Factors Affecting Adoption Behavior in the AI Platforms

H'ng, Thong Min (2025) Factors Affecting Adoption Behavior in the AI Platforms. Masters thesis, Tunku Abdul Rahman University of Management and Technology.

Text 56 H_ng Thong Min (MBA).pdf Restricted to Registered users only Download (4MB)

Abstract

This study investigates the factors affecting adoption behavior in the Artificial Intelligence (AI) platforms, focusing on perceived usefulness, perceived ease of use, techno-eustress, and techno-distress. Employing a quantitative cross-sectional research design, data were collected via an online survey from 340 participants and analyzed using SPSS and SmartPLS. The study explores the direct, indirect, and mediating effects among the constructs to better understand the psychological and technological drivers behind AI adoption. Findings reveal that perceived usefulness and ease of use significantly impact adoption behavior, while techno-eustress and techno-distress play complex roles as both motivators and barriers. This research contributes to the broader understanding of AI consumer engagement, offering practical implications for marketers and developers to tailor strategies that enhance user adoption behaviour. Ethical considerations, such as voluntary participation and data confidentiality, were rigorously maintained to ensure the integrity of the results. Keywords: Artificial Intelligence Adoption, Perceived Usefulness, Perceived Ease of Use, Techno-Eustress, Techno-Distress, Adoption Behaviour