A carregar...
Publicação
How generative AI tools shape decision outcomes
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 933.16 KB | Adobe PDF |
Orientador(es)
Resumo(s)
This study looks at how generative artificial intelligence tools influence decision outcomes in knowledge based work, with a specific focus on decision quality and decision efficiency. While much of the literature has focused on adoption and usage intentions, much less attention has been given to how generative artificial intelligence affects the outcomes of decisions themselves. To address this gap this paper develops and tests a research model that integrates key constructs from technology acceptance model (TAM), Trust and heuristic systematic model. The data was collected through an online questionnaire, the 303 valid responses were then analysed using partial least squares structural equation modelling. The results indicate that the model explains a substantial proportion of variance in both decision quality and decision efficiency. Decision quality is significantly influenced by perceived usefulness, trust in AI, systematic processing and heuristic processing, whereas perceived ease of use does not have a significant direct effect on decision quality. Decision efficiency is significantly influenced by perceived ease of use, perceived usefulness and trust in AI while heuristic processing shows a weaker positive effect and systematic processing is not significant. The model also shows that trust in AI moderates the relationship between TAM beliefs and decision outcomes, strengthening the effects of perceived ease of use and weakening the effects of perceived usefulness on both outcomes. Overall, this paper extends AI adoption literature by focusing on the decision outcomes and highlights the combined importance of usability, usefulness trust and cognitive processing in AI assisted decision making.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems Management
Palavras-chave
Generative artificial intelligence Technology Acceptance model Trust in AI Heuristic Systematic model Decision outcomes