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

Zhang, Fengjiao; Pan, Zhao; Lu, Yaobin

doi:10.1016/j.im.2022.103736

Cited by 38 publications

(19 citation statements)

References 129 publications

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“…Anonymity can also be preferred when sharing good and effective examples with other students (Basso et al, 2016;Biehl et al, 2013;Chang, 2021). Since not revealing the real identity for student privacy supports security in OLC, it has been suggested in the current study and different studies in the literature (Anwar, 2021;Basso et al, 2016;Biehl et al, 2013;Chang, 2021;Garg et al, 2023;Zhang, Luo, et al, 2023;Zhang, Pan, et al, 2023).…”

Section: Discussionmentioning

confidence: 96%

“…In this study, it was obtained from Delphi interviews that not revealing the real identity and using contextual identity can prevent privacy violations. This measure has also been suggested in different studies (Anwar, 2021;Garg et al, 2023;Zhang, Pan, et al, 2023). The possibility of participating in the activities with an anonymous identity keeps the student in a safe environment (Zhang, Luo, et al, 2023).…”

Section: Discussionmentioning

confidence: 99%

“…Experts also suggested that the reliability of the system should be evaluated periodically by all users and that contextual privacy agreements should be defined. To ensure that all users are in a safe learning environment, smart technologies (Farahani & Monsefi, 2023; Schomakers et al, 2022; Zhang, Pan, et al, 2023) can be used to record all their behaviour. As can be seen in the privacy protection suggestions in OLC table, this suggestion was proposed in the Delphi interviews and was determined as ‘Preferring smart technology supported environments’ item.…”

Section: Discussionmentioning

confidence: 99%

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University students' digital spaces in online learning communities: Implications for understanding, protecting and maintaining privacy

Özer Şanal,

Çiçek

2023

Brit J Educational Tech

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In addition to learning effectively and effectively in online learning communities (OLCs), students must be in a secure environment and privacy must be respected. The study aimed to identify privacy violations that university students encounter in OLCs, and identify recommendations and some strategies to implement to ensure privacy at the OLC. A qualitative research method was applied in the study. First, focus group interviews were conducted with a total of 108 students who participated actively in the OLC. After analysing the interview data, a privacy violations report (RPV‐OLC) was prepared at the OLC. According to the RPV‐OLC, a problem description for the Delphi technique was designed and 17 experts were identified for the interview. Delphi panels with experts were completed in 5 months. The content analysis process was used for the data obtained. Students said they encountered information sharing and access, access to information, system/course settings, resistance to negotiations, communication problems and lack of knowledge. On the other hand, experts suggest that different suggestions and strategies could be implemented to ensure privacy in the OLC, such as partial privacy, mutual trust, contextual privacy agreements, role‐based or anonymous identity use, and privacy education. The study focused on defining the concept of privacy and student privacy violations in online learning environments and providing solutions for educators, students and system administrators. Practitioner notesWhat is already known about this topic Digital learning environments pose a threat to the privacy of students. The fact that privacy violations in the OLC can trigger concerns among students has a negative impact on learning processes. There is high interest at the moment in how to plan the most effective teaching in online learning environments—but privacy is being neglected. What this paper adds This article explains the privacy violations university students encounter at the OLC. This document contains guidelines on how to mitigate and prevent privacy violations in OLC. The results of the study also provide suggestions for privacy protection at the OLC. Implications for practice and/or policy It is important that the instructors who participate in the OLC are informed about the necessary measures, rules, principles, activities and follow‐up measures to protect their personal privacy. If we can overcome students' concerns about privacy violations at the OLC, we can create more comfortable learning spaces. The aim of learning should not only be to peak performance; the most important responsibility of educators or system administrators is to preserve each student's private space, while at the same time achieving the best performance.

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Section: Discussionmentioning

confidence: 96%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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University students' digital spaces in online learning communities: Implications for understanding, protecting and maintaining privacy

Özer Şanal,

Çiçek

2023

Brit J Educational Tech

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“…Multi-layered surveillance systems in smart city may involve complex interactions among the stakeholders including citizens and municipality officials (Clarinval et al , 2020). Therefore, the adoption of digitalization and innovation in an urban context may help to improve quality of life for citizens (Ho, 2017), leading to public value (Panagiotopoulos et al , 2019), while addressing citizens’ privacy and security concerns (Ismagilova et al , 2022; Zhang et al , 2022a).…”

Section: Introductionmentioning

confidence: 99%

Citizen empowerment through smart surveillance: evidence from Indian smart cities

Khanna

Khanra

2023

DPRG

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Purpose Citizens often perceive surveillance by government authorities as oppressive and, hence, demonstrate reluctance in value co-creation from such services. This study aims to investigate the challenges and benefits of citizen empowerment through technology-driven surveillance or “smart surveillance.” Design/methodology/approach Guided by Dynamic Capability theory, the authors conduct in-depth interviews with officers in-charge of surveillance in smart cities. Given the contemporary advancements, this approach allows a retrospective and real-time understanding of interviewees’ experiences with smart surveillance. Findings The authors develop five propositions for citizen empowerment through smart surveillance to summarize the findings of this study. Research limitations/implications This study advances the relevance of Dynamic Capability in public administration. Practical implications Smart city authorities and policymakers may leverage the insights provided in this study to design appropriate policies for smart surveillance. Originality/value The authors find that factors such as digital technology and infrastructure, information management, skill divide and perceived return on investment may influence citizen empowerment through smart surveillance.

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“…Existing studies mainly focused on examining the antecedents and consequences of the privacy paradox. On the one hand, researchers have studied the factors affecting the privacy paradox from a technological, organizational, and individual level, and found that technical transparency (Zhang et al, 2023), psychological characteristics (Ying et al, 2023;Tian et al, 2022), privacy cynicism (Tian et al, 2022) and other factors have the significant influence on it. On the other hand, extensive studies believe that the privacy paradox also has a significant influence on individuals' decision-making.…”

Section: Introductionmentioning

confidence: 99%

Privacy paradox resolution in mHealth: the moderating effect of rationality degree

Zhu,

Li,

Yan

et al. 2023

JEIM

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PurposeThe collection and use of personal medical information for mobile health (mHealth) service raise significant privacy concerns. In this context, this study aims to explore the privacy paradox and its impact from the perspective of paradox resolution.Design/methodology/approachBased on social support theory and privacy calculus theory, this study first studies the effect of social support on perceived benefits, and explores the moderating effect of perceived health status on the privacy trade-off process. Secondly, the study examines the path of “privacy concerns – disclosure intention – disclosure behavior” to verify the existence of the privacy paradox. Following this, based on rational choice theory, the rationality degree is introduced as a moderating variable to investigate both its impact on the central route and the strength of this impact on the privacy paradox.FindingsEmpirical results show that informational support and emotional support influence perceived benefits significantly. Perceived benefits significantly influence privacy concerns, and perceived health status has a significant positive moderating effect. The authors further find that there is a privacy paradox within the mHealth context, and the privacy paradox is moderated negatively by rationality degree. The findings indicate that the impact strength of the privacy paradox will decrease with increases in rationality degree.Research limitations/implicationsThe findings indicate that it is crucial to evaluate the privacy paradox and its impact from the perspective of paradox resolution.Originality/valueThis study offers a complete comprehension of the privacy paradox in mHealth and provides several valuable recommendations for enhancing both mHealth services and privacy controls.

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

Cited by 38 publications

References 129 publications

University students' digital spaces in online learning communities: Implications for understanding, protecting and maintaining privacy

University students' digital spaces in online learning communities: Implications for understanding, protecting and maintaining privacy

Citizen empowerment through smart surveillance: evidence from Indian smart cities

Privacy paradox resolution in mHealth: the moderating effect of rationality degree

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