Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Psikologi Prima Indonesia Economic Journal
Tasya Augustiya
Universitas Muhammadiyah Bandung
Humanities Economics, Econometrics & Finance Education Neuroscience Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Strategi Atasi Perilaku Menarik Diri di Perusahaan Rintisan Berbasis Teknologi (Technopreneur): Mengubah Tantangan jadi Peluang dengan Mendesain Ulang Pekerjaan Sendiri Tasya Augustiya; Novia Astuti Dewi
Indonesia Economic Journal Vol. 2 No. 1 (2026): JANUARI-JUNI
Publisher : Indo Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63822/we56rz19

Abstract

The issue of withdrawal behavior is critical because it disrupts productivity and stability in technology-based startups. This study aims to determine whether the ability to redesign one’s own work plays a role in addressing withdrawal behavior among employees in technology-based startups. This quantitative study of technology-based startups employed a simple linear regression approach and was conducted among 202 employees of startups in Indonesia. The research instruments included the Job Crafting and Organizational Withdrawal Behavior scales, which have been validated for reliability and validity. The results of the data analysis indicate that employees’ ability to redesign their own work significantly influences withdrawal behavior. In other words, the higher an employee’s ability to redesign their own work, the lower the level of withdrawal behavior exhibited. Thus, the conclusion of this study indicates that the level of an employee’s ability to redesign their own work in technology-based companies can reduce withdrawal behavior and has proven to be an effective strategy for addressing withdrawal behavior in the workplace of startups.
The Role of AI-Driven Recommendation Satisfaction in Repurchase Intention: A PRISMA-Based Systematic Review of E-Commerce Studies Hanifah Fadila Idwan; Fikria Nabila Ramadhani Fairuz; Paramitha Russelyva Azzahra; Tasya Augustiya
Psikologi Prima Vol. 9 No. 1 (2026): Psikologi Prima
Publisher : unprimdn.ac.id

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/psychoprima.v9i1.8101

Abstract

This study aims to systematically review the relationship between user satisfaction with artificial intelligence (AI)-based recommendation systems and repurchase intention on e-commerce platforms. As competition in the digital commerce sector intensifies, understanding how AI-driven personalization shapes consumer loyalty has become increasingly critical. This study employed a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, in which an initial search using keywords “AI recommendation”,” customer satisfaction”, and “repurchase intention” on the Scopus database yielded 400 documents published between 2020 and 2025. Following a multi-stage screening process including removal of non-eligible document types, evaluation of title and abstract relevance, and full-text accessibility checks, 40 articles were ultimately included for analysis. Findings consistently demonstrate that customer satisfaction functions as the dominant mediating variable between AI recommendation quality and repurchase intention. Personalized recommendation systems reduce users' information overload, while AI-powered chatbots with empathetic and proactive strategies further enhance satisfaction. The effectiveness of AI recommendations in driving repurchase intention is contextual and moderated by demographic factors such as gender, age, and digital literacy. These findings extend existing consumer behavior theory by integrating user experience as a critical dimension in assessing AI system effectiveness on e-commerce platforms.
Co-Authors Fikria Nabila Ramadhani Fairuz Hanifah Fadila Idwan Novia Astuti Dewi Paramitha Russelyva Azzahra