Using generative AI as decision-support tools: unraveling users’ trust and AI appreciation DOI
Minh-Tay Huynh

Journal of Decision System, Год журнала: 2024, Номер unknown, С. 1 - 32

Опубликована: Ноя. 26, 2024

This study examines how organisational users accept recommendations when collaborating with Generative Artificial Intelligence (GenAI) to inform decisions, balancing perceived benefits and privacy concerns. Combining the theory of consumption values calculus theory, this work develops a research model capturing key factors driving users' trust in GenAI AI appreciation. Structural equation modelling analysis (N = 211) reveals that functional, social, emotional, epistemic positively impact disclosing information for advice. Information sensitivity increases risks, while control reduces perception. Perceived influence trust, risks negatively affect it. Trust is significant predictor contributes human-AI collaboration by illuminating mechanism leading appreciation addressing The findings offer actionable insights managers organisations seeking adopt their decision support system.

Язык: Английский

Effects of Technology Adaptation and Perceived Value on Continuance Intention in M-commerce of Gen Z: Innovativeness as a Moderator DOI Creative Commons
Minh Tri Ha, Vuong Bach Vo, Nguyễn Văn Anh

и другие.

SAGE Open, Год журнала: 2025, Номер 15(1)

Опубликована: Янв. 1, 2025

This study investigates the combined influence of privacy calculus theory (perceived risks, perceived benefits, value) and social cognitive (mobile computing self-efficacy, exploitive technology adaptation) on continuance intention Gen Z m-commerce users in Vietnam. Using convenience sampling a questionnaire-based survey approach, collected 385 responses from current users. To validate hypotheses, SmartPLS technique was employed. The findings revealed that value, adaptation, mobile self-efficacy are positively influenced by intention. Furthermore, not only highlights significant role within benefits–risks–value construct but also underscores framework. Remarkably, this is first to unveil moderating effect personal innovativeness relationship between adaption provides valuable insights recommendations for businesses aiming retain customers enhancing factors

Язык: Английский

Процитировано

0
Adaptation and resilience in retail: Exploring consumer clusters in the new normal DOI Creative Commons
Liana Stanca, Dan‐Cristian Dabija, Veronica Câmpian

и другие.

Journal of Retailing and Consumer Services, Год журнала: 2024, Номер 82, С. 104112 - 104112

Опубликована: Окт. 9, 2024

Язык: Английский

Процитировано

1
Consumer private data collection strategies for AI-enabled products DOI
Zhaojun Yang,

Yinmeng Li,

Jun Sun

и другие.

Electronic Commerce Research and Applications, Год журнала: 2024, Номер unknown, С. 101460 - 101460

Опубликована: Ноя. 1, 2024

Язык: Английский

Процитировано

0
Using generative AI as decision-support tools: unraveling users’ trust and AI appreciation DOI
Minh-Tay Huynh

Journal of Decision System, Год журнала: 2024, Номер unknown, С. 1 - 32

Опубликована: Ноя. 26, 2024

This study examines how organisational users accept recommendations when collaborating with Generative Artificial Intelligence (GenAI) to inform decisions, balancing perceived benefits and privacy concerns. Combining the theory of consumption values calculus theory, this work develops a research model capturing key factors driving users' trust in GenAI AI appreciation. Structural equation modelling analysis (N = 211) reveals that functional, social, emotional, epistemic positively impact disclosing information for advice. Information sensitivity increases risks, while control reduces perception. Perceived influence trust, risks negatively affect it. Trust is significant predictor contributes human-AI collaboration by illuminating mechanism leading appreciation addressing The findings offer actionable insights managers organisations seeking adopt their decision support system.

Язык: Английский

Процитировано

0