Extended TAM model to explore the factors that affect intention to use AI robotic architects for architectural design

Lin, Chau-Jy; Xu, Ni

doi:10.1080/09537325.2021.1900808

Cited by 18 publications

(9 citation statements)

References 41 publications

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“…The theory aims to analyze the influence of external factors on personal beliefs, attitudes, and intentions [ 46 ]. TAM has been applied in various fields such as technology, marketing, AI robotics, and psychology to examine online consumer behavior and technology adoption [ 3 ]. The key concept in TAM is that perceived ease of use and perceived usefulness significantly impact users’ attitudes and intentions to continue using a particular technology, thereby influencing their actual use behavior.…”

Section: Literature Review and Theoretical Modelsmentioning

confidence: 99%

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Users’ continuance intention towards an AI painting application: An extended expectation confirmation model

Yu,

Yang,

2024

PLoS ONE

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With the rapid advancement of technology, Artificial Intelligence (AI) painting has emerged as a leading intelligence service. This study aims to empirically investigate users’ continuance intention toward AI painting applications by utilizing and expanding the Expectation Confirmation Model (ECM), Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), and the Flow Theory. A comprehensive research model is proposed. A total of 443 questionnaires were distributed to users with AI painting experiences for data collection. The hypotheses were tested through structural equation modeling. The primary conclusions drawn from this research include: 1) Confirmation plays a crucial role, significantly and positively predicting satisfaction and social impact. 2) Personal innovativeness has a significant effect on confirmation. 3) Satisfaction, flow experience, and social influence directly and positively predict intention, with social influence showing the most significant impact, while perceived usefulness, perceived enjoyment, and performance expectancy show no significant impact on intention. 4) Habit plays a negative moderating role in the association between social influence and continued intention to use. These findings offer valuable insights and inspiration for users seeking to understand the appropriate utilization of AI painting and provide actionable directions for the development of AI painting.

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Section: Literature Review and Theoretical Modelsmentioning

confidence: 99%

“…Existing research on AI painting uses different theories, including the technology acceptance model [ 3 ], and the unified theory of acceptance and use of technology [ 4 ], to explain users’ adoption of AI painting. However, the findings are still fragmented.…”

Section: Introductionmentioning

confidence: 99%

Users’ continuance intention towards an AI painting application: An extended expectation confirmation model

Yu,

Yang,

2024

PLoS ONE

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“…Therefore, TAM has been used to explain users' acceptance of new technologies in many products areas, such as blockchain (N. Liu & Ye, 2021), AI product (C. Y. Lin & Xu, 2022), mobile wallets (Sarmah et al, 2021), Dockless Bikes Sharing System (Lyu & Zhang, 2021), MOOC learning (Y. R. Wang et al, 2020), telemedicine services (Kamal et al, 2020), and e-Tax Service (Rifat et al, 2019). Furthermore, the TAM is employed to explain the consumers' adoption of fitness wearable, which extend TAM by adding subjective norm into the framework (Lunney et al, 2016).…”

Section: Using Aƫtudementioning

confidence: 99%

“…Therefore, TAM has been used to explain users’ acceptance of new technologies in many products areas, such as blockchain (N. Liu & Ye, 2021), AI product (C. Y. Lin & Xu, 2022), mobile wallets (Sarmah et al, 2021), Dockless Bikes Sharing System (Lyu & Zhang, 2021), MOOC learning (Y.…”

Section: Literature Reviewmentioning

confidence: 99%

Consumer Acceptance of Sports Wearables: The Role of Products Attributes

Wang

Fang²,

Liu

et al. 2023

Sage Open

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Based on the technology acceptance model (TAM), this paper discusses how the functional attributes and design characteristics of sports wearable devices affect users’ attitude and behavior. In order to estimate the relationship between variables, structural equation model (SEM) was used to analyze the data from questionnaire. By analyzing the relationship among data analysis, real-time monitoring, appearance design, simple operation, perceived usefulness, perceived ease of use, use attitude, and use behavior, it is found that data analysis and real-time monitoring has a significant impact on the perceived usefulness of sports wearable devices. The simple operation and appearance design have a significant impact on the perceived ease of use of sports wearable devices. The perceived usefulness and perceived ease of use of sports wearable devices further affect users’ attitude and behavior. The result means all study hypotheses were accepted. Therefore, providing perfect data analysis function, developing accurate real-time monitoring function, introducing friendly appearance design, and simplifying product operation mode can improve the use value and operation convenience of sports wearable devices and enhance the acceptance of users.

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“…Researchers have continuously upgraded and extended TAM based on TAM, such as TAM2, TAM3, UTAUT, UTAUT 2, etc [26][27][28][29][30][31][32]. Although RATAM, a new high-tech acceptance theory model for AI robot architecture design contexts, provides new insights into the future development of AI in architectural design [33].To our knowledge. There has been no such empirical research applying the extended TAM to AIBPS, and no research has been conducted to investigate the factors that influence user adoption of AIBPS.…”

Section: Of 22mentioning

confidence: 99%

Everyone's an Artist? Exploring User Acceptance of AI-Based Painting Systems

Xu¹,

Zhang²,

Li³

et al. 2023

Preprint

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Artificial intelligence (AI) applications in different fields are developing rapidly, among which AI painting technology, as an emerging technology, has received wide attention from users for its creativity and efficiency. This study aimed to investigate the factors that influence user acceptance of the use of AIBPS by proposing an extended model that combines the Extended Technology Acceptance Model (ETAM) with the AI-based Painting System (AIBPS).A questionnaire was administered to 528 Chinese participants, using validated factor analysis data and Structural Equation Modeling (SEM) was used to test the hypotheses. The findings showed that hedonic motivation (HM) and perceived trust (PE) had a positive effect (+) on users' perceived usefulness (PU) and perceived ease of use (PEOU), while previous experience (PE) and technical features (TF) had no effect (-) on users' perceived usefulness (PU). This study provides an important contribution to the literature on AIBPS and the evaluation of systems of the same type, which helps to promote the sustainable development of AI in different domains and provides a possible space for further extension of TAM, thus helping to improve the user experience of AIBPS. The results of the study provide insights for system developers and enterprises to better motivate users to use AIBPS.

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Extended TAM model to explore the factors that affect intention to use AI robotic architects for architectural design

Cited by 18 publications

References 41 publications

Users’ continuance intention towards an AI painting application: An extended expectation confirmation model

Users’ continuance intention towards an AI painting application: An extended expectation confirmation model

Consumer Acceptance of Sports Wearables: The Role of Products Attributes

Everyone's an Artist? Exploring User Acceptance of AI-Based Painting Systems

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