Trust in a specific technology: An investigation of its components and measures

By D. Harrison McKnight, Michelle Carter, Jason Bennett Thatcher, Paul F. Clay. TMIS, 2011

1,174 citations recorded by the source corpus.

Subfields: Communication, Information Systems and Management, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/1581959e828d2701b72702264bca37ca7f408124

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Citations in the corpus

Trust in AI and Its Role in the Acceptance of AI Technologies (2022, methodology): “, 1995) and trust in technology (Mcknight et al., 2011): benevolence/helpfulness, integrity/reliability, and competence/functionality.”
Cognitive Underpinnings of Beliefs and Confidence in Beliefs about Fully Automated Vehicles (2018, background): “Propensity to trust technology Participants completed the 4 item ‘‘faith in general technology” and the 3 item ‘‘trusting stance” subscales constituting the propensity to trust technology (McKnight et al., 2011).”
Trustworthy artificial intelligence (2020, methodology): “…literature suggests a causal ordering among trust constructs, such that an individual ’ s general trusting beliefs in people or technology directly influences institution-based trust and indirectly shapes trust in a specific person or technology (McKnight et al. 2011; McKnight and Chervany 2001).”
Algorithmic bias: review, synthesis, and future research directions (2021, background): “For example, the propensity to trust in technology, including AI and analytics, can shape people’s perceptions and behaviours regarding algorithmic biases (Dodge et al., 2019; Glikson & Woolley, 2020; M. Lee, 2018a; Mcknight et al., 2011; Rossi, 2019; Springer & Whittaker, 2019).”
User Perceptions and Trust of Explainable Machine Learning Fake News Detectors (2022, background): “It is generally independent of trustee and environment characteristics (Mcknight, Carter, Thatcher, & Clay, 2011; Mcknight, Cummings, & Chervany, 1998), but has the strongest predictive power when information about the trustee’s ability, integrity, and benevolence is unclear (Gill, Boies, Finegan,…”
Technology, Humanness, and Trust: Rethinking Trust in Technology (2015, background): “Finally, helpfulness is the conceptual corollary to benevolence and means the belief that the technology will provide adequate and responsive help (McKnight et al., 2011) (Table 1).”
Managing Citizens' Uncertainty in E-Government Services: The Mediating and Moderating Roles of Transparency and Trust (2016, background): “On one hand, accuracy and completeness are expected to directly affect trust, because trust is grounded in users’ knowing the technology sufficiently well that they can anticipate how it will respond under different conditions (McKnight et al. 2011).”
My Chatbot Companion - a Study of Human-Chatbot Relationships (2021, background): “…has previously been seen in the light of the technology ’ s functionality, ability to provide help and operational reliability and the technology provider ’ s integrity, benevolence and competence — including privacy aspects (McKnight et al., 2011; Prakash and Das, 2020; Ta et al., 2020).”
Towards Autonomous Cars: The Effect of Autonomy Levels on Acceptance and User Experience (2014, background): “T is surveyed with one item from [17], which asks how much participants would trust the car.”