Implicit Theories and the Trust Repair Process

Author(s):  
Tai-Kong Kam
2021 ◽  
Author(s):  
Taenyun Kim ◽  
Hayeon Song

After an intelligent agent makes an error, trust repair can be attempted to regain lost trust. While several ways are possible, individuals' underlying perception of malleability in machines--implicit theory-- can also influence the agent's trust repair process. In this study, we investigated the influence of implicit theory of machines on intelligent agents' apology after the trust violation. A 2 (implicit theory: Incremental vs. Entity) X 2 (apology attribution: Internal vs. External) between-subject design experiment of simulated stock market investment was conducted (N = 150) via online. Participants were given a situation in which they had to make investment decisions based on the recommendation of an artificial intelligence agent. We created an investment game consist of 40 investment opportunities to see the process of trust development, trust violation, and trust repair. The results show that trust damaged less severely in Incremental rather than Entity implicit theory condition and External rather than internal attribution apology condition after the trust violation. However, trust recovered more highly in Entity-External condition. We discussed both theoretical and practical implications.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Malek Sghaier ◽  
Hamida Skandrani ◽  
Julie Robson

Purpose This study aims to identify the responses required to repair political trust in Tunisia and the differences between two key stakeholder groups, namely, politicians and voters. Design/methodology/approach A sequential mixed method study was adopted using two data sources: semi-structured interviews conducted with citizens and politicians; and media data from TV political talk shows. Data was collected over a three-year period following several key events that affected trust. Findings New responses were identified to repair political trust, and these were categorized using a trust repair framework. In addition to short- and long-term responses, a new category, swift response, was identified to resolve immediate political uncertainty. The role of the trustor (i.e. voters) in actively restoring trust was identified for the first time. Research limitations/implications This study focussed on trust repair responses suggested by voters and politicians and not necessarily responses that were implemented by government or political parties during the period of study. The effectiveness of the suggested responses in repairing trust was not evaluated. Practical implications Identification of the responses required to repair trust with voters, how these differ over time, and according to different trust violations will help Tunisian politicians rebuild trust more effectively during election and non-election periods. Notably, differences highlighted between the responses suggested by voters and politicians suggest that politicians may not understand how to repair voter trust. Originality/value Contrary to previous studies that assume a trustor (the voter) is a passive observer, this research identified the proactive role that citizens play in the trust repair process.


2020 ◽  
Author(s):  
Taenyun Kim ◽  
Hayeon Song

Trust is essential in individuals' perception, behavior, and evaluation of intelligent agents. Indeed, it is the primary motive for people to accept new technology. Thus, it is crucial to repair trust in the event when it is damaged. This study investigated how intelligent agents should apologize to recover trust and how the effectiveness of the apology is different when the agent is humanlike compared to machine-like based on two seemingly competing frameworks of the CASA (Computers-Are-Social-Actors) paradigm and automation bias. A 2 (agent: Human-like vs. Machine-like) X 2 (apology attribution: Internal vs. External) between-subject design experiment was conducted (N = 193) in the context of the stock market. Participants were presented with a scenario in which they were supposed to make investment choices with the help of an artificial intelligence agent's advice. To see the trajectory of initial trust-building, trust violation, and trust repair process, we designed an investment game that consists of 5 rounds of 8 investment choices (in total, 40 investment choices). The results show that trust was repaired more efficiently when a human-like agent apologizes with internal compared to external attribution. However, the opposite pattern was observed among participants who had machine-like agents; the external compared to internal attribution condition showed better trust repair. Both theoretical and practical implications are discussed.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Christopher A. Nelson ◽  
Annie Peng Cui ◽  
Michael F. Walsh

Purpose Building on prior trust repair research, this study aims to develop a more robust theoretical framework that describes trust repair strategies used by salespeople following a breach of trust. Design/methodology/approach To achieve the aim of this paper, individual depth interviews with 18 professional salespeople, 4 sales executives and 7 purchasing agents were undertaken. Findings This paper examines the value of using trust repair strategies (e.g. restoration, regulation and verbal repair strategies) both in isolation and in conjunction. The results suggest that individual trust repair strategies operate through impacting different dimensions of justice, as justice provides a reliable indicator as to whether the salesperson can be trusted in the future. This paper also finds that combining multiple trust repair strategies can have an additive effect on trust. Originality/value This paper uses thematic analysis to inductively identify the effective trust repair strategies that are used by salespeople in actual exchange relationships while integrating these insights with the existing theoretical frameworks in the literature. It contributes to theory through creating a conceptual model explaining the breach of trust and trust repair process, introducing justice as a direct mediating mechanism between trust repair strategies and increased trust. The research also develops a new perspective on combining salesperson words and actions to repair trust. It also provides a managerial contribution through introducing an optimized approach to trust repair in buyer-seller relationships.


2017 ◽  
Vol 78 ◽  
pp. 233-241 ◽  
Author(s):  
Ying Yu ◽  
Yan Yang ◽  
Fengjie Jing

2017 ◽  
Vol 225 (2) ◽  
pp. 146-156 ◽  
Author(s):  
Ivar Bråten ◽  
Andreas Lien ◽  
John Nietfeld

Abstract. In two experiments with Norwegian undergraduates and one experiment with US undergraduates, we examined the potential effects of brief task instructions aligned with incremental and entity views of intelligence on students’ performance on a rational thinking task. The research demonstrated that even brief one-shot task instructions that deliver a mindset about intelligence intervention can be powerful enough to affect students’ performance on such a task. This was only true for Norwegian male students, however. Moreover, it was the task instruction aligned with an entity theory of intelligence that positively affected Norwegian male students’ performance on the rational thinking task, with this unanticipated finding speaking to the context- and culture-specificity of implicit theories of intelligence interventions.


1999 ◽  
Author(s):  
Renae Franiuk ◽  
Dov Cohen ◽  
Eva Pomerantz

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