are higher than those of the male teachers. The digital citizenship levels of the teachers who spent a long time on the Internet are higher than other teachers. As the age of the teachers increases, the average digital citizenship score decreases. This study reveals that there is a positive relationship between the teachers’ level of digital citizenship and their online privacy concerns. Increased online anxiety encourages the teachers to develop their digital citizenship skills. In this context, increasing the teachers’ awareness of digital citizenship and online privacy will contribute to the development of digital citizenship skills by supporting the idea that they should be concerned about their online privacy.
The rapid development of artificial intelligence (AI) has significantly transformed digital marketing enhancing its effectiveness and raising new ethical and privacy concerns. This study investigates the ethical implications of AI-based digital marketing, particularly focusing on user privacy. In terms of methodology, a systematic literature review (SLR) was conducted to identify relevant variables, followed by Multiple Correspondence Analysis (MCA) using R within the framework of homogeneity analysis of variance using alternating least squares (HOMALS). The MCA analysis identified 3 multivariate groupings, and 21 individual variables extracted from 28 studies. The MCA identified a total of 4 clusters in the eigenvalues/variances analysis, and 5 clusters in the biplot analysis. The findings emphasize the need for a balanced approach that respects user privacy and ethical use of data when developing actions using AI-based digital marketing. However, no significant relationship is evident between the study of variables such as cross-device tracking or data-driven technologies and, the ethics of AI-based digital marketing, despite these being the most profitable actions in this environment. There is no evidence of developing personalized social media content or ads linked to privacy standards. However, a strong connection between behavioral analytics, smart content and metaverse is identified, highlighting the risks of this emerging technology in this research field, as it is not linked to privacy or ethics. Among the results, the strong proximity of real-time tracking, IoT, and surveillance variables underscores the critical need to ethically understand how user behavior in real-time is being monitored, as they do not offer a strong link to privacy or ethics. Additionally, this study provides 21 future research questions that address whether these practices are being ethically implemented, following standards like “privacy-by-default” or “privacy-by-design,” and complying with privacy laws in AI-based digital marketing. To ensure these practices align with ethical standards, it is essential to adopt frameworks prioritizing data dignity, which calls for treating user data as an extension of personal identity, requiring responsible and ethical handling throughout the data collection and processing lifecycle.
Delivery riders belong to crowd workers in the gig economy, representing a vulnerable group. Their privacy concerns and protection have not been duly investigated. To address this research problem, we surveyed to examine the issue of crowdsourced delivery riders' privacy concerns in China. It was found that these riders had often experienced privacy breaches and expressed major privacy concerns, such as the leakage of facial recognition information and contact details. Moreover, they lacked sufficient awareness of the Crowdwork platform's surveillance and knowledge of the Personal Information Protection Law (PIPL) in China. It is suggested that PIPL target vulnerable groups in addition to the general public, and privacy research in Human‐Computer Interaction (HCI) in China should focus on vulnerable populations like crowdsourced delivery riders.
Data-driven political campaigning strategies often remain a black box for citizens; however, educational interventions provide a means to enhance understanding, conscious evaluations, and skills. In this context, we term this combination digital campaign competence (DCC). We conducted an online pre-registered experiment in Austria ( N = 553) using a 2 × 2 between-subject design to compare intervention formats (reading a voter guide vs. playing a campaign game) and content framing (emphasizing risks vs. benefits of data-driven campaigning) plus a control condition. Results show no significant differences in framing on DCC. However, variations are observed among different formats, with the non-interactive voter guide proving to be the most effective one. Contrary to our expectations, the voter guide emphasizing the risks of data-driven political campaigning enhanced conceptual understanding levels, influenced evaluative perceptions, and aided skill development to detect highly targeted ads. We argue that innovative interventions do not always guarantee success in enhancing competencies.
Abstract: Relationships between humans and artificial intelligence (AI) raise new concerns about privacy. AI raises new threats to privacy as it becomes more like humans in language and appearance, more observant, and more inferentially powerful. As humans increasingly form relationships with AI, we expose ourselves in new ways to technology that we don't fully understand. Further, if AI is given the capacity for some type of awareness, it may be able to infringe privacy in radically new ways. Drawing from recent empirical work in psychology and from the contextual integrity theory of privacy, this article analyzes some of the ways that human-AI relationships may threaten values that privacy functions to promote. We then propose six tentative policies to guide the design and development of AI products to mitigate these threats to privacy. Relationships between humans and artificial intelligence (AI) raise new concerns about privacy. AI raises new threats to privacy as it becomes more like humans in language and appearance, more observant, and more inferentially powerful. As humans increasingly form relationships with AI, we expose ourselves in new ways to technology that we don't fully understand. Further, if AI is given the capacity for some type of awareness, it may be able to infringe privacy in radically new ways. Drawing from recent empirical work in psychology and from the contextual integrity theory of privacy, this article analyzes some of the ways that human-AI relationships may threaten values that privacy functions to promote. We then propose six tentative policies to guide the design and development of AI products to mitigate these threats to privacy. [Pre-print. Under review]
The rapid adoption of digital technologies during COVID-19 lockdowns offers a unique perspective on differences in privacy cultures. In this study, we compare how cultural predisposition and identities relate to privacy during the transition to remote learning in higher education in Estonia, France, and Israel. We conducted 83 in-depth interviews with academics, who talked about their adoption of communication technologies and strategies for managing their self-presentation and relations with others. Patterns of tech adoption were most reflective of distinct privacy predispositions, with those coming from privacy-sensitive cultures conveying an individual and institutional resistance to privacy-invasive technologies. However, strategies for self-management in response to new patterns of visibility were similar across countries. Our findings make three contributions to privacy research: they (1) show how different identities (professional, national) underpin privacy attitudes and behaviors; (2) demonstrate the multidimensionality of privacy; and (3) point to institutional decision-making as the critical point for privacy-protecting interventions.
Little is known about the context sensitivity of users' online security perceptions and behaviors to national and individual attributes, and there is inadequate research about the spectrum of users' behaviors in dealing with online security threats. In addressing this gap, this paper draws on two complementary theoretical bases: (1) the contextualization of the protection motivation theory (PMT) to online security behavior and (2) a polycontextual lens for the cross-national comparison of users' security behaviors in the United States and China. The conceptualized model is tested based on 718 survey observations collected from the United States and China. The results support our model and show the divergence between the United States, an exemplar of modern Western society, and China, an exemplar of traditional Eastern society, in forming threat perceptions and in seeking help and avoidance as coping behaviors. Our results also uncovered the significant moderating impacts of espoused culture on the way perceptions of security threats and coping appraisals influence security behaviors. Our findings underline the importance of context-sensitive theory building in security research and provide insights into the motivators and moderators of individuals' online security behaviors in the two nations.
This meta-analysis examined how demand and resource correlates and behavioral and attitudinal correlates were related to each of the 3 dimensions of job burnout. Both the demand and resource correlates were more strongly related to emotional exhaustion than to either depersonalization or personal accomplishment. Consistent with the conservation of resources theory of stress, emotional exhaustion was more strongly related to the demand correlates than to the resource correlates, suggesting that workers might have been sensitive to the possibility of resource loss. The 3 burnout dimensions were differentially related to turnover intentions, organizational commitment, and control coping. Implications for research and the amelioration of burnout are discussed.
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Mental fatigue is often characterized by reduced motivation for effortful activity and impaired task performance. We used subjective, behavioral (performance), and psychophysiological (P3, pupil diameter) measures during an n-back task to investigate the link between mental fatigue and task disengagement. After 2 h, we manipulated the rewards to examine a possible reengagement effect. Analyses showed that, with increasing fatigue and time-on-task, performance, P3 amplitude, and pupil diameter decreased. After increasing the rewards, all measures reverted to higher levels. Multilevel analysis revealed positive correlations between the used measures with time-on-task. We interpret these results as support for a strong link between task disengagement and mental fatigue.
This third version of the MBI was developed across several occupations and countries, in order to assess burnout in all occupations. It was originally published in 1996 by CPP, but is now published and distributed online by Mind Garden (www.mindgarden.com/products/mbi.htm)
oblem: Partial Least Squares (PLS), a form of structural equation modeling (SEM), can provide much value for causal inquiry in communication-related and behavioral research fields. Despite the wide availability of technical information on PLS, many behavioral and communication researchers often do not use PLS in situations in which it could provide unique theoretical insights. Moreover, complex models comprising formative (causal) and reflective (consequent) constructs are now common in behavioral research, but they are often mis-specified in statistical models, resulting in erroneous tests. Key concepts: First-generation techniques, such as correlations, regressions, or difference of means tests (e.g., ANOVA or t-tests), offer limited modeling capabilities, particularly in terms of causal modeling. In contrast, second-generation techniques (i.e., covariance-based SEM or PLS) offer extensive, scalable, and flexible causal-modeling capabilities. Second-generation techniques do not invalidate the need for first-generation techniques, however. The key point of second-generation techniques is that they are superior for the complex causal modeling that dominates recent communication and behavioral research. Key lessons: For exploratory work, or for studies that include formative constructs, PLS should be selected. For confirmatory work, either covariance-based SEM or PLS may be used. Despite claims that lower sampling requirements exist for PLS, inadequate sample sizes result in the same problems for either technique. Implications: SEM’s strength is in modeling. In particular, SEM allows for complex models that include latent (unobserved) variables, formative variables, chains of effects (mediation), and multiple group comparisons of these more complex relationships.
While information privacy has been studied in multiple disciplines over the years, the advent of the information age has both elevated the importance of privacy in theory and practice, and increased the relevance of information privacy literature for Information Systems, which has taken a leading role in the theoretical and practical study of information privacy. There is an impressive body of literature on information privacy in IS, and the two Theory and Review articles in this issue of MIS Quarterly review this literature. By integrating these two articles, this paper evaluates the current state of the IS literature on information privacy (where are we now?) and identifies promising research directions for advancing IS research on information privacy (where should we go?). Additional thoughts on further expanding the information privacy research in IS by drawing on related disciplines to enable a multidisciplinary study of information privacy are discussed.
Structural Equation Modeling (SEM) and MIS Quarterly (MISQ) journals jointly invited researchers to submit their papers on partial least square (PLS). Two papers out of 18 submitted were selected and one paper was accepted for publication in MISQ. The first article by Wetzels, Odekerken-Schroder, and van Oppen, entitled 'Using PLS Path Modeling for Assessing Hierarchical Construct Models: Guidelines and Empirical Illustration,' demonstrates how PLS can be used to create hierarchical constructs. The second article, 'Assessing Between-Group Differences in Information Systems Research: A Comparison of Covariance-and Component-based SEM,' by Qureshi and Compeau studies the conditions that are most appropriate for applying alternative approaches to determine the presence or absence of between group differences. The authors create a baseline case with fixed path coefficients in each of the approaches and then generates comparison models to produce differences in path coefficients at five different effect sizes.
Structural equation modeling (SEM) has become a quasi-standard in marketing and management research when it comes to analyzing the cause-effect relations between latent constructs. For most researchers, SEM is equivalent to carrying out covariance-based SEM (CB-SEM). While marketing researchers have a basic understanding of CB-SEM, most of them are only barely familiar with the other useful approach to SEM-partial least squares SEM (PLS-SEM). The current paper reviews PLS-SEM and its algorithm, and provides an overview of when it can be most appropriately applied, indicating its potential and limitations for future research. The authors conclude that PLS-SEM path modeling, if appropriately applied, is indeed a "silver bullet" for estimating causal models in many theoretical models and empirical data situations.
This chapter evaluates a model of the organizational context of burnout with direct reference to a new measure, the Areas of Worklife Scale (AWS). The model proposes a structured framework for considering six areas of worklife – workload, control, reward, community, fairness, and values – that have resonated through the literature on burnout over the previous two decades. The chapter presents extensive data on the AWS, testing a model of the six areas’ interrelationships as well as their overall relationship to the three aspects of burnout. The results of these analyses are discussed in reference to the psychometric qualities of the measure and the implications of a structured approach to work environments for future development of research on burnout. Implications for developing workplace interventions are also considered.
This meta-analysis integrates the correlations of 77 studies on V. H. Vroom's (1964) original expectancy models and work-related criteria. Correlations referring to predictions with the models and the single components—valence, instrumentality, and expectancy—were included in relation to 5 types of criterion variables: performance, effort, intention, preference, and choice. Within-subjects correlations and between-subjects correlations were included separately. Overall, the average correlations were somewhat lower than reported in previous narrative reviews. In certain categories, moderators pertaining to the measurement of the concepts were analyzed with a hierarchical linear model, but these moderators did not explain heterogeneity. The results show a differentiated overview: the use of the correlational material for the validity of expectancy theory is discussed.
In Study 1, over 200 college students estimated how much their own chance of experiencing 42 events differed from the chances of their classmates. Overall, Ss rated their own chances to be significantly above average for positive events and below average for negative events. Cognitive and motivational considerations led to predictions that degree of desirability, perceived probability, personal experience, perceived controllability, and stereotype salience would influence the amount of optimistic bias evoked by different events. All predictions were supported, although the pattern of effects differed for positive and negative events. Study 2 with 120 female undergraduates from Study 1 tested the idea that people are unrealistically optimistic because they focus on factors that improve their own chances of achieving desirable outcomes and fail to realize that others may have just as many factors in their favor. Ss listed the factors that they thought influenced their own chances of experiencing 8 future events. When such lists were read by a 2nd group of Ss, the amount of unrealistic optimism shown by this 2nd group for the same 8 events decreased significantly, although it was not eliminated. (22 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
In this paper, the authors show that PLS path modeling can be used to assess a hierarchical construct model. They pro-vide guidelines outlining four key steps to construct a hier-1 Carol Saunders was the accepting senior editor for this paper. archical construct model using PLS path modeling. This approach is illustrated empirically using a reflective, fourth-order latent variable model of online experiential value in the context of online book and CD retailing. Moreover, the guidelines for the use of PLS path modeling to estimate parameters in a hierarchical construct model are extended beyond the scope of the empirical illustration. The findings of the empirical illustration are used to discuss the use of covariance-based SEM versus PLS path modeling. The authors conclude with the limitations of their study and suggestions for future research.
Burnout is a prolonged response to chronic emotional and interpersonal stressors on the job, and is defined by the three dimensions of exhaustion, cynicism, and inefficacy. The past 25 years of research has established the complexity of the construct, and places the individual stress experience within a larger organizational context of people's relation to their work. Recently, the work on burnout has expanded internationally and has led to new conceptual models. The focus on engagement, the positive antithesis of burnout, promises to yield new perspectives on interventions to alleviate burnout. The social focus of burnout, the solid research basis concerning the syndrome, and its specific ties to the work domain make a distinct and valuable contribution to people's health and well-being.
The job demands-resources (JD-R) model was used to examine the relationship between job characteristics, burnout, and (other-ratings of) performance (N = 146). We hypothesized that job demands (e.g., work pressure and emotional demands) would be the most important antecedents of the exhaustion component of burnout, which, in turn, would predict in-role performance (hypothesis 1). In contrast, job resources (e.g., autonomy and social support) were hypothesized to be the most important predictors of extra-role performance, through their relationship with the disengagement component of burnout (hypothesis 2). In addition, we predicted that job resources would buffer the relationship between job demands and exhaustion (hypothesis 3), and that exhaustion would be positively related to disengagement (hypothesis 4). The results of structural equation modeling analyses provided strong support for hypotheses 1, 2, and 4, but rejected hypothesis 3. These findings support the JD-R model's claim that job demands and job resources initiate two psychological processes, which eventually affect organizational outcomes. © 2004 Wiley Periodicals, Inc.
The rapid spread of technological innovations like mobile data services (MDS) has made mobile computing a fact of everyday life for many people. Therefore, we need to understand the contribution of mobile computing to overall quality of life (QoL). Employing the satisfaction hierarchy model and bottom-up spillover theory, this study proposes a theoretical model in the context of MDS that connects user satisfaction (a traditional outcome variable of IT) with contribution to QoL (a new outcome variable for mobile computing) in a range of life domains. The validity of the proposed model and outcome variable was tested through three empirical studies conducted in Korea. User satisfaction with MDS was found to affect the contribution of MDS to QoL in eleven life domains, and these contributions in turn influenced the overall contribution of MDS to QoL. The paper ends with a discussion of the study's implications and limitations.
Ease of information flow is both the boon and the bane of large-scale, decentralized systems like the World Wide Web. For all the benefits and opportunities brought by the information revolution, with that same revolution have come the challenges of inappropriate use. Such excesses and abuses in the use of information are most commonly viewed through the lens of information security. This paper argues that debates over online privacy, copyright, and information policy questions have been overly dominated by the access restriction perspective. Our alternative is to design systems that are oriented toward information accountability and appropriate use, rather than information security and access restriction. Our goal is to extend the Web architecture to support transparency and accountability.
Based on focus group interviews, we considered how young adults’ attitudes about privacy can be reconciled with their online behavior. The “privacy paradox” suggests that young people claim to care about privacy while simultaneously providing a great deal of personal information through social media. Our interviews revealed that young adults do understand and care about the potential risks associated with disclosing information online and engage in at least some privacy-protective behaviors on social media. However, they feel that once information is shared, it is ultimately out of their control. They attribute this to the opaque practices of institutions, the technological affordances of social media, and the concept of networked privacy, which acknowledges that individuals exist in social contexts where others can and do violate their privacy.
Warning messages are fundamental to users’ security interactions. Unfortunately, they are largely ineffective, as shown by prior research. A key contributor to this failure is habituation: decreased response to a repeated warning. Previous research has only inferred the occurrence of habituation to warnings, or measured it indirectly, such as through the proxy of a related behavior. Therefore, there is a gap in our understanding of how habituation to security warnings develops in the brain. Without direct measures of habituation, we are limited in designing warnings that can mitigate its effects. In this study, we use neurophysiological measures to directly observe habituation as it occurs in the brain and behaviorally. We also design a polymorphic warning artifact that repeatedly changes its appearance in order to resist the effects of habituation. In an experiment using functional magnetic resonance imaging (fMRI; n = 25), we found that our polymorphic warning was significantly more resistant to habituation than were conventional warnings in regions of the brain related to attention. In a second experiment (n = 80), we implemented the four most resistant polymorphic warnings in a realistic setting. Using mouse cursor tracking as a surrogate for attention to unobtrusively measure habituation on participants’ personal computers, we found that polymorphic warnings reduced habituation compared to conventional warnings. Together, our findings reveal the substantial influence of neurobiology on users’ habituation to security warnings and security behavior in general, and we offer our polymorphic warning design as an effective solution to practice
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.
There is scant research on the broader outcomes of IT in users’ life contexts beyond adoption. This study uses a goal hierarchy approach to deepen our understanding of the relationship between the use of Facebook and psychological well-being (PWB) in young adults. The study applies a mixed-method design that combines means-end analysis and regression analysis to examine data collected from laddering interviews with 161 Facebook users. The means-end chain analysis provided knowledge of the hierarchical goal structure in Facebook (i.e., activities → mediated goals → ultimate goals). Regression analysis was used to identify the relationships between the ultimate goals of Facebook use (e.g., psychological stability, belongingness) and the dimensions of PWB (e.g., self-acceptance, autonomy). The findings explain the significant association of Facebook use with well-being and the dual outcomes of enjoyment (positive in SNS; negative in users’ lives). Prior research focused on relationships among abstract factors, but this study delivers a more specific and nuanced explanation of user behavior on SNSs by providing knowledge of how specific Facebook activities relate to goals and PWB.
Security fatigue has been used to describe experiences with online security. This study identifies the affective manifestations resulting from decision fatigue and the role it plays in users' security decisions. A semistructured interview protocol was used to collect data (N = 40). Interview questions addressed online activities; computer security perceptions; and the knowledge and use of security icons, tools, and terminology. Qualitative data techniques were used to code and analyze the data identifying security fatigue and contributing factors, symptoms, and outcomes of fatigue. Although fatigue was not directly part of the interview protocol, more than half of the participants alluded to fatigue in their interviews. Participants expressed a sense of resignation, loss of control, fatalism, risk minimization, and decision avoidance, all characteristics of security fatigue. The authors found that the security fatigue users experience contributes to their cost-benefit analyses in how to incorporate security practices and reinforces their ideas of lack of benefit for following security advice.
Based upon the stressor-strain-outcome framework, this study proposes that perceived system feature overload, information overload, and social overload are stressors which induce strain, in terms of social network fatigue and dissatisfaction. Both of social network fatigue and dissatisfaction further influence discontinuous use intention. The empirical results indicate that three types of perceived overload exert greater effects on social network fatigue than dissatisfaction, both of which further increase users’ intention of discontinuance. The study also finds that demographic characteristics, such as gender and age, also have moderating effects on these relationships.
The Web form is the primary method of collecting personal data from individuals on the Web. Privacy concerns, time spent, and typing effort act as a major deterrent to completing Web forms. Yet consumers regularly provide more data than required. In a field experiment, we recruited 1,500 Web users to complete a form asking for ten items of identity and profile information of varying levels of sensitivity. We manipulated the number of mandatory fields (none vs. two) and the compensation for participation (0.50) to quantify the extent of over-disclosure, the motives behind it, and the resulting costs and privacy invasion. We benchmarked the efficiency of compulsion and incentives in soliciting data against voluntary disclosure alone.We observed a high prevalence of deliberate and unpaid over-disclosure of data. Participants regularly completed more form fields than required, or provided more details than requested. Through careful experimental design, we verified that participants understood that additional data disclosure was voluntary, and the information provided was considered sensitive. In our experiment, we found that making some fields mandatory jeopardised voluntary disclosure for the remaining optional fields. Conversely, monetary incentives for disclosing those same fields yielded positive spillover by increasing revelation ratios for other optional fields. We discuss the implications for commercial website operators, regulators, privacy-enhancing browser standards, and further experimental research in privacy economics.
While many studies have found that perceived usefulness-an extrinsic motivator-is the strongest determinant of using utilitarian systems, others have found that it is less important than perceived enjoyment-an intrinsic motivator-in predicting hedonic system usage. In light of these interesting but mixed findings, our research applies the motivation theory to investigate the effects of extrinsic and intrinsic motivators on system-use behavior in utilitarian, hedonic, and dual-purposed contexts. We then construct associated hypotheses and empirically test them by analyzing data collected from the literature. The results generally confirm our prediction that, in the context of utilitarian systems, extrinsic motivators are more important than intrinsic motivators, whereas, in the context of hedonic systems, intrinsic motivators play a more critical role than extrinsic motivators. The results thus substantiate our contention that, when information systems vary from utilitarian to hedonic, the most important determinants shift from extrinsic to intrinsic motivators. This paper contributes not only to a new application of the motivation theory to IT adoption, but also to an integrated and in-depth analysis of motivators, which may reorient IS scholars toward potentially more fruitful avenues for studying user behavior.
In an always connected communication environment, users of social networking services (SNSs) need to pay continuous attention to the overwhelming volume of social demands from SNSs. These increased energy requirements may cause SNS fatigue, which can lead to physical and psychological strain. Using the transactional theory of stress and coping as the overarching theory, this study regards overload (i.e., stressors) as a core determinant of SNS fatigue (i.e., strain) and identifies three dimensions of overload – information overload, communication overload, and system feature overload. It also includes SNS characteristics as the antecedents of overload.
The data used in this study were collected from 201 individuals through online and offline surveys. Our results show that all three dimensions of overload were significant stressors that influence SNS fatigue. Regarding the predictors of overload, the characteristics of the SNS system significantly influenced the features of system overload, while information equivocality positively influences information overload. However, information relevance was not a significant predictor of information overload and information equivocality was not a significant predictor of communication overload.
Data breach incidents are on the rise, and have resulted in severe financial and legal implications for the affected organizations. We apply the opportunity theory of crime, the institutional anomie theory, and institutional theory to identify factors that could increase or decrease the contextual risk of data breach. We investigate the risk of data breach in the context of an organizations physical location, its primary industry, and the type of data breach that it may have suffered in the past. Given the location of an organization, the study finds support for application of the opportunity theory of crime and the institutional anomie theory in estimating the risk of data breach incidents within a state. In the context of the primary industry in which an organization operates, we find support for the institutional theory and the opportunity theory of crime in estimating risk of data breach incidents within an industry. Interestingly though, support for the opportunity theory of crime is partial. We find that investment in information technology (IT) security corresponds to a higher risk of data breach incidents within both a state and an industry, a result contrary to the one predicted by the opportunity theory of crime. A possible explanation for the contradiction is that investments in IT security are not being spent on the right kind of data security controls, a fact supported by evidence from the industry. The work has theoretical and practical implications. Theories from criminology are used to identify the risk factors of data breach incidents and the magnitude of their impact on the risk of data breach. Insights from the study can help IT security practitioners to assess the risk environment of their firm (in terms of data breaches) based on the firm's location, its industry sector, and the kind of breaches that the firm may typically be prone to.
This study began with the premise that people can use varying degrees of their selves. physically. cognitively. and emotionally. in work role performances. which has implications for both their work and experi ences. Two qualitative. theory-generating studies of summer camp counselors and members of an architecture firm were conducted to explore the conditions at work in which people personally engage. or express and employ their personal selves. and disengage. or withdraw and defend their personal selves. This article describes and illustrates three psychological conditions-meaningfulness. safety. and availabil ity-and their individual and contextual sources. These psychological conditions are linked to existing theoretical concepts. and directions for future research are described. People occupy roles at work; they are the occupants of the houses that roles provide. These events are relatively well understood; researchers have focused on "role sending" and "receiving" (Katz & Kahn. 1978). role sets (Merton. 1957). role taking and socialization (Van Maanen. 1976), and on how people and their roles shape each other (Graen. 1976). Researchers have given less attention to how people occupy roles to varying degrees-to how fully they are psychologically present during particular moments of role performances. People can use varying degrees of their selves. physically, cognitively, and emotionally. in the roles they perform. even as they main tain the integrity of the boundaries between who they are and the roles they occupy. Presumably, the more people draw on their selves to perform their roles within those boundaries. the more stirring are their performances and the more content they are with the fit of the costumes they don. The research reported here was designed to generate a theoretical frame work within which to understand these "self-in-role" processes and to sug gest directions for future research. My specific concern was the moments in which people bring themselves into or remove themselves from particular task behaviors, My guiding assumption was that people are constantly bring ing in and leaving out various depths of their selves during the course of The guidance and support of David Berg, Richard Hackman, and Seymour Sarason in the research described here are gratefully acknowledged. I also greatly appreciated the personal engagements of this journal's two anonymous reviewers in their roles, as well as the comments on an earlier draft of Tim Hall, Kathy Kram, and Vicky Parker.
The US Federal Trade Commission (FTC) has embarked on a series of three workshops on exploring privacy. The first, in December 2009 in Washington, DC, focused on market and regulatory issues; the second, in January in Berkeley, California, examined technological issues; and the third, scheduled for March in Washington again, will focus on possible solutions. But after hearing from more than 70 speakers at two standing-room only workshops, at least one theme is emerging: notice and choice are inadequate tools for protecting information privacy or security.
A proposed Internet of Things system architecture offers a solution to the broad array of challenges researchers face in terms of general system security, network security, and application security.
Privacy has been an enduring concern associated with commercial information technology (IT) applications, in particular regarding the issue of personalization. IT-enabled personalization, while potentially making the user computing experience more gratifying, often relies heavily on the user’s personal information to deliver individualized services, which raises the user’s privacy concerns. We term the tension between personalization and privacy, which follows from marketers exploiting consumers’ data to offer personalized product information, the personalization–privacy paradox. To better understand this paradox, we build on the theoretical lenses of uses and gratification theory and information boundary theory to conceptualize the extent to which privacy impacts the process and content gratifications derived from personalization, and how an IT solution can be designed to alleviate privacy concerns.
Set in the context of personalized advertising applications for smartphones, we propose and prototype an IT solution, referred to as a personalized, privacy-safe application, that retains users’ information locally on their smartphones while still providing them with personalized product messages. We validated this solution through a field experiment by benchmarking it against two more conventional applications: a base non-personalized application that broadcasts non-personalized product information to users, and a personalized, non-privacy safe application that transmits user information to a central marketer’s server. The results show that (compared to the non-personalized application), while personalized, privacy-safe or not increased application usage (reflecting process gratification), it was only when it was privacy-safe that users saved product messages (reflecting content gratification) more frequently. Follow-up surveys corroborated these nuanced findings and further revealed the users’ psychological states, which explained our field experiment results. We found that saving advertisements for content gratification led to a perceived intrusion of information boundary that made users reluctant to do so. Overall our proposed IT solution, which delivers a personalized service but avoids transmitting users’ personal information to third parties, reduces users’ perceptions that their information boundaries are being intruded upon, thus mitigating the personalization–privacy paradox and increasing both process and content gratification.
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.
Employee cynicism is an attitude characterized by frustration, hopelessness, and disillusionment, as well as contempt toward and distrust of business organizations, executives, and/or other objects in the workplace. This paper uses theory on contract violation to help integrate the diverse literature on cynicism and develop plausible propositions concerning some of the predictors and moderators of employee cynicism. First, the pertinent theory and research on cynicism is reviewed. Four specific domains of research are discussed in terms of their relevance to cynicism in an organizational setting. Next, the literature on psychological and implied contracts and their violation is presented as a framework for the study of employee cynicism. Finally, hypothetical linkages between cynicism and specific characteristics of the contemporary workplace are explored, offering propositions for future research.
The statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined. A drawback of the commonly applied chi square test, in addition to the known problems related to sample size and power, is that it may indicate an increasing correspondence between the hypothesized model and the observed data as both the measurement properties and the relationship between constructs decline. Further, and contrary to common assertion, the risk of making a Type II error can be substantial even when the sample size is large. Moreover, the present testing methods are unable to assess a model's explanatory power. To overcome these problems, the authors develop and apply a testing system based on measures of shared variance within the structural model, measurement model, and overall model.
Classic and contemporary methods for analyzing construct validity are compared and contrasted through reanalyses of data from the organizational research literature to establish a basis for assessing the validity of measures used in organizational research. Campbell and Fiske's (1959) criteria are found to be lacking, particularly in their assumptions, diagnostic information, and power. Confirmatory factor analysis (CFA) is shown to overcome most limitations inherent in Campbell and Fiske's procedures. Nevertheless, two potential shortcomings are identified with the CFA method: the confounding of random error with measure-specific variance and the inability to test for interactions between traits and methods. Three alternative methods are presented for addressing the former issue, and the direct product model is described as a solution to the latter. The techniques considered herein go farther than currently used procedures for enhancing our ability to ascertain the validity of variables commonly studied in organizational research.
This longitudinal study examined antecedents and consequences of psychological burnout among 362 teachers and school administrators. Antecedents included red tape, disruptive students and lack of supervisor support. Consequences of burnout included heart symptoms and depressive mood. Respondents completed questionnaires sent to them at their schools at two points in time, one year apart. LISREL analyses indicated that the predictors had significant relationships with burnout levels one year later, and that burnout served as a mediator between the predictors and emotional and physical health outcomes.
begin . . . by making some very general points about the nature of coping / the issue taken up in this first section is how to think about the processes of coping within the framework of behavior in general / this issue has implications for what aspects of coping may be worth research attention
consider how the points made in the first section apply to research investigating the ways in which people cope with serious threats to their [physical] health, using two of our own studies for purposes of illustration / close the chapter with a second look at issues in coping research
stress theory and broader models of behavior / consequences of effort and disengagement / coping as self-regulation / confronting health threats / breast cancer patients (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Impelled by the development of technologies that facilitate collection, distribution, storage, and manipulation of personal consumer information, privacy has become a “hot” topic for policy makers. Commercial interests seek to maximize and then leverage the value of consumer information, while, at the same time, consumers voice concerns that their rights and ability to control their personal information in the marketplace are being violated. However, despite the complaints, it appears that consumers freely provide personal data. This research explores what we call the “privacy paradox” or the relationship between individuals’ intentions to disclose personal information and their actual personal information disclosure behaviors.
Previous research indicates that perceived usefulness is a major determinant and predictor of intentions to use computers in the workplace. In contrast, the impact of enjoyment on usage intentions has not been examined. Two studies are reported concerning the relative effects of usefulness and enjoyment on intentions to use, and usage of, computers in the workplace. Usefulness had a strong effect on usage intentions in both Study 1, regarding word processing software (β=.68), and Study 2, regarding business graphics programs (β=.79). As hypothesized, enjoyment also had a significant effect on intentions in both studies, controlling for perceived usefulness (β=.16 and 0.15 for Studies 1 and 2, respectively). Study 1 found that intentions correlated 0.63 with system usage and that usefulness and enjoyment influenced usage behavior entirely indirectly through their effects on intentions. In both studies, a positive interaction between usefulness and enjoyment was observed. Together, usefulness and enjoyment explained 62% (Study 1) and 75% (Study 2) of the variance in usage intentions. Moreover, usefulness and enjoyment were found to mediate fully the effects on usage intentions of perceived output quality and perceived ease of use. As hypothesized, a measure of task importance moderated the effects of ease of use and output quality on usefulness but not on enjoyment. Several implications are drawn for how to design computer programs to be both more useful and more enjoyable in order to increase their acceptability among potential users.
This article investigates Facebook users' awareness of privacy issues and perceived benefits and risks of utilizing Facebook. Research found that Facebook is deeply integrated in users' daily lives through specific routines and rituals. Users claimed to understand privacy issues, yet reported uploading large amounts of personal information. Risks to privacy invasion were ascribed more to others than to the self. However, users reporting privacy invasion were more likely to change privacy settings than those merely hearing about others' privacy invasions. Results suggest that this lax attitude may be based on a combination of high gratification, usage patterns, and a psychological mechanism similar to third-person effect. Safer use of social network services would thus require changes in user attitude.
Differentiated product models are predicated on the belief that a product's utility can be derived from the summation of utilities for its individual attributes. In one framed field experiment and two natural field experiments, we test this assumption by experimentally manipulating the order of attribute presentation in the product customization process of custom-made suits and automobiles. We find that order affects the design of a suit that people configure and the design and price of a car that people purchase by influencing the likelihood that they will accept the default option suggested by the firm. (c) 2010 by The University of Chicago. All rights reserved..
This paper presents a cognitive-energetical framework for the analysis of effects of stress and high workload on human performance. Following Kahneman's (1973) model, regulation of goals and actions is assumed to require the operation of a compensatory control mechanism, which allocates resources dynamically. A two-level compensatory control model provides the basis for a mechanism of resource allocation through an effort monitor, sensitive to changes in the level of regulatory activity, coupled with a supervisory controller which can implement different modes of performance-cost trade-off. Performance may be protected under stress by the recruitment of further resources, but only at the expense of increased subjective effort, and behavioural and physiological costs. Alternatively, stability can be achieved by reducing performance goals, without further costs. Predictions about patterns of latent decrement under performance protection are evaluated in relation to the human performance literature. Even where no primary task decrements may be detected, performance may show disruption of subsidiary activities or the use of less efficient strategies, as well as increased psychophysiological activation, strain, and fatigue after-effects. Finally, the paper discusses implications of the model for the assessment of work strain, with a focus on individual-level patterns of regulatory activity and coping.
Reluctance to provide personal health information could impede the success of web-based healthcare services. This paper focuses on the role of personal dispositions in disclosing health information online. The conceptual model argues that individuals' intention to disclose such information depends on their trust, privacy concern, and information sensitivity, which are determined by personal dispositions—personality traits, information sensitivity, health status, prior privacy invasions, risk beliefs, and experience—acting as intrinsic antecedents of trust. The data (collected via a lab experiment) and the analysis shed light on the role of personal dispositions. This could assist in enhancing healthcare websites and increase the success of online delivery of health services.
Internet shopping has become the fastest-growing use of the Internet; most online consumers, however, use information gathered online to make purchases off-line. A number of authors have attributed consumers' reluctance to purchase online to apparent barriers; however, such barriers have not been examined within a theoretical context. This study examined the nature of perceived risks associated with Internet shopping and the relationship between types of risk perceived by Internet shoppers and their online patronage behaviors within a perceived risk theoretical framework. The research examined four types of perceived risk that were of concern to Internet shoppers and browsers — financial, product performance, psychological, and time/convenience loss risk, the relationship between the types of risk perceived and selected demographics, and the effect of perceived risks on Internet patronage behaviors. Findings suggest that perceived risk is a useful context to explain barriers to online shopping. A model for examining Internet patronage behavior from a perceived risk framework is proposed; management implications and propositions for future research are also presented.
Organizational information practices can result in a variety of privacy problems that can increase consumers' concerns for information privacy. To explore the link between individuals and organizations regarding privacy, we study how institutional privacy assurances such as privacy policies and industry self-regulation can contribute to reducing individual privacy concerns. Drawing on Communication Privacy Management (CPM) theory, we develop a research model suggesting that an individual's privacy concerns form through a cognitive process involving perceived privacy risk, privacy control, and his or her disposition to value privacy. Furthermore, individuals' perceptions of institutional privacy assurances -- namely, perceived effectiveness of privacy policies and perceived effectiveness of industry privacy self-regulation -- are posited to affect the riskcontrol assessment from information disclosure, thus, being an essential component of privacy concerns. We empirically tested the research model through a survey that was administered to 823 users of four different types of websites: 1) electronic commerce sites, 2) social networking sites, 3) financial sites, and 4) healthcare sites. The results provide support for the majority of the hypothesized relationships. The study reported here is novel to the extent that existing empirical research has not explored the link between individuals' privacy perceptions and institutional privacy assurances. We discuss implications for theory and practice and provide suggestions for future research.
For more than a century, concern for privacy (CFP) has co-evolved with advances in information technology. The CFP refers to the anxious sense of interest that a person has because of various types of threats to the person's state of being free from intrusion. Research studies have validated this concept and identified its consequences. For example, research has shown that the CFP can have a negative influence on the adoption of information technology; but little is known about factors likely to influence such concern. This paper attempts to fill that gap. Because privacy is said to be a part of a more general ‘right to one's personality’, we consider the so-called ‘Big Five’ personality traits (agreeableness, extraversion, emotional stability, openness to experience, and conscientiousness) as factors that can influence privacy concerns. Protection motivation theory helps us to explain this influence in the context of an emerging pervasive technology: location-based services. Using a survey-based approach, we find that agreeableness, conscientiousness, and openness to experience each affect the CFP. These results have implications for the adoption, the design, and the marketing of highly personalized new technologies.