BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Vrije Universiteit Amsterdam//NONSGML v1.0//EN
NAME:ABRI Lunch Seminar Jonas Andersen
METHOD:PUBLISH
BEGIN:VEVENT
DTSTART:20260519T120000
DTEND:20260519T130000
DTSTAMP:20260519T120000
UID:2026/abri-lunch-seminar-jonas-@8F96275E-9F55-4B3F-A143-836282E12573
CREATED:20260506T223317
LOCATION:HG-05A36 VU Main Building De Boelelaan 1105 1081 HV Amsterdam
SUMMARY:ABRI Lunch Seminar Jonas Andersen
X-ALT-DESC;FMTTYPE=text/html: We are happy to invite
you to the ABRI Lunch Seminar "Understanding and Anticipating the Eme
rgent Outcomes of Algorithmic Matching on Digital Platforms" by Dr. J
onas Andersen (Department of Management, Aarhus University) organized
by ABRI and the KIN Center for Digital Innovation.
The semina
r 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
Alg
orithmic matching facilitates value creation on digital platforms by
connecting users to content, services, and to one another. Prior rese
arch on outcomes of algorithmic matching across different contexts, h
owever, 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 a
nd argue that the core characteristics of algorithmic matching make e
mergent, system-level outcomes not only possible but likely. We ident
ify three foundational characteristics, data fidelity, reductionist i
nteraction rules, and user intention heterogeneity, that jointly incr
ease the likelihood of mismatches, triggering user adaptation. Drawin
g on complex adaptive systems as a meta-theoretical lens, we develop
a multi-level theory that explains how three interacting feedback mec
hanisms generate dynamic, path-dependent emergent outcomes: ecosystem
-level growth and diversity feedback, platform-level design and gover
nance feedback, and user-level behavioral adaptation and prediction f
eedback. We demonstrate how these three feedback mechanisms can lead
to emergent outcomes via an agent-based simulation of a dating platfo
rm. Our theorizing advances research on matching and complexity in di
gital platforms and offers a foundation for evaluating the long-run i
mplications of algorithmic design and governance choices.
DESCRIPTION: The seminar will take place on Tuesday, May 19th, from 12
:00 to 13:00 (HG-05A36).
This is a lunch seminar; please reg
ister your attendance by accepting/declining your emailed invitation
by Friday, May 15th at the latest (for catering).
Ab
stract
Algorithmic matching facilitates value creation on
digital platforms by connecting users to content, services, and to o
ne another. Prior research on outcomes of algorithmic matching across
different contexts, however, typically conceptualizes matching outco
mes as individual- or population-level effects observed at a static p
oint in time, assuming that these outcomes are non-emergent. We chall
enge this assumption and argue that the core characteristics of algor
ithmic matching make emergent, system-level outcomes not only possibl
e but likely. We identify three foundational characteristics, data fi
delity, reductionist interaction rules, and user intention heterogene
ity, that jointly increase the likelihood of mismatches, triggering u
ser adaptation. Drawing on complex adaptive systems as a meta-theoret
ical lens, we develop a multi-level theory that explains how three in
teracting feedback mechanisms generate dynamic, path-dependent emerge
nt outcomes: ecosystem-level growth and diversity feedback, platform-
level design and governance feedback, and user-level behavioral adapt
ation and prediction feedback. We demonstrate how these three feedbac
k mechanisms can lead to emergent outcomes via an agent-based simulat
ion of a dating platform. Our theorizing advances research on matchin
g and complexity in digital platforms and offers a foundation for eva
luating the long-run implications of algorithmic design and governanc
e choices. We are happy to invite you to the ABRI Lunch Seminar "Unde
rstanding and Anticipating the Emergent Outcomes of Algorithmic Match
ing on Digital Platforms" by Dr. Jonas Andersen (Department of Manage
ment, Aarhus University) organized by ABRI and the KIN Center for Dig
ital Innovation.
END:VEVENT
END:VCALENDAR