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All Journal International Journal of Advances in Applied Sciences CommIT (Communication & Information Technology) Prosiding SNATIF Jurnal Pekommas Akuntansi Krida Wacana Jurnal Manajemen Dayasaing INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Jurnal Ilmiah Matrik Journal Information System Development Mesin International Journal of New Media Technology Jurnal ULTIMA InfoSys Jurnal Akuntansi Aqidah-Ta: Jurnal Ilmu Aqidah SENSITEK Jurnal Ilmu Teknik dan Komputer IJIIS: International Journal of Informatics and Information Systems Journal of Applied Data Sciences IAIC Transactions on Sustainable Digital Innovation (ITSDI) Jurnal Sains Teknologi dan Sistem Informasi Jurnal Sains dan Teknologi Proceeding National Conference Business, Management, and Accounting (NCBMA) JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) International Journal Research on Metaverse
Hery Hery
Universitas Pelita Harapan
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Veterinary

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Factors Influencing Customer Purchase Decisions in AI-Driven Online Shopping: Systematic Review Arnold Aribowo; Hery, Hery; Andree Emmanuel Widjaja; Calandra Alencia Haryani
SATESI: Jurnal Sains Teknologi dan Sistem Informasi Vol. 6 No. 1 (2026): April 2026
Publisher : Yayasan Pendidikan Penelitian Pengabdian ALGERO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/satesi.v6i1.7476

Abstract

This paper offers a PRISMA-guided systematic literature review to examine how Artificial Intelligence (AI) is applied in e-commerce. The focus is on identifying key factors that influence customer purchasing decisions in AI-driven online transactions. It examines Information Systems (IS) theories relevant to the integration of AI and e-commerce, offering insights into frameworks used to analyze the relationship between AI and consumer behavior. Additionally, the paper identifies gaps in current research and provides recommendations for future studies, particularly in areas requiring further exploration to understand the evolving impact of AI on e-commerce. Through a review of existing literature, the study identifies critical factors such as perceived enjoyment, perceived usefulness, perceived ease of use, interactivity, consumer engagement, AI technology, and information quality, which significantly affect consumer purchase intentions. This review finds that Stimulus-Organism-Response (SOR) and Technology Acceptance Model (TAM) are the most commonly adopted theories, while Media Richness Theory is used less frequently. The findings provide a robust foundation for future research, enabling the formulation of empirically testable hypotheses. Furthermore, this study offers a more integrated perspective by organizing identified constructs into a multi-dimensional framework and suggests directions for future empirical research, such as developing research models and validating them through survey-based approaches and Structural Equation Modeling (SEM-PLS), as well as qualitative methods. The study aims to offer insights to AI developers and e-commerce practitioners, helping them enhance AI-powered systems to better meet consumer needs and expectations, ultimately improving customer satisfaction and increasing purchase rates.
Cognitive and Technological Factors Shaping Students’ Sustained Use of ChatGPT in Higher Education Aribowo, Arnold; Hery, Hery; Widjaja, Andree Emmanuel
Journal of Applied Data Sciences Vol 7, No 2: May 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i2.1291

Abstract

This study examines the cognitive and technological factors shaping students' sustained use of ChatGPT in Indonesian higher education. Despite the rapid adoption of generative Artificial Intelligence (AI) in education, a clear understanding of the factors sustaining continued engagement with such systems remains limited. While continuance intention has been widely examined, the application of the Expectation–Confirmation Model (ECM) in generative AI contexts remains underexplored. This gap is especially evident when considering the role of AI-specific system attributes in shaping post-adoption evaluations. Although ECM has been extended with various constructs in prior studies, the specific integration of AI characteristics, particularly perceived intelligence and anthropomorphism, has not been explored in generative AI use in education, especially within Indonesian higher education. To address this gap, a multi-theoretic framework integrating ECM and AI characteristics was developed. Data from 322 Indonesian students were analyzed using Partial Least Squares-Structural Equation Modeling. All ten hypotheses were supported, and the model explains 43.3% of the variance in continuance intention (R² = 0.433). Perceived Intelligence strongly influences Perceived Anthropomorphism with a path coefficient of 0.591, representing the strongest relationship in the model, while other paths demonstrate moderate or modest effects. The findings confirm ECM's robustness in generative AI settings and highlight the pivotal role of AI characteristics in shaping post-adoption evaluations and sustained use. These results contribute to the growing body of research on generative AI adoption in education by demonstrating how system intelligence and human-like interaction jointly influence continuance intention. The findings also offer practical guidance for AI developers to enhance system intelligence and natural interaction. Future research could explore how students experience AI over time and what shapes their sustained use using different research methods.
Co-Authors Adriansyah, Willy Amalia, Alya M. Angelinda Fransisca, Angelinda Ari Darmawan Pasek Arnold Aribowo Calandra A. Haryani Calandra Alencia Haryani Christiani, Agustina Christopher, Raphael Debora Margareta Efendi Tarigan, Riswan Ellyse Obe Johanis Eric Jobiliong Feliks Victor Parningotan Samosir Ferdinand, Ferry Vincenttius Fransisko, Andy Habsara Hareva, David Harjono, Nathanael Joshua Haryani, Calandra Haryani, Calandra A. Haryani, Calandra Alencia Helena Juliana Kristina Jansen Wiratama Januardin, . Joshua Nathanael Justin A. Haratua Kevin Christianto Leo, Hengky Lisia, Vanella Mitra, Aditya R. Mohammad Rizky Firdaus Mouw, Christ Wibowo Mudinillah, Adam Nathanael, Joshua Prasetya, Kusno Prasetya, Tegar Yudha Renaldi, Ary Riswan Efendi Tarigan Rosanna, Nadya Safira Aqista Suryasari Tarigan, Riswan E. Veronica, Winnie Widjaja, Andree E. Wijaya, Yoana Sonia Willy Darmawan Wiracayana Ratanaghara Jayamangala