Virtual Humans as Co-Workers: A Novel Methodology to Study Peer Effects

34 Pages Posted: 23 Sep 2016 Last revised: 21 Nov 2018

See all articles by Özgür Gürerk

Özgür Gürerk

University of Erfurt - Economics, Law, and Social Sciences

Andrea Bönsch

Visual Computing Institute

Thomas Kittsteiner

RWTH Aachen University - School of Business and Economics

Andreas Staffeldt

RWTH Aachen University - School of Economics and Business Administration

Date Written: November 20, 2018

Abstract

We introduce a novel methodology to study peer effects. Using virtual reality technology, we create a naturalistic work setting in an immersive virtual environment where we embed a computer-generated virtual human as the co-worker of a human subject, both performing a sorting task at a conveyor belt. In our setup, subjects observe the virtual peer, while the virtual human is not observing them. In two treatments, human subjects observe either a low productive or a high productive virtual peer. We find that human subjects rate their presence feeling of "being there" in the immersive virtual environment as natural. Subjects also recognize that virtual peers in our two treatments showed different productivities. We do not fi nd a general treatment effect on productivity. However, we fi nd that competitive subjects display higher performance when they are in the presence of a highly productive peer - compared to when they observe a low productive peer. We use tracking data to learn about the subjects' body movements. Analyzing hand and head data, we show that competitive subjects are more careful in the sorting task than non-competitive subjects. We also discuss some VR related methodological issues.

Keywords: peer effects, real effort, virtual reality, virtual human, reflection problem, immersive virtual environment

JEL Classification: C91, J24, M50

Suggested Citation

Gürerk, Özgür and Bönsch, Andrea and Kittsteiner, Thomas and Staffeldt, Andreas, Virtual Humans as Co-Workers: A Novel Methodology to Study Peer Effects (November 20, 2018). Available at SSRN: https://ssrn.com/abstract=2842411 or http://dx.doi.org/10.2139/ssrn.2842411

Özgür Gürerk (Contact Author)

University of Erfurt - Economics, Law, and Social Sciences ( email )

Nordhaeuser Str. 63
D - 99089 Erfurt
Germany

Andrea Bönsch

Visual Computing Institute ( email )

Templergraben 55
52056 Aachen, 52056
Germany

Thomas Kittsteiner

RWTH Aachen University - School of Business and Economics ( email )

Templergraben 55
52056 Aachen, 52056
Germany

Andreas Staffeldt

RWTH Aachen University - School of Economics and Business Administration ( email )

Aachen
Germany

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