2021
DOI: 10.1002/hbe2.293
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Hello Alexa! Exploring effects of motivational factors and social presence on satisfaction with artificial intelligence ‐enabled gadgets

Abstract: From requesting Alexa to set a reminder to asking Google Assistant to make a call, artificial intelligence (AI)‐enabled voice assistants are quickly melding into our lives. This study aims to understand why users interact with a voice assistant system. Results from an online survey identified four types of motivations underlying the use of voice assistants: entertainment, companionship, dynamic control, and functional utility. Results showed that functional utility and dynamic control were positively related t… Show more

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Cited by 23 publications
(7 citation statements)
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“…Such work could draw on the extended Technology Acceptance Model [21,23,44], which examines factors such as the perceived usefulness of specific technologies and how much users report trusting them. It will also be important to explore the effects of people's prior experiences with related technologies [45].…”
Section: Ratingmentioning
confidence: 99%
“…Such work could draw on the extended Technology Acceptance Model [21,23,44], which examines factors such as the perceived usefulness of specific technologies and how much users report trusting them. It will also be important to explore the effects of people's prior experiences with related technologies [45].…”
Section: Ratingmentioning
confidence: 99%
“…Self-determination theory served as the foundation for the study by Chiu, Moorhouse, Chai, and Ismailov (2023), which looked at how teacher assistance influences how well students met their needs and how intrinsically motivated they were to learn using AI technology. It is obvious, in contrast to friendship and amusement, that the functional usefulness and dynamic control had a beneficial relationship to users' happiness (Shao & Kwon, 2021). It was also investigated how social presence affected user satisfaction.…”
Section: Ai In Ll and Teaching In Literaturementioning
confidence: 99%
“…Several theoretical models include this aspect as a core driver of technology adoption (e.g., perceived usefulness in the Technology Acceptance Model, TAM, Davis et al, 1989; performance expectancy in the Unified Theory of Acceptance and Use of Technology, UTAUT, Venkatesh et al, 2003). Furthermore, empirical research has repeatedly shown that functionality of technical systems is highly relevant for technology acceptance, and adoption of technologies in general and conversational AI in specific (e.g., McLean & Osei-Frimpong, 2019; Moriuchi, 2019; Moussawi et al, 2020; Pitardi & Marriott, 2021; Shao & Kwon, 2021). Besides, for people who already use a (smart) technology, competence is an important driver of usage continuance intentions (e.g., Dehghani, 2018; Moussawi et al, 2022).…”
Section: Introductionmentioning
confidence: 99%