The seminar will take place on Tuesday, May 19th, from 12:00 to 13:00 (HG-05A36).
This is a lunch seminar; please register your attendance by accepting/declining your emailed invitation by Friday, May 15th at the latest (for catering).
Abstract
Algorithmic matching facilitates value creation on digital platforms by connecting users to content, services, and to one another. Prior research on outcomes of algorithmic matching across different contexts, however, typically conceptualizes matching outcomes as individual- or population-level effects observed at a static point in time, assuming that these outcomes are non-emergent. We challenge this assumption and argue that the core characteristics of algorithmic matching make emergent, system-level outcomes not only possible but likely. We identify three foundational characteristics, data fidelity, reductionist interaction rules, and user intention heterogeneity, that jointly increase the likelihood of mismatches, triggering user adaptation. Drawing on complex adaptive systems as a meta-theoretical lens, we develop a multi-level theory that explains how three interacting feedback mechanisms generate dynamic, path-dependent emergent outcomes: ecosystem-level growth and diversity feedback, platform-level design and governance feedback, and user-level behavioral adaptation and prediction feedback. We demonstrate how these three feedback mechanisms can lead to emergent outcomes via an agent-based simulation of a dating platform. Our theorizing advances research on matching and complexity in digital platforms and offers a foundation for evaluating the long-run implications of algorithmic design and governance choices.
ABRI Lunch Seminar Jonas Andersen 19 May 2026 12:00 - 13:00
About ABRI Lunch Seminar Jonas Andersen
Starting date
- 19 May 2026
Time
- 12:00 - 13:00
Location
- VU Main Building
- HG-05A36
Address
- De Boelelaan 1105
- 1081 HV Amsterdam
Organised by
- ABRI and the KIN Center for Digital Innovation
Language
- English
Biography Jonas Valbjørn Andersen
Jonas Valbjørn Andersen is associate professor of digital innovation and analytics in critical information systems in the Department of Management at Aarhus University. He has a background from the management consulting and IT industry and holds a Ph.D. in Information Systems and Management from Warwick Business School, University of Warwick, UK. His research focuses on digital innovation, analytics, and decision-making in critical information systems in finance, healthcare, defense, and agriculture. Specifically, he studies the balance between decentralisation and control in critical information systems. His research focuses on applying state-of-the-art data science and machine learning as well as simulation methods to organizational processes related to decision support or algorithmic decision-making. He primarily works on unstructured data including digital trace data typically collected from large-scale registers and systems logs as well as natural language processing and network analysis of open data sources. Data analysis is applied in combination with system modelling and simulation based on systems thinking in general and more specifically on a complex adaptive systems approach. His most recent research focuses on the application of advanced healthcare analytics in precision medicine and clinical decision support. His work aims to contribute with insights on application of data science to decision-making and on understanding the nature of data production, collection, cleaning, and modelling for decision-making outcomes related to critical information systems.