Information Systems: Academic Discipline — Prolific Citations Library

Explore 8 peer-reviewed papers in Information Systems (2021–2025). Academic research using Prolific for high-quality human data collection.

This page lists 8 peer-reviewed papers in the discipline of Information Systems in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.

Papers (8 of 8)

Taking the person seriously: Ethically aware IS research in the era of reinforcement learning-based personalization

Authors: T Greene, G Shmueli, S Ray

Year: 2025

Published in: Journal of the Association for ..., 2023 - aisel.aisnet.org

Institution: National Tsing Hua University, Copenhagen Business School

Research Area: Information Systems Ethics, Reinforcement Learning for Personalization

Discipline: Information Systems

The paper examines the ethical risks of reinforcement learning-based personalization and proposes three research directions for IS scholars to address its societal implications and inadequacies in existing regulations.

Methods: The study presents a conceptual analysis of emergent features and societal risks associated with reinforcement learning-based personalization and proposes research directions.

Key Findings: Potential harms of reinforcement learning-based personalization, such as reduced autonomy, social and political destabilization, and mass surveillance, alongside the limitations of current data protection laws.

DOI: https://aisel.aisnet.org/jais/vol24/iss6/6

Citations: 33
When AI-Based Agents Are Proactive: Implications for Competence and System Satisfaction in Human-AI Collaboration

Authors: C Diebel, M Goutier, M Adam, A Benlian

Year: 2025

Published in: Business & Information Systems ..., 2025 - Springer

Institution: Technical University of Darmstadt, University of Goettingen

Research Area: Human-AI Collaboration, System Satisfaction, User Competence

Discipline: Information Systems, Human-Computer Interaction (HCI), Artificial Intelligence

Proactive AI-based agent assistance decreases users' competence-based self-esteem and system satisfaction, especially for users with higher AI knowledge.

Methods: Vignette-based online experiment using self-determination theory as the framework to evaluate user responses to proactive vs. reactive AI assistance.

Key Findings: Impact of proactive vs. reactive AI help on users' competence-based self-esteem and system satisfaction, moderated by users' AI knowledge levels.

DOI: https://doi.org/10.1007/s12599-024-00918-y

Citations: 32
The effect of popularity cues and peer endorsements on assertive social media ads

Authors: A Agarwal, SY Lee

Year: 2025

Published in: Information Systems ..., 2025 - pubsonline.informs.org

Institution: University of Texas

Research Area: Information Systems, Behavioral Economics, Social Media Marketing, Advertising

Discipline: Information Systems Research, Marketing, Behavioral Science

This academic article explores a specific topic within the field of Information Systems Research.

Citations: 14
Perceived algorithmic fairness: An empirical study of transparency and anthropomorphism in algorithmic recruiting

Authors: J Ochmann, L Michels, V Tiefenbeck

Year: 2024

Published in: Information Systems ..., 2024 - Wiley Online Library

Institution: University of St. Gallen, Technische Universität München, ETH Zürich

Research Area: Algorithmic Fairness in Recruiting, Human-Algorithm Interaction, Transparency, Anthropomorphism.

Discipline: Information Systems

The study explores how transparency and anthropomorphism influence applicants' perceptions of algorithmic fairness in recruiting, revealing justice dimensions that shape these perceptions.

Methods: An online application scenario with eight experimental groups analyzing fairness perceptions using a stimulus-organism-response framework and organizational justice theory.

Key Findings: Perceptions of algorithmic fairness based on justice dimensions (procedural, distributive, interpersonal, and informational justice) and the impact of transparency and anthropomorphism interventions.

DOI: https://doi.org/10.1111/isj.12482

Citations: 65

Sample Size: 801
Fairness in algorithmic management: Bringing platform-workers into the fold

Authors: N Jabagi, AM Croteau, L Audebrand, J Marsan

Year: 2024

Published in: 2024 - aisel.aisnet.org

Institution: FSA ULaval, JMSB, Concordia

Research Area: Algorithmic management, Perceived fairness, Platform work, Information Systems

Discipline: Information Systems, Social Science

DOI: https://aisel.aisnet.org/hicss-57/cl/ai_and_future_work/5

Citations: 8
Examining the moderating role of online celebrity trustworthiness and risk propensity in UTAUT2 framework: A mixed-method approach

Authors: Ruturaj Baber, Prerana Baber, Sumit Narula

Year: 2024

Published in: Science Direct

Institution: Amity University Haryana, Christ University, Jiwaji University

Research Area: Online Celebrity Influence, Technology Acceptance (UTAUT2), Consumer Behavior

Discipline: Information Systems, Behavioral Science, Marketing
Transparency Fallacy: Perceived Fairness in Algorithmic Management: M. Mirbabaie et al.

Authors: M Mirbabaie, M Langer, J Rieskamp

Year: 2022

Published in: Business & Information ..., 2025 - Springer

Research Area: Algorithmic Management (AM), Perceived Fairness, Transparency, Human-Computer Interaction (HCI)

Discipline: Business, Information Systems

Citations: 2
Large language models and the wisdom of small crowds

Authors: S Trott

Year: 2021

Published in: Open Mind, 2024 - direct.mit.edu

Institution: Stanford University, Microsoft Research

Research Area: LLMs in Social Science Research, Crowdworking, Human Behavior Simulation

Discipline: Artificial Intelligence, Social Science, Information Systems

Citations: 22