Exploring User Acceptance Of Portable Intelligent Personal Assistants: A Hybrid Approach Using PLS-SEM And fsQCA
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
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2024
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| _version_ | 1866909301383102464 |
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| author | Mvondo, Gustave Florentin Nkoulou Niu, Ben |
| author_facet | Mvondo, Gustave Florentin Nkoulou Niu, Ben |
| contents | This research explores the factors driving user acceptance of Rabbit R1, a newly developed portable intelligent personal assistant (PIPA) that aims to redefine user interaction and control. The study extends the technology acceptance model (TAM) by incorporating artificial intelligence-specific factors (conversational intelligence, task intelligence, and perceived naturalness), user interface design factors (simplicity in information design and visual aesthetics), and user acceptance and loyalty. Using a purposive sampling method, we gathered data from 824 users in the US and analyzed the sample through partial least squares structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA). The findings reveal that all hypothesized relationships, including both direct and indirect effects, are supported. Additionally, fsQCA supports the PLS-SEM findings and identifies three configurations leading to high and low user acceptance. This research enriches the literature and provides valuable insights for system designers and marketers of PIPAs, guiding strategic decisions to foster widespread adoption and long-term engagement. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_17119 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Exploring User Acceptance Of Portable Intelligent Personal Assistants: A Hybrid Approach Using PLS-SEM And fsQCA Mvondo, Gustave Florentin Nkoulou Niu, Ben Human-Computer Interaction Artificial Intelligence HCC This research explores the factors driving user acceptance of Rabbit R1, a newly developed portable intelligent personal assistant (PIPA) that aims to redefine user interaction and control. The study extends the technology acceptance model (TAM) by incorporating artificial intelligence-specific factors (conversational intelligence, task intelligence, and perceived naturalness), user interface design factors (simplicity in information design and visual aesthetics), and user acceptance and loyalty. Using a purposive sampling method, we gathered data from 824 users in the US and analyzed the sample through partial least squares structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA). The findings reveal that all hypothesized relationships, including both direct and indirect effects, are supported. Additionally, fsQCA supports the PLS-SEM findings and identifies three configurations leading to high and low user acceptance. This research enriches the literature and provides valuable insights for system designers and marketers of PIPAs, guiding strategic decisions to foster widespread adoption and long-term engagement. |
| title | Exploring User Acceptance Of Portable Intelligent Personal Assistants: A Hybrid Approach Using PLS-SEM And fsQCA |
| topic | Human-Computer Interaction Artificial Intelligence HCC |
| url | https://arxiv.org/abs/2408.17119 |