The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online
By Gaurav Bansal, F. Zahedi, David Gefen. Decision Support Systems, 2010
999 citations recorded by the source corpus.
Subfields: Information Systems and Management, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/f8e706dca65d83f64b372ac0b657de0b38d7c1a6
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In Information Systems and Management
In Sociology and Political Science
Citations in the corpus
- Blissfully ignorant: the effects of general privacy concerns, general institutional trust, and affect in the privacy calculus (2015, background): “While some authors have conceptualized trust as an antecedent (Wake fi eld, 2013) or as an outcome of privacy concerns (Bansal et al ., 2010), others have argued that trust and privacy concerns are independent factors that may exert separate in fl uences on intentions to disclose information (Dinev &…”
- Impact of Trust and Privacy Concerns on Technology Acceptance in Healthcare: An Indian Perspective (2020, positive): “[11] established that personal disposition indirectly impacts trust through information sensitivity and privacy concern.”
- Investigating the impacting factors for the healthcare professionals to adopt artificial intelligence-based medical diagnosis support system (AIMDSS) (2018, result): “Previous studies demonstrated a significant influence of trust on usage behavior of information technologies, which further supports the argument (Bansal et al. 2010; Chiu et al. 2012; Ke et al. 2009).”
- The role of privacy fatigue in online privacy behavior (2018, background): “Although Internet users can enjoy improved online services with the daily use of information communication technology (ICT), they may face threats associated with personal information misuse (Bansal & Gefen, 2010).”
- Location information disclosure in location-based social network services: Privacy calculus, benefit structure, and gender differences (2015, background): “…of information transparency Willing to be profiled online for personalized services / personalized advertising NA Utility maximization theory Bansal, Zahedi, and Gefen (2010) e-health Health information privacy concern Trust Intention to disclose health information NA Utility theory Privacy…”
- Mobile health technology adoption across generations: Narrowing the digital divide (2018, background): “, 2016), and trust in health websites increases willingness to interact with websites (Bansal et al., 2010).”
- Alexa, she's not human but… Unveiling the drivers of consumers' trust in voice‐based artificial intelligence (2021, background): “It has been found that perceived vulnerability and ability to control (Bansal & Gefen, 2010; Mohamed & Ahmad, 2012), prior experience (Cho et al., 2010), Internet literacy (Dinev & Hart, 2006), policy and regulations (Lwin et al., 2007), business communication (Lwin et al., 2016), and fairness of…”
- Information Privacy Research: An Interdisciplinary Review (2011, background): “Personality differences such as introversion versus extroversion (Lu et al. 2004), independent-self versus interdependent-self (Xu 2007), and “big-five” personality traits7 (Bansal et al. 2010) have been found to affect individual privacy concerns.”
- Information privacy and correlates: an empirical attempt to bridge and distinguish privacy-related concepts (2013, background): “Personality differences such as introversion vs extroversion (Lu et al , 2004), independent-self vs interdependent-self (Xu, 2007), and ‘Big-Five’ personality traits (Bansal et al , 2010) have been found to affect individual privacy concerns.”
- Use of AI-based tools for healthcare purposes: a survey study from consumers’ perspectives (2020, background): “The risk perceptions related to an IS system can reduce the possible utility attached to the technology [50].”