The Buck Stops There: The Impact of Perceived Accountability and Control on the Intention to Delegate to Software Agents

Stout, Nathan Keith; Dennis, Alan R.; Wells, Taylor

doi:10.17705/1thci.00058

Cited by 17 publications

(10 citation statements)

References 93 publications

(131 reference statements)

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“…Participants often emphasize AI to be mechanical (the lowest level of AI) and consider it suitable to augment their higher level of human intelligence (Huang and Rust, 2022). Consumers' perceived customizability (a subdimension of AI credibility) can help increase empowerment in delegating tasks to AI and increase consumers' willingness to delegate tasks to AI (Puntoni et al, 2021;Stout et al, 2014).…”

Section: Consumer-ai Experience and Outcomesmentioning

confidence: 99%

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AI credibility and consumer-AI experiences: a conceptual framework

Khan,

Mishra

2023

JSTP

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PurposeThis study aims to conceptualize the relationship of perceived artificial intelligence (AI) credibility with consumer-AI experiences. With the widespread deployment of AI in marketing and services, consumer-AI experiences are common and an emerging research area in marketing. Various factors affecting consumer-AI experiences have been studied, but one crucial factor – perceived AI credibility is relatively underexplored which the authors aim to envision and conceptualize.Design/methodology/approachThis study employs a conceptual development approach to propose relationships among constructs, supported by 34 semi-structured consumer interviews.FindingsThis study defines AI credibility using source credibility theory (SCT). The conceptual framework of this study shows how perceived AI credibility positively affects four consumer-AI experiences: (1) data capture, (2) classification, (3) delegation, and (4) social interaction. Perceived justice is proposed to mediate this effect. Improved consumer-AI experiences can elicit favorable consumer outcomes toward AI-enabled offerings, such as the intention to share data, follow recommendations, delegate tasks, and interact more. Individual and contextual moderators limit the positive effect of perceived AI credibility on consumer-AI experiences.Research limitations/implicationsThis study contributes to the emerging research on AI credibility and consumer-AI experiences that may improve consumer-AI experiences. This study offers a comprehensive model with consequences, mechanism, and moderators to guide future research.Practical implicationsThe authors guide marketers with ways to improve the four consumer-AI experiences by enhancing consumers' perceived AI credibility.Originality/valueThis study uses SCT to define AI credibility and takes a justice theory perspective to develop the conceptual framework.

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Section: Consumer-ai Experience and Outcomesmentioning

confidence: 99%

“…Consumers' perceived customizability (a subdimension of AI credibility) can help increase empowerment in delegating tasks to AI and increase consumers' willingness to delegate tasks to AI (Puntoni et al. , 2021; Stout et al. , 2014).…”

Section: Conceptual Frameworkmentioning

confidence: 99%

AI credibility and consumer-AI experiences: a conceptual framework

Khan,

Mishra

2023

JSTP

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“…In general, the mediated and virtual nature of the interactions, and the associated lack of physical clues, heighten the challenges of intangibility and uncertainty of the interaction (Kollmann & Suckow, 2008; Morgan-Thomas & Veloutsou, 2013). The distance with the interlocutor reduces its perceived accountability, which refers to the idea that one’s actions need to be justified to others, and in particular to customers (Frink et al, 2004; Johnson, 2005; Stout et al, 2014). On the internet and on the phone, brands’ employees are not as much accountable to customers that they are at the point of sales.…”

Section: Literature Reviewmentioning

confidence: 99%

Does making less effort entail satisfaction? A large empirical study on client relationship services

Ardelet

Benavent

2022

International Journal of Market Research

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The customer effort score has become one of the indicators most monitored by companies in recent years. The idea is that the less effort customers exert when interacting with a brand, the more satisfied they will be, the more likely they will recommend and continue interacting with the brand. In this article, we explore the actual relationship between the client’s effort to solve the problem that led them to contact the brand and the satisfaction derived from this interaction. We present a weekly survey conducted over 2 years, covering 314 194 interactions with 96 brands from 2016 to 2017. The results show a negative effect of client effort intensity on satisfaction, except in some situations where effort intensity increases satisfaction, with an interaction effect of the interaction channel, and the business sector.

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“…This is particularly shown by the participants, with most feeling that incorrect tariff decisions would be largely their responsibility. Recent work [Stout et al 2014] suggested that delegation of autonomy is perceived by users as a means to shift blame from themselves to autonomous system for undesirable outcomes. In contrast, our results show that the ability to delegate autonomy in a flexible manner ultimately leads users to feel in control and therefore responsible.…”

Section: Interaction With Autonomymentioning

confidence: 99%

Tariff Agent

Alan

Costanza

Ramchurn

et al. 2016

ACM Trans. Comput.-Hum. Interact.

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Smart systems are becoming increasingly ubiquitous, and consequently transforming our lives. The level of system autonomy plays a vital role in the development of smart systems as it profoundly affects how people and these systems interact with each other. However, to date, there are very few studies on human interaction with such systems. This article presents findings from two field studies where two different prototypes for automating energy tariff-switching were developed and evaluated in the wild. Both prototypes offer flexible autonomy by which users can shift the system's level of autonomy among three options: suggestion-only, semi-autonomy and full autonomy, whenever they like. Our findings based on thematic analysis show that flexible autonomy is a promising way to sustain users' engagement with smart systems, despite their occasional mistakes. The findings also suggest that users take responsibility for the undesired outcomes of automated actions when delegation of autonomy can be adjusted flexibly.

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The Buck Stops There: The Impact of Perceived Accountability and Control on the Intention to Delegate to Software Agents

Cited by 17 publications

References 93 publications

AI credibility and consumer-AI experiences: a conceptual framework

AI credibility and consumer-AI experiences: a conceptual framework

Does making less effort entail satisfaction? A large empirical study on client relationship services

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