The Role of Trust as a Mediator Between System Characteristics and Response Behaviors

By Eric T. Chancey, James P. Bliss, Alexandra B. Proaps, Poornima Madhavan. 2015

59 citations recorded by the source corpus.

Subfields: Radiological and Ultrasound Technology, Social Psychology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Radiological and Ultrasound Technology

1. Ewart J. de Visser
2. Robert R. Hoffman
3. Tyler H. Shaw

In Social Psychology

1. Robert R. Hoffman
2. Shane T. Mueller
3. Gary Klein
4. Ewart J. de Visser
5. Yi-Ching Lee
6. Tyler H. Shaw
7. Eva Wiese
8. Spencer Kohn

Citations in the corpus

• Metrics for Explainable AI: Challenges and Prospects (2018, background): “e. XAI Metrics p. 19 5 Measuring Trust in the XAI Context 5.1 Introduction Trust in automation is of concern in computer science and cognitive systems engineering, as well as the popular media (e.g., Chancey et al., 2015; Hoff and Bashir 2015; Fitzhugh, Hoffman & Miller, 2011; Hoffman et al., 20”
• Measurement of Trust in Automation: A Narrative Review and Reference Guide (2021, result): “However, evidence for the effects of trust on response time has been mixed, and some authors recommend caution in using this measure (Chancey et  al., 2015).”