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Quantitative Movement Testing: Measuring Patient Movements from a Single Smartphone Video Vision-Language Models Suppress Female Representations Under Ambiguous Input The New Social Image: How AI Competency and AI Proactivity Influence Self- and Peer-Perceptions in the Workplace TUX: Measuring Human--AI Tacit Understanding LLUMI: Improving LLM Writing Assistance for Mental Health Support with Online Community Feedback VideoFDB: Evaluating Full-Duplex Vision-Speech Capabilities in Conversational Agents Label Over Logic? How Source Cues Bias Human Fallacy Judgments More Than LLMs Inform, Coach, Relate, Listen: Auditing LLM Caregiving Support Roles How Coding Agents Fail Their Users: A Large-Scale Analysis of Developer-Agent Misalignment in 20,574 Real-World Sessions MetaRanker: Human-in-the-loop Active Ranking for Metalens Image Quality Analyzing Persona Effects in Generated Explanations from Multimodal LLM Agents in Urban Perception First head-to-head comparison of agentic AI applied to the analysis of simulated data of the Einstein Telescope Granuscore: A Reference-Free Measure of Granularity for Text Analysis and Question Answering The Timing Dependencies of Trust: Speed, Accuracy, and cBCI Neuro-Decoupling in Human-AI Teams Bayesian Distributional Models of Executive Functioning Visual Matters: Connecting Aesthetic Appeal and Production Quality of Photos, Infographics and Data Visualizations to Credibility of Social Media Posts Data-driven Head Motion Generation through Natural Gaze-Head Coordination Agreement Metrics for LLM-as-Judge Evaluation: What to Report and Why Perceptually Lossless Tactile Texture Synthesis with Compact Spectral Envelope Models MambaGaze: Bidirectional Mamba with Explicit Missing Data Modeling for Cognitive Load Assessment from Eye-Gaze Tracking Data CogAdapt: Transferring Clinical ECG Foundation Models to Wearable Cognitive Load Assessment via Lead Adaptation Augmented Analytics and Decision Quality: The Role of Trust among Non-Technical BI Users Faster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They Build PaintCopilot: Modeling Painting as Autonomous Artistic Continuation Personality Engineering with AI Agents: A New Methodology for Negotiation Research PULSE: Agentic Investigation with Passive Sensing for Proactive Intervention in Cancer Survivorship Access Timing as Scaffolding: A Reinforcement Learning Approach to GenAI in Education Conversations in Space: Structuring Non-Linear LLM Interactions on a Canvas MAPLE: Self-Supervised Learning-Enhanced Nonlinear Dimensionality Reduction for Visual Analysis nASR: An End-to-End Trainable Neural Layer for Channel-Level EEG Artifact Subspace Reconstruction in Real-Time BCI
Status Quo, Critical Reflection and Road Ahead of Digital...
Christian Meske, Ireti Amojo · 2019-11-19 · via cs.HC updates on arXiv.org

Research on Digital Nudging has become increasingly popular in the Information Systems (IS) community. This paper presents an overview of the current progress, a critical reflection and an outlook to further research regarding Digital Nudging in IS. For this purpose, we conducted a comprehensive literature review as well as an interview with Markus Weinmann from Rotterdam School of Management at Erasmus University, one of the first scholars who introduced Digital Nudging to the IS community, and Alexey Voinov, director of the Centre on Persuasive Systems for Wise Adaptive Living at University of Technology Sydney. The findings uncover a gap between what we know about what constitutes Digital Nudging and how consequent requirements can actually be put into practice. In this context, the original concept of Nudging bears inherent challenges, e.g. regarding the focus on the individuals' welfare, which hence also apply to Digital Nudging. Moreover, we need a better understanding of how Nudging in digital choice environments differs from that in the offline world. To further distinguish itself from other disciplines that already tested various nudges in many different domains, Digital Nudging Research in IS may benefit from a strong Design Science perspective, going beyond the test of effectiveness and providing specific design principles for the different types of digital nudges.