Antecedents of Generative Artificial Intelligence Technology Adoption: Extended Innovation of Diffusion Model with Cultural Dimensions and Risks Perceptions DOI Creative Commons
Jamilah Mohammed Alamri

Journal of Ecohumanism, Journal Year: 2025, Volume and Issue: 4(1)

Published: Jan. 21, 2025

As Artificial Intelligence (AI) technologies are taking the lead among technological advancements around world, societies increasingly becoming interwoven with Generative AI (GAI) in all aspects, including higher education (HE). This study’s main aim is to examine how individual-level cultural dimensions influence students’ adoption of GAI learning, drawing on an extended Innovation Diffusion Theory (IDT) model. It explores impact (individualism/collectivism and uncertainty avoidance), IDT innovation factors (relative advantage, complexity, compatibility, observability, trialability), individual (self-efficacy, perceived risk) Saudi perceptions across several universities. Quantitative data were collected from 306 online survey analyzed using CB-SEM. Results highlight instrumental role dimensions, individualism/collectivism avoidance negatively affecting adoption. While complexity showed no significant impact, other variables positively influenced Furthermore, self-efficacy risk found be indicators use. The study emphasizes differences that shape technology collectivist moving toward individualism such as Saudi. identifies limitations, provides useful insights, suggests recommendations for future research uptake culturally diverse HE contexts.

Language: Английский

Antecedents of Generative Artificial Intelligence Technology Adoption: Extended Innovation of Diffusion Model with Cultural Dimensions and Risks Perceptions DOI Creative Commons
Jamilah Mohammed Alamri

Journal of Ecohumanism, Journal Year: 2025, Volume and Issue: 4(1)

Published: Jan. 21, 2025

As Artificial Intelligence (AI) technologies are taking the lead among technological advancements around world, societies increasingly becoming interwoven with Generative AI (GAI) in all aspects, including higher education (HE). This study’s main aim is to examine how individual-level cultural dimensions influence students’ adoption of GAI learning, drawing on an extended Innovation Diffusion Theory (IDT) model. It explores impact (individualism/collectivism and uncertainty avoidance), IDT innovation factors (relative advantage, complexity, compatibility, observability, trialability), individual (self-efficacy, perceived risk) Saudi perceptions across several universities. Quantitative data were collected from 306 online survey analyzed using CB-SEM. Results highlight instrumental role dimensions, individualism/collectivism avoidance negatively affecting adoption. While complexity showed no significant impact, other variables positively influenced Furthermore, self-efficacy risk found be indicators use. The study emphasizes differences that shape technology collectivist moving toward individualism such as Saudi. identifies limitations, provides useful insights, suggests recommendations for future research uptake culturally diverse HE contexts.

Language: Английский

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