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MATG_Masters_Thesis_Collins_Thesis_Revisions_GradSchool_Submission_v2.pdf (2.8 MB)
ETD Abstract Container
Abstract Header
Trust Discounting in the Multi-Arm Trust Game
Author Info
Collins, Michael
Permalink:
http://rave.ohiolink.edu/etdc/view?acc_num=wright1607086117161125
Abstract Details
Year and Degree
2020, Master of Science (MS), Wright State University, Human Factors and Industrial/Organizational Psychology MS.
Abstract
Social interactions are complex and constantly changing decision making environments. Prior research (Mayer, Davis, & Schoorman, 1995) has found that people use their trust in others as a criterion for decision making during social interactions. Trust is not only relevant for human-human interaction, but has also been found to be important for human-machine interaction as well, which is becoming a growing feature in many work domains (De Visser et al., 2016). Prior research on trust has attempted to identify the behavioral characteristics an individual (trustor) uses to assess the trustworthiness of another (trustee) to determine the trustor's level of trust. Experimental findings have been used to develop into various models of trust (Mayer et al., 1995; Juvina, Collins, Larue, Kennedy & de Mello, 2019) to explain how a trustor comes to trust a trustee. An aspect of trust that has not been investigated is how or if trust changes when a trustor attempts to interact with a trustee, but cannot interact with the trustee. Under such situations Juvina et al.’s (2019) trust model makes the novel prediction that trust will decrease. To assess the prediction of Juvina et al. (2019) model, a new experimental design (the multi-arm trust game) was developed to evaluate how trust is affected under conditions where an individual variably interacts with multiple trustees. Additionally, the identity the trustee (human and machine) was manipulated to examine differences between human-human and human-machine trust. Before data were collected, the model made ex-ante predictions of the participants’ behavior. The accuracy of these predictions was then evaluated after the data were collected. The results from our experiment found that our model was able to predict general characteristics of the data confirming the necessity of the model’s discounting mechanism, while also highlighting model limitations that are areas for future research.
Committee
Ion Juvina, Ph.D. (Advisor)
Kevin A. Gluck, PhD. (Committee Member)
Joseph Houpt, Ph.D. (Committee Member)
Valerie L. Shalin, Ph.D. (Committee Member)
Pages
133 p.
Subject Headings
Psychology
Keywords
Trust
;
Game Theory
;
Trust Game
;
Trust Discounting
;
Multi-Arm Bandit Game
;
Social Interaction
;
Decision Making
;
Mathematical Models
;
Prediction
Recommended Citations
Refworks
EndNote
RIS
Mendeley
Citations
Collins, M. (2020).
Trust Discounting in the Multi-Arm Trust Game
[Master's thesis, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright1607086117161125
APA Style (7th edition)
Collins, Michael.
Trust Discounting in the Multi-Arm Trust Game.
2020. Wright State University, Master's thesis.
OhioLINK Electronic Theses and Dissertations Center
, http://rave.ohiolink.edu/etdc/view?acc_num=wright1607086117161125.
MLA Style (8th edition)
Collins, Michael. "Trust Discounting in the Multi-Arm Trust Game." Master's thesis, Wright State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1607086117161125
Chicago Manual of Style (17th edition)
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Document number:
wright1607086117161125
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1,560
Copyright Info
© 2020, all rights reserved.
This open access ETD is published by Wright State University and OhioLINK.