Does the domain of technology impact user trust? Investigating trust in automation across different consumer-oriented domains in young adults, military, and older adults

Pak, Richard; Rovira, Ericka; McLaughlin, Anne Collins; Baldwin, Natalee

doi:10.1080/1463922x.2016.1175523

Cited by 32 publications

(27 citation statements)

References 47 publications

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“…This negative preference for completely self-driving cars has increased since 2015 (older adults: 50%, younger adults 35%; Schoettle and Sivak, 2015). But these opinion surveys are in direct contrast to experimental results that show older adults having higher trust compared to other age groups for lower forms of vehicular automation (e.g., Donmez et al, 2008; Pak et al, 2016b).…”

Section: The Importance Of Driving For Older Adults’ Well-beingcontrasting

confidence: 77%

Looking for Age Differences in Self-Driving Vehicles: Examining the Effects of Automation Reliability, Driving Risk, and Physical Impairment on Trust

et al. 2019

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Purpose Self-driving cars are an extremely high level of autonomous technology and represent a promising technology that may help older adults safely maintain independence. However, human behavior with automation is complex and not straightforward ( Parasuraman and Riley, 1997 ; Parasuraman, 2000 ; Rovira et al., 2007 ; Parasuraman and Wickens, 2008 ; Parasuraman and Manzey, 2010 ; Parasuraman et al., 2012 ). In addition, because no fully self-driving vehicles are yet available to the public, most research has been limited to subjective survey-based assessments that depend on the respondents’ limited knowledge based on second-hand reports and do not reflect the complex situational and dispositional factors known to affect trust and technology adoption. Methods To address these issues, the current study examined the specific factors that affect younger and older adults’ trust in self-driving vehicles. Results The results showed that trust in self-driving vehicles depended on multiple interacting variables, such as the age of the respondent, risk during travel, impairment level of the hypothesized driver, and whether the self-driving car was reliable. Conclusion The primary contribution of this work is that, contrary to existing opinion surveys which suggest broad distrust in self-driving cars, the ratings of trust in self-driving cars varied with situational characteristics (reliability, driver impairment, risk level). Specifically, individuals reported less trust in the self-driving car when there was a failure with the car technology; and more trust in the technology in a low risk driving situation with an unimpaired driver when the automation was unreliable.

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Section: The Importance Of Driving For Older Adults’ Well-beingcontrasting

confidence: 77%

Looking for Age Differences in Self-Driving Vehicles: Examining the Effects of Automation Reliability, Driving Risk, and Physical Impairment on Trust

et al. 2019

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“…Managing trust requires an in-depth investigation of the local market, as domestic culture might create barriers, in addition to national legislation. National differences might have a positive or a negative effect on trust in any new technology [35,36]. It is also important to note that sometimes the lack of alternatives or necessity could influence that factor towards trust [12].…”

Section: Social Influence-related Factorsmentioning

confidence: 99%

“…It is also important to note that sometimes the lack of alternatives or necessity could influence that factor towards trust [12]. Nevertheless, there is a lack of studies on the impact of culture on trust [36]. Consequently, it is evident that, for any new IoT technology or service entering a new market, the local community interest must be taken into the account and a deep investigation and appreciation of the local perceptions and opportunities related to trust must be conducted.…”

Section: Social Influence-related Factorsmentioning

confidence: 99%

Improving IoT Technology Adoption through Improving Consumer Trust

Alhogail

2018

Technologies

107

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Studies have shown that trust plays a crucial role in the consumers' decision to adopt Internet of Things (IoT) technologies and services since it helps them to overcome perceptions of risk and uncertainty related to it and enhances the customers' level of acceptance and adoption intention. Nevertheless, the literature of IoT still lacks studies on the behavioral aspect that explain the customers' perception towards IoT adoption and focuses more on technological aspect. The main goal of this study is to examine the factors that influence consumer trust and their role in the adoption of IoT technology. A conceptual trust model that encompasses the major factors affecting trust towards IoT technology adoption has been presented. The model is composed of three dimensions of factors that we assume will influence the level of trust which are: product related factors, social influence related factors and security related factors. This framework is validated through surveying consumers' opinions, which provide views and feedback regarding factors influencing their trust towards this technology. The model can assist researchers to further investigate the trust issues and create a trustworthy literature to guide IoT products' development and marketing strategies that are focused on the consumer's requirements.

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“…Previous studies have indicated several significant personal effects on users' trust toward automated systems, including dispositional trust [2,33,45], personality traits [33,34,49,58], age [11,16,21,42,51], gender [39,59], and culture/ethnicity [19,28,29,53]. However, as far as we know, no empirical research has investigated how personal factors affect dynamic formation of human-agent trust.…”

Section: Personal Influences: Empirical Gaps In Human-agent Trustmentioning

confidence: 99%

Personal Influences on Dynamic Trust Formation in Human-Agent Interaction

Huang

Bashir

2017

Proceedings of the 5th International Conference on Human Agent Interaction

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The development of automated technologies in our daily life has transformed the role of human operators from a controller to a teammate who shares control with automated agents. However, this 'teammate' relationship between humans and automation raises an important but challenging research question regarding the formation of human-agent trust. Considering that the formation of human-agent trust is a dynamic and sophisticated process involving human factors, this study conducted a two-phase online experiment to examine personal influences on users' trust propensity and their trust formation in human-agent interactions. Our findings revealed distinctive personal influences on dispositional trust and the formation of human-agent trust at different stages. We found that users who exhibit higher trust propensities in humans also develop higher trust toward automated agents in initial stages. This study, as the first of its kind, not only fills the gap of knowledge about personal influences on human-agent trust, but also offers opportunities to enhance the future design of automated agent systems.

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Does the domain of technology impact user trust? Investigating trust in automation across different consumer-oriented domains in young adults, military, and older adults

Cited by 32 publications

References 47 publications

Looking for Age Differences in Self-Driving Vehicles: Examining the Effects of Automation Reliability, Driving Risk, and Physical Impairment on Trust

Looking for Age Differences in Self-Driving Vehicles: Examining the Effects of Automation Reliability, Driving Risk, and Physical Impairment on Trust

Improving IoT Technology Adoption through Improving Consumer Trust

Personal Influences on Dynamic Trust Formation in Human-Agent Interaction

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