Meta AI features on users’ flow experience and acceptance in the beauty and cosmetics industry: moderating role of Meta AI literacy
Smriti Mathur et al.
What the paper says
Purpose This study aims to integrate Artificial Intelligence Device Use Acceptance, diffusion of innovation and flow theory to explore the impact of innovation dimensions (primary appraisal) on user flow experience (UFEx) (secondary appraisal) and users’ willingness to accept Meta artificial intelligence (AI) features (Outcome). The moderating role of Meta AI literacy in the relationships among primary appraisal, secondary appraisal and the outcome were also examined. Design/methodology/approach This study used covariance-based structured equation modelling to analyse the data collected from 383 respondents who use Meta AI features for beauty and cosmetic products on social media. Findings The findings of the study indicates that compatibility and observability positively influence users flow experience, which subsequently impacts users’ willingness to accept Meta AI features on social media. Furthermore, Meta AI literacy positively moderates the relationship between relative advantage, compatibility, trialability, observability and users flow experience. Originality/value This study introduces a unique framework grounded on Meta AI features in social media, particularly in beauty and cosmetics, contributing to the literature on Meta AI, UFEx and willingness to accept. This research makes a novel attempt to explore how Meta AI literacy shapes the links among primary appraisal, secondary appraisal and outcomes.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.