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All Journal ASEAN Marketing Journal Journal of Sustainability Industrial Engineering and Management System
Pradipta, Naufal
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Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences

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Perceptions on AI Fairness in Financial Recommendation Engines Pradipta, Naufal
Journal of Sustainability Industrial Engineering and Management System Vol. 3 No. 2 (2025): January - June
Publisher : Omnia Tempus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56953/jsiems.v3i2.48

Abstract

This research aims to explore the implications of machine learning algorithms on fairness, particularly in sensitive applications such as criminal justice, healthcare, consumer finance, and hiring systems. The study examines how algorithmic biases can perpetuate social inequities, focusing on racial and gender disparities in automated decision-making processes. The research employs a qualitative approach through a comprehensive literature review, synthesizing findings from various case studies and articles that highlight algorithmic bias in real-world scenarios. The analysis discusses the impact of these biases, outlining the risks they present in shaping public perception and trust in AI technologies. Findings from the review emphasize the need for greater transparency in algorithmic models and the implementation of bias-correction strategies. The study also highlights the importance of ensuring fairness in AI-driven processes, particularly in contexts where life-altering decisions, such as hiring and healthcare, are made. Ultimately, the research calls for the development of ethical frameworks and regulatory measures that promote algorithmic fairness while safeguarding individuals' rights. This work contributes to the ongoing discourse on AI ethics and offers recommendations for policymakers, technologists, and organizations to address the challenges of algorithmic fairness.
Revisiting Integrated Mobile Advertising Model in Indonesia: A Replication Study Pradipta, Naufal; Santoso, Adhi S; Nelloh, Liza Agustina M
ASEAN Marketing Journal Vol. 14, No. 1
Publisher : UI Scholars Hub

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Abstract

Manuscript type: Research Article Research Aims: Kim's previous study proposed a web advertising model such as personalization and flow theory toward purchase intention and its antecedents. The current research will re-assess the model in Indonesia. Design/methodology/approach: Using Structural Equation Modelling (SEM) toward 211 respondents Research Findings: This study showed that credibility is insignificant to advertising value and flow experience, and entertainment and incentives are insignificant to flow experience. Thus, informativeness is insignificant to advertising value and flow experience. Hence irritation is also insignificant to advertising value and flow experience. However, personalization showed a significant effect on flow experience but insignificant toward advertising value. Theoretical Contribution/Originality: Insignificant effect of the web advertising model, such as personalization and flow theory toward purchase intention and its antecedents Practitioner/Policy Implication: The promotion process on smartphone media to implement the web advertising model.
Co-Authors Nelloh, Liza Agustina M Santoso, Adhi S