Understanding Factors Influencing Generative AI Use Intention: A Bayesian Network-Based Probabilistic Structural Equation Model Approach

Electronics, Год журнала: 2025, Номер 14(3), С. 530 - 530

Опубликована: Янв. 28, 2025

This study investigates the factors influencing users’ intention to use generative AI by employing a Bayesian network-based probabilistic structural equation model approach. Recognizing limitations of traditional models like technology acceptance and unified theory technology, this research incorporates novel constructs such as perceived anthropomorphism animacy capture unique human-like qualities AI. Data were collected from 803 participants with prior experience using applications. The analysis reveals that social influence (standardized total effect = 0.550) is most significant predictor intention, followed effort expectancy (0.480) usefulness (0.454). Perceived (0.149) (0.145) also but lower relative impact. By utilizing model, overcomes linear models, allowing for exploration nonlinear relationships conditional dependencies. These findings provide actionable insights improving design, user engagement, adoption strategies.

Язык: Английский

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Enhancing student GAI literacy in digital multimodal composing through development and validation of a scale

Computers in Human Behavior, Год журнала: 2025, Номер 166, С. 108569 - 108569

Опубликована: Янв. 31, 2025

Язык: Английский

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GenAI in Indian Higher Education: Faculty at the Crossroads of Adoption

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Фев. 10, 2025

While global institutions embrace GenAI to enhance education, many faculty members in India remain hesitant adopt it. Earlier research found that only a few studies have examined the adoption of at university level, especially developing countries. Sparsely explores how teachers accept and use GenAI, they failed provide complete picture its adoption. It highlights significant gap. This study provides what influences GenAI. Being, part an information system, novel construct 'Output Quality' TAM is added. The employed quantitative, single cross-sectional design. A total 455 from higher education participated, their responses were analyzed using CB-SEM. reveals perceived ease drives most, followed by usefulness social norms. Output quality has most decisive impact on use. Institutions can inspire through incentives recognition. findings will guide educators, administrators, policymakers who want integrate into education.

Язык: Английский

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Empirical Analysis of Generative Ai Adoption in Software Development

Опубликована: Янв. 1, 2025

Язык: Английский

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Understanding customers’ intentions to use AI-enabled services in online fashion stores – a longitudinal study

International Marketing Review, Год журнала: 2025, Номер unknown

Опубликована: Март 4, 2025

Purpose Artificial intelligence (AI) services are vital in enhancing customer experience and purchase intentions the international online fashion retail sector. This study explores customers’ to use AI-enabled services, focusing on transaction utility, trust product uniqueness across journey context of stores. also assesses how privacy moderates intentions. Design/methodology/approach adopted a longitudinal research design purposive sampling technique collect total 566 participants. The final data were analyzed using IBM SPSS Amos version 21 software. Findings highlights significance AI integration (pre-purchase, during post-purchase stages). Most direct relationships significant, except relationship between stages. With few exceptions, commonly does not mediate antecedents intention services. Privacy post-purchase, pre-purchase stage. Originality/value bridges important gaps literature by integrating behavior, contributing broader knowledge interactions global e-commerce examines multiple attributes that impact intention, such as trust, uniqueness, three stages purchases post-purchase) privacy, major theories: mental accounting theory, commitment theory commodity theory.

Язык: Английский

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Responses to the AI Revolution in Hospitality and Tourism Higher Education: The Perception of Students Towards Accepting and Using Microsoft Copilot

European Journal of Investigation in Health Psychology and Education, Год журнала: 2025, Номер 15(3), С. 35 - 35

Опубликована: Март 14, 2025

This research aims to examine hospitality and tourism students’ acceptance usage of Microsoft Copilot for educational purposes in Egyptian public universities. It also investigates the mediating role behavioral intention (BI) connection between actual use Copilot. study adopted unified theory technology (UTAUT) framework achieve aim. A quantitative approach was used via online surveys distributed gathered from 760 students nine universities Egypt analyzed using PLS-SEM test hypothesized relationships. The major findings showed that PE, EE, SI, FC affected BI highlighted a substantial direct influence FC, alone on Therefore, partially mediates relationship SI real-world classroom utilization clarifies has slight Copilot, while occurs entirely through BI. However, there full mediation PE EE. results have several implications higher education institutions academics are relevant other comparable setting.

Язык: Английский

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Generative artificial intelligence in tourism management: An integrative review and roadmap for future research

Tourism Management, Год журнала: 2025, Номер 110, С. 105179 - 105179

Опубликована: Март 31, 2025

Язык: Английский

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Factors influencing Chinese college students’ intention to use AIGC: a study based on the UTAUT model

International Journal of Systems Assurance Engineering and Management, Год журнала: 2025, Номер unknown

Опубликована: Апрель 1, 2025

Язык: Английский

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Unveiling the Complexity of Designers’ Intention to Use Generative AI in Corporate Product Design: A Grounded Theory and fsQCA

Systems, Год журнала: 2025, Номер 13(4), С. 275 - 275

Опубликована: Апрель 9, 2025

While generative artificial intelligence (Gen AI) is accelerating digital transformation and innovation in corporate product design (CPD), limited research has explored how designers adopt this technology. This study aims to identify the key factors causal configurations that influence designers’ intentions Gen AI CPD. involved 327 in-service as participants, employed semi-structured interviews a questionnaire collect data, applied grounded theory fsQCA analyze data. The findings indicate following: (1) Personal innovativeness, technological anxiety, perceived usefulness, task–technology fit, risk, social influence, organizational support are influencing adoption of AI. (2) None these constitute necessary condition for (3) High intention results from interaction multiple factors, which can be categorized into three driving logics: “task demand-driven”, “organizational environment-driven”, “individual characteristics-driven”. It recommended managers establish an training framework, foster supportive environment, implement tailored strategies facilitate integration new technologies. clarifies CPD provides framework companies effectively integrate systems design.

Язык: Английский

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ChatGPT in higher education: Investigating bachelor and master students’ expectations towards AI tool

Education and Information Technologies, Год журнала: 2024, Номер unknown

Опубликована: Дек. 16, 2024

Язык: Английский

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