Demo Data from VLDB 2026 / reviewers in the wild / expert
Özgür Gürerk
dblp:198/4190
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2017
0000-0001-7971-7319ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1Human-computer interaction and ubiquitous computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Immersive interaction · 50% Collaborative and social computing · 50% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational finance and economics · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Collaborative and social computing › social computing
peer influence |
0.3 | 1 | 2017 | Peers at work: Economic real-effort experiments in the presence of virtual co-workers · VR 2017 |
Immersive interaction
virtual reality experiments |
0.3 | 1 | 2017 | Peers at work: Economic real-effort experiments in the presence of virtual co-workers · VR 2017 |
Computational finance and economics › economics
experimental economics |
0.1 | 1 | 2017 | Peers at work: Economic real-effort experiments in the presence of virtual co-workers · VR 2017 |
Methods — techniques the papers use, named apart from their topics
real-effort task · 0.6incentivized experiment · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Peers at work: Economic real-effort experiments in the presence of virtual co-workersabstractTraditionally, experimental economics uses controlled and incentivized field and lab experiments to analyze economic behavior. However, investigating peer effects in the classic settings is challenging due to the reflection problem: Who is influencing whom? To overcome this, we enlarge the methodological toolbox of these experiments by means of Virtual Reality. After introducing and validating a real-effort sorting task, we embed a virtual agent as peer of a human subject, who independently performs an identical sorting task. We conducted two experiments investigating (a) the subject's productivity adjustment due to peer effects and (b) the incentive effects on competition. Our results indicate a great potential for Virtual-Reality-based economic experiments. Andrea Bönsch, Jonathan Wendt, Heiko Overath, Özgür Gürerk, Christine Harbring, Christian Grund, Thomas Kittsteiner, Torsten W. Kuhlen |
VR | 4 |