Feb 2027· Computer/law journal· 0 citations· 21 references
TL;DR
The findings indicate an accuracy–relevance asymmetry: relevance attracts attention, whereas perceived accuracy more strongly reinforces purchase decisions.
Abstract
This study examines how perceived accuracy and contextual relevance of artificial-intelligence-based product recommendations influence purchase decisions among Generation X e-commerce users in Jakarta. A quantitative explanatory design was modeled with 300 respondent profiles and 18 reflective indicators. Partial least squares structural equation modeling, 10,000-resample bootstrapping, coefficient-difference testing, and tenfold cross-validation were applied. Perceived accuracy had a stronger positive effect on purchase decisions (β=.604, p<.001) than relevance (β=.217, p<.001), and the difference was significant (Δβ=.387, p<.001). The model explained 54.2% of purchase-decision variance and showed positive Qpredict2 values. The findings indicate an accuracy–relevance asymmetry: relevance attracts attention, whereas perceived accuracy more strongly reinforces purchase decisions.
It is shown that the value pathway is more dependable than the trust pathway in translating AI recommendation quality into purchase intention, indicating that recommendation quality is a meaningful but limited part of the wider purchase decision.
Bích Đào Phạm Thị· International Journal of Adv...· 0 citations
Artificial intelligence increasingly shapes how e-commerce platforms recommend integrated financial services, yet evidence concerning Generation X remains limited. This methodological study examines the relationships among perceived AI-based recommendation quality, trust, and embedded finance use, while also distinguis...
Selvia De Wana, Riwandari Juniasti, Amri Sinuraya· Dinasti International Journa...· 0 citations
The rapid diffusion of artificial intelligence (AI) in e-commerce has transformed consumer interactions with digital platforms through algorithmic recommendation systems. However, their complexity and opacity raise concerns about transparency and trust. This study examines how explainable AI-driven recommendation quali...
Ajeet Tiwari, Sheshpal Namdeo· International Journal of Ele...· 1 citation
This study examines how AI-driven marketing strategies shape consumer decision-making by integrating the Stimulus–Organism–Response (S-O-R) framework with the Technology Acceptance Model (TAM). Survey data from 246 consumers in Türkiye exposed to AI-based marketing tools were analyzed using regression and the Hayes PRO...
Sami Imad Eddine Ketita, Sibel Demirel· Wisdom Journal For Studies &...· 0 citations
Algorithmic explanations may inform consumer evaluation, but understanding a rationale and trusting its source are distinct judgments. Drawing on Signaling Theory, this study develops a conditional framework in which explanations provide useful information when they are comprehensible, decision-relevant, and credible....
Paula Peres, Marta Fernandes· Information· 0 citations
Artificial intelligence (AI) now shapes what young consumers see, compare and buy on digital platforms. This study examines how AI-powered consumer analytics, expressed through personalised recommendations and targeted advertising, relate to the sustainable product purchase decisions of Generation Z consumers in Hydera...
M. R. P. Kumar, Chelikani Hansika· International Journal of Res...· 0 citations
With $2.1 million funding from Google.org, the open-source Public Transit Intelligence Hub will unify public transit monitoring, operations, and passenger communication.
