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Increasing incidents of privacy invasion on social networking sites (SNS) are intensifying the concerns among stakeholders about the misuse of personal data. However, there seems to be limited research on exploring the impact of specific privacy concerns on users’ intention to engage in various privacy protection behaviors. This study aims to examine the role of social privacy concerns, institutional privacy concerns and privacy self-efficacy as antecedents of privacy protection–related control activities intention among young adults active on SNS.

Data collected from 284 young adults active on SNS was analyzed through partial least squares structural equation modeling using Smart PLS.

The results indicate that institutional privacy concerns, social privacy concerns and privacy self-efficacy positively influence the control activities intention of SNS users. The extent of privacy self-efficacy and privacy protection-related control activities intention differs among users based on gender.

This study is limited to a population of young adults in the age group of 18–25 years.

The findings of this study form the basis for specific recommendations addressing the different types of privacy concerns experienced by social media users, promoting responsible privacy control behaviors on online platforms and discouraging the possible misuse of information by third parties.

This study validates a theoretical framework that can contribute to future investigations concerning the use of SNS. The study findings form the basis for a set of practical recommendations for policymakers, SNS platforms and users.

In today’s digitized environment, information privacy has become a prime concern for everybody. The purpose of this paper is to provide an understanding of information privacy concern arising because of the application of computer-based information system in the various domains (E-Governance, E-Commerce, E-Health, E-Banking and E-Finance), and at different levels, i.e. individual, group, organizational and societal.

The authors performed an in-depth analysis of different research articles related to information privacy concerns and elements affecting those at certain level of applications. The primary sources of literature were articles retrieved from online databases. Various online journal and scholarly articles were searched in detail to locate information privacy-related articles.

The authors have carried out a detailed literature review to identify the different levels where the privacy is a big challenging task. This paper provides insights whether information privacy concern may obstruct in the successful dispersal and adoption of different applications in various application domains. Consumers’ attitude towards information privacy concerns have enlightened and addressed at individual levels in numerous domains. Privacy concerns at the individual level, as suggested by our analysis, seem to have been sufficiently addressed or addressed. However, information privacy concerns at other levels – group, organizational and societal levels – need the attention of researchers.

In this paper, the authors have posited that it will help the researchers to more focus at group level privacy perspective in the information privacy era.

The purpose of this paper is to improve the understanding of cloud service users’ privacy concerns, which are anticipated to considerably hinder cloud service market growth. The researchers have explored privacy concerns from dimensions that were identified as relevant in the cloud context.

Content analysis was used to identify privacy problems that were most often raised in previous cloud research. Multidimensional developmental theory (MDT) was used to build a conceptual model of cloud privacy concerns. Literature review was made to identify the privacy-related constructs used to measure privacy concerns in previous cloud research.

The paper provides systematization of recent cloud privacy research, proposal of a conceptual model of cloud privacy concerns, identification of measuring instruments that were used to measure privacy concerns in previous cloud research and identification of categories of problems that need to be addressed in future cloud research.

This paper has identified the categories of privacy problems and dimensions that have not yet been measured in the cloud context, to the best of the authors’ knowledge. Their simultaneous examination could clarify the effects of different dimensions on the privacy concerns of cloud users. The conceptual model of cloud privacy concerns will allow cloud service providers to focus on key cloud problems affecting users’ privacy concerns and use the most appropriate privacy protection communication and preservation approaches.

This study investigated the attitudes and concerns of Saudi higher educational institution (HEI) academics about privacy and security in online teaching during the COVID-19 pandemic.

Online Questionnaire questionnaire was designed to explore Saudi HEI academic’s attitudes and concerns about privacy and security issues in online teaching. The questionnaire asked about attitudes and concerns held before the pandemic and since the pandemic. The questionnaire included four sections. At the beginning of the questionnaire, participants were asked what the phrase “online privacy and security” meant to them, to gain an initial understanding of what it meant to academics. A definition for what we intended for the survey was then provided: “that a person’s data, including their identity, is not accessible to anyone other than themselves and others whom they have authorised and that their computing devices work properly and are free from unauthorised interference” (based on my reading of a range of sources, e.g. Schatz et al., 2017; Steinberg, 2019; NCS; Windley, 2005). This was to ensure that participants did understand what I was asking about in subsequent sections.

This study investigated the attitudes and concerns of Saudi HEI academics about privacy and security in online teaching during the COVID-19 pandemic. The findings provide several key insights: Key aspects of online privacy and security for Saudi HEI academics: Saudi HEI academic’s notion of online privacy and security is about the protection of personal data, preventing unauthorized access to data and ensuring the confidentiality and integrity of data. This underscores the significance of robust measures to safeguard sensitive information in online teaching, but also the need to make academics aware of the other aspects of online privacy and security. Potential to improve policies and training about online privacy and security in Saudi HEIs: Although many participants were aware of the online privacy and security policies of their HEI, only a small percentage had received training in this area. Thus, there is a need to improve the development and dissemination of policies and to provide academics with appropriate training in this area and encourage them to take available training. Use of videoconferencing and chat technologies and cultural sensitivities: The study highlighted moderate levels of concern among Saudi HEI academics regarding the use of videoconferencing and online chat technologies, and their concerns about cultural factors around the use of these technologies. This emphasizes the need for online teaching and the growing use of technologies in such teaching to respect cultural norms and preferences, highlighting the importance of fostering a culturally sensitive approach to technology deployment and use. Surprising low webcam use: An unexpected finding is the low use of webcams by both academics and students during online teaching sessions, prompting a need for a deeper understanding of the dynamics surrounding webcam engagement in such sessions. This calls for a reevaluation of the effectiveness of webcam use in the teaching process and underscores the importance of exploring methods for enhancing engagement and interaction in online teaching. In summary, this paper investigated the attitudes and concerns about privacy and security in the online teaching of Saudi HEI academics during the coronavirus pandemic. The study reveals areas where further research and policy development can enhance the online teaching experience. As the education landscape continues to evolve, institutions must remain proactive in addressing the concerns of their academics while fostering a culturally sensitive approach to technology deployment.

One limitation of this study is the relatively small qualitative data sample, despite the adequate size of the sample including 36 academics from various Saudi Arabian HEIs for quantitative analysis. It was necessary to make the most of the open-ended questions optional – participants did not have to answer about concerns if they did not want to, as we did not want to make the questionnaire too long and onerous to complete. Consequently, the number of academics responding to the open-ended questions was limited, emphasizing the need for additional data and alternative research methods to further these issues. The study was focused on investigating the concerns of HEI Saudi academics, recognizing that the attitudes and concerns of academics in other countries may differ. Furthermore, the research also includes an exploration of the changes in academic attitudes and concerns before and since the COVID-19 pandemic, which will be the subject of further data analysis.

This research delves into Saudi HEI academics' perceptions and concerns regarding privacy and security in online education during the COVID-19 Pandemic. Notably, it highlights the moderate priority placed on online privacy and security, the unexpectedly low usage of webcams and the potential for enhancing policies and training. The study emphasizes the necessity for comprehensive measures to protect sensitive data and the importance of tailored policies for educators. It also underscores the need for a more nuanced understanding of webcam usage dynamics, offering valuable insights for institutions aiming to improve online education and address educators' concerns amidst evolving educational landscapes.

This study aims to explore US hotel guests’ privacy concerns with a twofold aim as follows: to investigate the privacy categories, themes and attributes most commonly discussed by guests in their reviews and to examine the influence of cultural proximity on privacy concerns.

This study combined automated text analytics with content analysis. The database consisted of 68,000 hotel reviews written by US guests lodged in different types of hotels in five European cities. Linguistic Inquiry Word Count, Leximancer and SPSS software were used for data analysis. Automated text analytics and a validated privacy dictionary were used to investigate the reviews by exploring the categories, themes and attributes of privacy concerns. Content analysis was used to analyze the narratives and select representative snippets.

The findings revealed various categories, themes and concepts related to privacy concerns. The two most commonly discussed categories were privacy restriction and outcome state. The main themes discussed in association with privacy were “room,” “hotel,” “breakfast” and several concepts within each of these themes were identified. Furthermore, US guests showed the lowest levels of privacy concerns when staying at American hotel chains as opposed to non-American chains or independent hotels, highlighting the role of cultural proximity in privacy concerns.

Hotel managers can benefit from the results by improving their understanding of hotel and service attributes mostly associated with privacy concerns. Specific suggestions are provided to hoteliers on how to increase guests’ privacy and on how to manage issues related to cultural distance with guests.

This study contributes to the hospitality literature by investigating a neglected issue: on-site hotel guests’ privacy concerns. Using an unobtrusive method of data collection and text analytics, this study offers valuable insights into the categories of privacy, the most recurrent themes in hotel guests’ reviews and the potential relationship between cultural proximity and privacy concerns.

The adoption of social media has been extensively discussed. However, to explain the adoption of traditional social media, considering the benefits and risks accumulated from the experiences of social media use, the extent literature is limited. Thus, this paper investigated the act of traditional social media users’ switching behavior from a dynamic perspective and the level of information privacy concerns and social media privacy to measure the risks and benefit accumulated from this dynamic process.

This study of Facebook and Twitter users, who are regarded as representative of traditional social media, are selected as research targets surveyed and were required to answer a specially designed questionnaire in order to determine their general feeling on social media platforms they currently use. As a part of this process, quota sampling was used to collect different samples based on gender and age. In this paper, t-test, one-way ANOVA and multiple comparisons were used for the statistical analysis, conducted through SPSS.

Information privacy concerns and social media dependency affect the adoption of social media. Secondly, social media dependency is a more salient determinant for social media adoption. Therefore, social media firms should pay more attention to enhancing user dependency of social media by increasing user involvement of social media.

This study intends to conduct a research design that provides an overall and holistic understanding of user usage experience. To do this, it investigates the intensity of switching behavior through the level of dependency and the level of information privacy concern that users inevitably exhibit through the use of social media over long time.

This paper aims to empirically examine the impact of psychological factors (i.e. privacy and intrusiveness concerns) on user intentions regarding artificial intelligence (AI)-enabled social commerce applications at their core through perceived usefulness. The theoretical model is supported by the theory of planned behaviour (TPB).

Data was gathered from 488 social media users in Saudi Arabia.

Privacy concerns significantly affect perceived usefulness. Furthermore, the link between privacy concerns and behavioural intentions was mediated by perceived usefulness.

Business leaders should raise users’ awareness about the effectiveness of AI-powered tools that can influence their behavioural intentions. Furthermore, managers must be aware of the regulations that protect user privacy, track online activity and offer secure communication channels.

This paper expands on TPB by bridging the theoretical and practical divide. It further develops a theoretical framework for practitioners to better understand customers’ physiological aspects of using AI-powered social commerce platforms.

Este artículo examina empíricamente el impacto de los factores psicológicos (es decir, preocupaciones de privacidad e intrusión) en las intenciones de los usuarios con respecto a las aplicaciones de comercio social habilitadas con inteligencia artificial (IA) en su núcleo a través de la utilidad percibida. El modelo teórico se sustenta en la teoría del comportamiento planificado (TPB).

Los datos se recopilaron de 488 usuarios de redes sociales en Arabia Saudita.

Las preocupaciones sobre la privacidad afectan significativamente la utilidad percibida. Además, el vínculo entre las preocupaciones por la privacidad y las intenciones de comportamiento estuvo mediado por la utilidad percibida.

Los líderes empresariales deberían concienciar a los usuarios sobre la eficacia de las herramientas impulsadas por la IA que pueden influir en sus intenciones de comportamiento. Además, los gerentes deben conocer las regulaciones que protegen la privacidad de los usuarios, rastrear la actividad en línea y ofrecer canales de comunicación seguros.

Este artículo amplía el TPB cerrando la brecha teórica y práctica. Además, desarrolla un marco teórico para que los profesionales comprendan mejor los aspectos fisiológicos de los clientes al utilizar plataformas de comercio social impulsadas por IA.

本文透過實證研究了心理因素 (即隱私和侵入性問題) 對人工智慧 (AI) 驅動的社交商務應用程式的使用者意圖的影響, 其核心是透過感知有用性。 此理論模型得到計劃行為理論 (TBP) 的支持。

資料收集自沙烏地阿拉伯的 488 名社群媒體用戶。

隱私問題顯著影響感知的用處。 此外, 隱私問題和行為意圖之間的連結是透過感知有用性來調節的。

企業領導者應該提高使用者對人工智慧工具有效性的認識, 這些工具可以影響他們的行為意圖。 此外, 管理人員必須了解保護用戶隱私、追蹤線上活動並提供安全通訊管道的法規。

本文透過彌合理論和實踐鴻溝，對 TPB 進行了擴展。 它進一步為從業者開發了一個理論框架，以便更好地了解使用人工智慧驅動的社交商務平台的客戶的生理方面。

Studies on the coronavirus disease 2019 (COVID-19) tracing apps have mostly focused on how to optimize adoption and continuous use, but did not consider potential long-term effects of their introduction. This study aims to analyse whether the characteristics of the recent introduction of tracing apps may negatively impact individuals' attitudes and intentions to adopt future tracking technology.

In an online experiment across three countries (Australia, Germany, UK), the authors measured how perceived benefits of COVID-19 tracing apps as well as specific government and campaign-related factors affect privacy concerns, attitude towards future tracking apps and intention to adopt. The authors manipulated the type of provider (governmental vs private) and the type of beneficiaries of the future tracking technology app (the individual alone or also the public) as determinants of adoption.

The authors find that privacy concerns towards the COVID-19 tracing apps negatively impact attitude and intention to adopt future tracking apps. Future adoption is more likely if the app is provided by the government, whereas additional benefits to the public do not positively stimulate adoption. Second, the study analyzed different factors, including perceptions on governments and the app introduction, as well as perceived benefits.

Taking the introduction of COVID-19 apps in different countries as a basis, the authors link both perceived benefits and contextual factors to privacy concerns, attitudes towards and intention to adopt the related technology in the future. The authors hereby clarify the responsibility of governmental actors who conduct large-scale technology introductions for the future diffusion of related technologies.

To cope with the COVID-19 pandemic, contact tracing mobile apps (CTMAs) have been developed to trace contact among infected individuals and alert people at risk of infection. To disrupt virus transmission until the majority of the population has been vaccinated, achieving the herd immunity threshold, CTMA continuance usage is essential in managing the COVID-19 pandemic. This study seeks to examine what motivates individuals to continue using CTMAs.

Following the coping theory, this study proposes a research model to examine CTMA continuance usage, conceptualizing opportunity appraisals (perceived usefulness and perceived distress relief), threat appraisals (privacy concerns) and secondary appraisals (perceived response efficacy) as the predictors of individuals' CTMA continuance usage during the pandemic. In the United States, an online survey was administered to 551 respondents.

The results revealed that perceived usefulness and response efficacy motivate CTMA continuance usage, while privacy concerns do not.

This study enriches the understanding of CTMA continuance usage during a public health crisis, and it offers practical recommendations for authorities.

This paper aims to explore the overall research question “How can artificial intelligence (AI) influence consumer information disclosure?”. It considers how anthropomorphism of AI, personalisation and privacy concerns influence consumers’ attitudes and encourage disclosure of their private information.

This research draws upon the personalisation-privacy paradox (PPP) and privacy calculus theory (PCT) to address the research question and examine how AI can influence consumer information disclosure. It is proposed that anthropomorphism of AI and personalisation positively influence consumer attitudes and intentions to disclose personal information to a digital assistant, while privacy concerns negatively affect attitude and information disclosure.

This paper develops a conceptual model based on and presents seven research propositions (RPs) for future research.

Building upon PPP and PCT, this paper presents a view on the benefits and drawbacks of AI from a consumer perspective. This paper contributes to literature by critically reflecting upon on the question how consumer information disclosure is influenced by AI. In addition, seven RPs and future research areas are outlined in relation to privacy and consumer information disclosure in relation to AI.

El papel del antropomorfismo, la personalización y los problemas de privacidad y perspectivas para la investigación futura

Resumen

Este artículo explora la pregunta general de investigación “¿Cómo puede influir la inteligencia artificial (IA) en la divulgación de información por parte de los consumidores? Se analiza cómo el antropomorfismo de la IA, la personalización y la preocupación por la privacidad influyen en la actitud de los consumidores y fomentan la revelación de su información privada.

Esta investigación se basa en la paradoja de la personalización y la privacidad y en la teoría del cálculo de la privacidad para abordar la pregunta de investigación y examinar cómo la IA puede influir en la revelación de información de los consumidores. Se propone que el antropomorfismo de la IA y la personalización influyen positivamente en las actitudes de los consumidores y en su intención de revelar información personal a un asistente digital, mientras que la preocupación por la privacidad afecta negativamente a la actitud y a la revelación de información.

Este artículo desarrolla un modelo conceptual basado en siete propuestas de investigación para el futuro.

Basándose en la paradoja de la personalización y la privacidad y en la teoría del cálculo de la privacidad, este artículo presenta un punto de vista sobre los beneficios e inconvenientes de la IA desde la perspectiva del consumidor. Este artículo contribuye a la literatura al reflexionar de forma crítica sobre la cuestión de cómo influye la IA en la revelación de información del consumidor. Además, se esbozan siete propuestas de investigación y futuras áreas de investigación en relación con la privacidad y la divulgación de información del consumidor en relación con la IA.

鼓励消费者分享他们的秘密？拟人化、个性化和隐私问题的作用以及未来研究的途径

摘要

本文探讨了 “人工智能如何影响消费者的信息披露？"这一总体研究问题。它考虑了人工智能（AI）的拟人化、个性化和隐私问题是如何影响消费者的态度并鼓励他们披露私人信息的。

本研究借鉴了个性化-隐私悖论和隐私计算理论来解决研究问题, 并研究人工智能如何影响消费者信息披露。本文提出, 人工智能的拟人化和个性化对消费者向数字助理披露个人信息的态度和意图有积极影响, 而隐私问题对态度和信息披露有消极影响。

本文在此基础上建立了一个概念模型, 并为未来的研究提出了七个研究命题。

在个性化-隐私悖论和隐私计算理论的基础上, 本文从消费者的角度提出了对人工智能的好处和坏处的看法。本文通过对消费者信息披露如何受到人工智能影响的问题进行批判性反思, 对文献做出了贡献。此外, 本文概述了与人工智能相关的隐私和消费者信息披露方面的七个研究命题和未来研究领域。