Literature DB >> 22046724

A meta-analysis of factors affecting trust in human-robot interaction.

Peter A Hancock1, Deborah R Billings, Kristin E Schaefer, Jessie Y C Chen, Ewart J de Visser, Raja Parasuraman.   

Abstract

OBJECTIVE: We evaluate and quantify the effects of human, robot, and environmental factors on perceived trust in human-robot interaction (HRI).
BACKGROUND: To date, reviews of trust in HRI have been qualitative or descriptive. Our quantitative review provides a fundamental empirical foundation to advance both theory and practice.
METHOD: Meta-analytic methods were applied to the available literature on trust and HRI. A total of 29 empirical studies were collected, of which 10 met the selection criteria for correlational analysis and 11 for experimental analysis. These studies provided 69 correlational and 47 experimental effect sizes.
RESULTS: The overall correlational effect size for trust was r = +0.26,with an experimental effect size of d = +0.71. The effects of human, robot, and environmental characteristics were examined with an especial evaluation of the robot dimensions of performance and attribute-based factors. The robot performance and attributes were the largest contributors to the development of trust in HRI. Environmental factors played only a moderate role.
CONCLUSION: Factors related to the robot itself, specifically, its performance, had the greatest current association with trust, and environmental factors were moderately associated. There was little evidence for effects of human-related factors. APPLICATION: The findings provide quantitative estimates of human, robot, and environmental factors influencing HRI trust. Specifically, the current summary provides effect size estimates that are useful in establishing design and training guidelines with reference to robot-related factors of HRI trust. Furthermore, results indicate that improper trust calibration may be mitigated by the manipulation of robot design. However, many future research needs are identified.

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Mesh:

Year:  2011        PMID: 22046724     DOI: 10.1177/0018720811417254

Source DB:  PubMed          Journal:  Hum Factors        ISSN: 0018-7208            Impact factor:   2.888


  56 in total

1.  A Little Anthropomorphism Goes a Long Way.

Authors:  Ewart J de Visser; Samuel S Monfort; Kimberly Goodyear; Li Lu; Martin O'Hara; Mary R Lee; Raja Parasuraman; Frank Krueger
Journal:  Hum Factors       Date:  2017-02       Impact factor: 2.888

2.  On the future of transportation in an era of automated and autonomous vehicles.

Authors:  P A Hancock; Illah Nourbakhsh; Jack Stewart
Journal:  Proc Natl Acad Sci U S A       Date:  2019-01-14       Impact factor: 11.205

3.  Understanding Older Adult's Perceptions of Factors that Support Trust in Human and Robot Care Providers.

Authors:  Rachel E Stuck; Wendy A Rogers
Journal:  Int Conf Pervasive Technol Relat Assist Environ       Date:  2017-06

4.  Changes in motor performance and mental workload during practice of reaching movements: a team dynamics perspective.

Authors:  Isabelle M Shuggi; Patricia A Shewokis; Jeffrey W Herrmann; Rodolphe J Gentili
Journal:  Exp Brain Res       Date:  2017-12-06       Impact factor: 1.972

5.  Human-Robot Mutual Adaptation in Shared Autonomy.

Authors:  Stefanos Nikolaidis; David Hsu; Yu Xiang Zhu; Siddhartha Srinivasa
Journal:  Proc ACM SIGCHI       Date:  2017-03

6.  Leading Teams in the Digital Age: Four Perspectives on Technology and What They Mean for Leading Teams.

Authors:  Lindsay Larson; Leslie DeChurch
Journal:  Leadersh Q       Date:  2020-01-13

7.  How different types of users develop trust in technology: a qualitative analysis of the antecedents of active and passive user trust in a shared technology.

Authors:  Jie Xu; Kim Le; Annika Deitermann; Enid Montague
Journal:  Appl Ergon       Date:  2014-05-29       Impact factor: 3.661

8.  Promises and trust in human-robot interaction.

Authors:  Lorenzo Cominelli; Francesco Feri; Roberto Garofalo; Caterina Giannetti; Miguel A Meléndez-Jiménez; Alberto Greco; Mimma Nardelli; Enzo Pasquale Scilingo; Oliver Kirchkamp
Journal:  Sci Rep       Date:  2021-05-06       Impact factor: 4.379

9.  Parental Acceptance of Children's Storytelling Robots: A Projection of the Uncanny Valley of AI.

Authors:  Chaolan Lin; Selma Šabanović; Lynn Dombrowski; Andrew D Miller; Erin Brady; Karl F MacDorman
Journal:  Front Robot AI       Date:  2021-05-19

10.  An empirical investigation of trust in AI in a Chinese petrochemical enterprise based on institutional theory.

Authors:  Jia Li; Yiwen Zhou; Junping Yao; Xuan Liu
Journal:  Sci Rep       Date:  2021-06-30       Impact factor: 4.379

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