A service Robot Acceptance Model: User acceptance of humanoid robots during service encounters

Stock, Ruth; Merkle, Moritz

doi:10.1109/percomw.2017.7917585

Cited by 69 publications

(74 citation statements)

References 16 publications

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“…TAM has been extended to evaluate technology acceptance in other domains such as in the e-learning system [35], smart in-store technology [36] and internet banking adoption [37]. To date, TAM has been applied to predict the acceptance of social robots in [29] frontline service [38], education [39] and healthcare [40]. Earlier research pointed out that social presence was one of the predictors in modelling the acceptance of robots in human-robot interaction [41].…”

Section: Introductionmentioning

confidence: 99%

Persuasive Robots Acceptance Model (PRAM): Roles of Social Responses Within the Acceptance Model of Persuasive Robots

Ghazali

Ham

Barakova

et al. 2020

Int J of Soc Robotics

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In the last years, there have been rapid developments in social robotics, which bring about the prospect of their application as persuasive robots to support behavior change. In order to guide related developments and pave the way for their adoption, it is important to understand the factors that influence the acceptance of social robots as persuasive agents. This study extends the technology acceptance model by including measures of social responses. The social responses include trusting belief, compliance, liking, and psychological reactance. Using the Wizard of Oz method, a laboratory experiment was conducted to evaluate user acceptance and social responses towards a social robot called SociBot. This robot was used as a persuasive agent in making decisions in donating to charities. Using partial least squares method, results showed that trusting beliefs and liking towards the robot significantly add the predictive power of the acceptance model of persuasive robots. However, due to the limitations of the study design, psychological reactance and compliance were not found to contribute to the prediction of persuasive robots' acceptance. Implications for the development of persuasive robots are discussed.

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Section: Introductionmentioning

confidence: 99%

Persuasive Robots Acceptance Model (PRAM): Roles of Social Responses Within the Acceptance Model of Persuasive Robots

Ghazali

Ham

Barakova

et al. 2020

Int J of Soc Robotics

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“…To run the experiments in a setting as realistic as possible, the setting of a hotel reception was built up that resembles a realistic hotel situation, which was guided by the design of established experimental studies [31] [32].…”

Section: Experimental Settingmentioning

confidence: 99%

Customer Responses to Service Robots – Comparing Human-Robot Interaction with Human-Human Interaction

Merkle

2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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This paper investigates how service failures affect customers by comparing human-robot interactions with human-human interactions. More specifically, it compares customers' satisfaction in a service robot interaction depending on a service failure with the customers' satisfaction in a frontline service employee interaction. On a theoretical basis, extant literature on the uncanny valley paradigm proposed that service robots would create lower satisfaction than human frontline employees would. However, I find that service robots could keep up with human frontline employees. Based on an extensive literature research on service failures, I propose that customer satisfaction after a service failure declines far less for a human frontline employee compared with a service robot. Nevertheless, I find evidence that service robots create even higher customer satisfaction than human frontline employees after the exactly similar service failure. I base my findings on an experimental laboratory study with 120 student participants and the service robot "Pepper" from Softbank Corp.

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“…However, the external validity of these experiments is rather limited. As a compromise, researchers could rely on contentenriched settings, such as the environment of an apartment [17] or a hotel lobby [7].…”

Section: Experimental Hri Research With Humanoid Robotsmentioning

confidence: 99%

“…Most studies rely on predefined, standardized dialogue for their experiments. Despite the frequent use of dialogues, few studies explicitly report how they validated the dialogues that they present during the experiment ( [7]).…”

Section: Experimental Hri Research With Humanoid Robotsmentioning

confidence: 99%

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How to Include Humanoid Robots into Experimental Research: A Multi-Step Approach

Homburg¹

2018

Proceedings of the 51st Hawaii International Conference on System Sciences

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Robots have penetrated many areas of daily life, including increased uses of humanoid robots in personal and organizational settings such as health care, eldercare, and service encounters with customers. Little research examines humanoid robots in these professional settings, even though the human-robot interaction (HRI) is particularly critical in such contexts. On the basis of a literature review and experience from several experimental studies, this article offers some guidance for designing HRI experiments with humanoid robots. In addition to detailing major challenges associated with designing HRI studies, this article suggests important next steps for experimental research with humanoid robots, as well as implications for further study.

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A service Robot Acceptance Model: User acceptance of humanoid robots during service encounters

Cited by 69 publications

References 16 publications

Persuasive Robots Acceptance Model (PRAM): Roles of Social Responses Within the Acceptance Model of Persuasive Robots

Persuasive Robots Acceptance Model (PRAM): Roles of Social Responses Within the Acceptance Model of Persuasive Robots

Customer Responses to Service Robots – Comparing Human-Robot Interaction with Human-Human Interaction

How to Include Humanoid Robots into Experimental Research: A Multi-Step Approach

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