Experimental economics uses controlled and incentivized lab and field experiments to learn about economic behavior. By means of three examples, we illustrate how experiments conducted in immersive virtual environments can benefit (experimental) economic research

Braun, Lucas

Bönsch, Andrea

Grund, Christian

Gürerk, Özgür

Harbring, Christine

Kittsteiner, Thomas

Staffeldt, Andreas

Munich Personal RePEc Archive

MPRA
Munich Personal RePEc Archive
Experimental Economics in Virtual
Reality
O¨zgu¨r Gu¨rerk and Andrea Bo¨nsch and Lucas Braun and
Christian Grund and Christine Harbring and Thomas
Kittsteiner and Andreas Staffeldt
RWTH Aachen University
December 2014
Online at https://mpra.ub.uni-muenchen.de/66617/
MPRA Paper No. 66617, posted 14. September 2015 19:21 UTC
Experimental Economics in Virtual Reality 1
Experimental Economics in Virtual Reality
Oculus and Co. will establish a new experimental method in economic research
Özgür Gürerk1,*, Andrea Bönsch2, Lucas Braun1, Christian Grund1, Christine Harbring1,
Thomas Kittsteiner1, & Andreas Staffeldt1
1: School of Business and Economics, RWTH Aachen University
2: Virtual Reality Group, RWTH Aachen University
Abstract: Experimental economics uses controlled and incentivized lab and field experiments
to learn about economic behavior. By means of three examples, we illustrate how experiments
conducted in immersive virtual environments can benefit (experimental) economic research.
*: Corresponding author: Özgür Gürerk, Professor of Experimental Economics, RWTH
Aachen University, Templergraben 64, 52062 Aachen, Germany, ozgur.gurerk@rwth-
aachen.de, www.expecon.de.
Recent developments in virtual reality (VR) technology have the potential to revolutionize the
way economists do experimental research. With Oculus’ light and affordable head mounted
display (HMD) human subjects can literally move and use objects in virtual spaces and
interact with others. This technology as well as surround-screen projection systems like
CAVEs (Cruz-Neira et al., 1993), allow the experimenter to observe economically relevant
behavior and social interaction in a highly immersive and at the same time tightly controlled
virtual environment.
Experimental Economics in Virtual Reality 2
Previous applications of VR in (experimental) economics were mainly limited to research in
low immersive virtual worlds, e.g. Second Life (see e.g., Chesney et al., 2009; Füllbrunn et
al., 2011), where immersion, i.e., the feeling of “being there”, is perceived only indirectly
through mouse-controlled avatars, i.e., virtual representations of human subjects. While
virtual worlds have some remarkable research potential (Bainbridge, 2007), they also have
very important drawbacks for experimental research, e.g., the loss of control over subjects’
characteristics (Duffy, 2011). This led economists only recently to begin utilizing controlled
virtual world experiments (Twieg & McCabe, 2014).
Blascovich et al. (2002) suggested the use of immersive virtual environments (IVEs) as a
methodological tool in (social) psychology. They, together with others, discovered that
humans indeed perceive highly IVEs as “real”. This phenomenon is referred to as presence
(Slater et al., 1994). Due to high costs, however, for a decade, social science research using
VR was limited to few labs and small sample sizes. Recently, affordable HMDs and other
periphery devices accelerated research in social sciences, such as social psychology to study
social evaluation situations (Schmid et al., 2013), in clinical psychology for treatment of
social disorders (Falconer et al., 2014), or in linguistics for understanding the role of gestures
in human communication (Staum Casasanto et al., 2010).
More than other disciplines, economics focuses on the evaluation of counterfactual scenarios
which help to analyze strategic decisions and their efficiency effects. Counterfactuals,
however, are not easily observable, not even in field experiments. On the other hand,
counterfactual scenarios in the conventional lab settings are often perceived as “sterile
environments” since they are not embedded in a natural frame (Harrison & List, 2004).
Experiments in highly IVEs could fill a gap by enabling us to test counterfactuals in an
exactly controlled but more realistic setup. One could also test settings that would be very
costly or simply impossible to implement in the field, e.g., due to physical restrictions or
Experimental Economics in Virtual Reality 3
ethical reasons. In the next paragraphs, by means of three examples, we illustrate how
experiments in highly IVEs can add value to experimental economics and benefit economic
research.
Naturalistic representation: Eliciting (risk) preferences
Preferences expressed and economic decisions taken by human subjects can depend on
perceptions of the external context and environment in which a decision problem is presented.
A subject who experiences “physical” presence in VR may automatically suppress that she is
participating in an experiment displaying a more “natural” behavior. Economists have used
the passive observation of 3D modeled wildfires on monitors to evaluate subjects’ perception
of risks, and driving simulators to elicit risk preferences. By applying a low IVE to a context
of evaluation choices, they combine “the strengths of the artefactual controls of laboratory
experiments with the naturalistic domain of field experiments or direct field studies” (Fiore et
al., 2013). These advantages are very likely to be more pronounced in highly IVEs (cf.
Cummings & Bailenson, 2015).
Tracking & realistic interactive tasks: Breaking the limits of real effort experiments in
the lab
VR labs allow subjects to perform more natural tasks than in traditional labs where this is
confined to a 2D computer screen. Furthermore, tracking in VR enables measuring a subject’s
position, orientation, and movements in space. In a current study conducted in the CAVE of
the RWTH Aachen University, we capture exact measures of subject’s effort not in only one
but in several dimensions (Gürerk et al., 2014). In our setup, the subject is inside a virtual
production hall. There, she physically works at a virtual conveyor belt sorting out virtual
cubes with a defect. To check for defects, the subject can literally grasp and rotate the cubes.
We are able to measure performance multidimensionally by taking the number of not rejected
Experimental Economics in Virtual Reality 4
cubes with various types of defects, the number of rejected cubes without defects, the number
of grasps and the duration of grasps into account. We can evaluate how subjects make the
trade-off between quantity and quality as a function of the economic incentives provided.
Other dimensions of tracking such as precision of grasps, body movement and eye tracking
can also be included.
Panel a: aixCAVE Panel b: HMD
Figure 1: Panel a: Subject interacting with a virtual cube in the aixCAVE of the RWTH
Aachen University. Panel b: Person with HMD grasping a virtual object.
The magic of co-presence: Solving the reflection puzzle through human-avatar
interaction
Using virtual humans in social interactions (Schroeder, 2011) creates the opportunity to
analyze causal relationships between simultaneously observed individuals’ (or groups’)
behavior, which in traditional experiments is severely hampered due to the well-known
reflection problem (Manski, 1993). In the setup explained in the section before, we introduce
a virtual co-worker, i.e., a computer-controlled avatar who works at a parallel conveyor belt
Experimental Economics in Virtual Reality 5
and is observable by the human subject (Gürerk et al., 2015). The virtual co-worker exhibits
different working behavior from slow to fast or precise to careless, respectively. Since the
human subject cannot influence the virtual co-worker, we can rule out the identification
problem. This enables us to observe non-confounded peer effects of the avatars’ work speed
and work care on the human subject’s performance. As a further related idea, physically or
behaviorally pre-programmed avatars may help overcome cultural barriers when conducting
experiments with participants coming from different parts of the world.
Figure 2: Subject working in the aixCAVE of the RWTH Aachen University in the
presence of a virtual co-worker.
Challenges
The main challenge in conducting experimental research within IVEs is the trade-off between
costs and internal as well as external validity. Using more costly VR systems like a CAVE
instead of a low-cost HMD usually increases the immersion, as subjects can perceive their
complete (physical) body, especially their interacting hands. Furthermore, an avatar's realistic
Experimental Economics in Virtual Reality 6
visualization and movements crucially affect its acceptance by the subjects. Modeling natural
interaction patterns of avatars used to be a fundamental technological issue, but recent
developments in optical tracking technology brought improvements with affordable prices.
Conclusion
Currently, experts as Jaron Lanier or entrepreneurs as Mark Zuckerberg expect a great future
for VR in entertainment as well as in transforming human communication and collaboration
in shared virtual spaces, e.g., virtual shopping or doctor visits. We believe the new
possibilities have also great potential to take experimenting in economics to the next level, by
enabling us to elicit preferences more reliably, by leading to a better understanding of the
relation between incentives and effort, and by the investigation of economic (and social)
interactions in a way never possible before.
References
Bainbridge, W. S. (2007). The scientific research potential of virtual worlds. Science 317,
472–476.
Blascovich, J., Loomis, J., Beall, A.C., Swinth, K.R., Hoyt, C.L., and Bailenson, J.N. (2002).
Immersive Virtual Environment Technology as a Methodological Tool for Social Psychology.
Psychol. Inq. 13, 103–124.
Chesney, T., Chuah, S.-H., & Hoffmann, R. (2009). Virtual world experimentation: An
exploratory study. Journal of Economic Behavior & Organization, 72(1), 618–635.
Cruz-Neira, C., Sandin, D. J. & DeFanti, T. A. (1993). Surround-screen projection-based
virtual reality: the design and implementation of the CAVE. Proceedings of the ACM
SIGGRAPH ’93 Conference on Computer Graphics, 135–142.
Experimental Economics in Virtual Reality 7
Cummings, J. J., & Bailenson, J. N. (2015). How Immersive Is Enough? A Meta-Analysis of
the Effect of Immersive Technology on User Presence. Media Psychology, 0(0), 1–38.
Duffy, John. Trust in Second Life. (2011). Southern Economic Journal 78, 53-62.
Falconer CJ, Slater M, Rovira A, King JA, Gilbert P, et al. (2014). Embodying Compassion:
A Virtual Reality Paradigm for Overcoming Excessive Self-Criticism. PLoS ONE 9(11):
e111933.
Fiore, S. M., Harrison, G. W., Hughes, C. E. & Rutström, E. E. (2009). Virtual experiments
and environmental policy - Frontiers of Environmental and Resource Economics. J. Environ.
Econ. Manage. 57: 65–86.
Füllbrunn, S., Richwien, K. & Sadrieh, A. (2011). Trust and Trustworthiness in Anonymous
Virtual Worlds. J. Media Econ. 24, 48–63.
Gürerk, Ö., Grund, C., Harbring, C., Kittsteiner, T., & Staffeldt., A., (2014). Real Effort on
the Holodeck: Experimental Economics in Virtual Reality. http://ssrn.com/abstract=2544739.
Gürerk, Ö., Kittsteiner, T., Bönsch, A., & Staffeldt., A., (2015). Avatars at Work: Do Peer
Effects Really Exist? RWTH Aachen University.
Harrison, G. W. & List, J. A. (2004). Field Experiments. J. Econ. Lit. 42, 1009–1055.
Manski, C. F. Identification of Endogenous Social Effects: The Reflection Problem. (1993).
Rev. Econ. Stud. 60, 531–542.
Slater, M., Usoh, M., & Steed, A. (1994). Depth of presence in virtual environments.
Presence, 3(2), 130–144.
Schroeder, R. (2011). Being There Together: Social interaction in shared virtual
environments. Oxford University Press.
Experimental Economics in Virtual Reality 8
Schmid, P. C. & Schmid Mast, M. (2013). Power increases performance in a social evaluation
situation as a result of decreased stress responses. Eur. J. Soc. Psychol. 43, 201–211.
Staum Casasanto, L., Jasmin, K., & Casasanto, D. (2010). Virtually accommodating: Speech
rate accommodation to a virtual interlocutor. In S. Ohlsson, & R. Catrambone (Eds.),
Proceedings of the 32nd Annual Conference of the Cognitive Science Society, pp. 127-132.
Austin, TX: Cognitive Science Society.
Twieg, P. B. and McCabe, K. A. (2014). The Determinants of Territorial Property Rights in a
Spatial Commons Experiment. SSRN: http://ssrn.com/abstract=2503260.
Appendix
Project Profiles
Experimental Economics in VR, School of Business and Economics, RWTH Aachen
University
Experimental Economics in VR is one of the key projects of the “Business & Behavioral
Metrics Lab” of the “Interdisciplinary Management Factory” at the School of Business and
Economics. The Business & Behavioral Metrics Lab, founded in 2012, aims at the
development of a series of techniques for a radically new concept in experimental economic
research. The idea is to analyze and quantify individual behavior in organizations and markets
that is supported with new technological measuring methods, e.g., virtual reality experiments,
under controlled laboratory conditions. Different work environments in organizations will be
replicated as realistically as possible through collaboration with other disciplines and their
technical expertise. More information about the project “Experimental Economics in VR”:
http://www.expecon.rwth-aachen.de/go/id/ffma/
Experimental Economics in Virtual Reality 9
Virtual Reality Group, IT Center, RWTH Aachen University
Since its inception in 1998, the VR Group has focused on two aspects: to conduct application-
oriented research in and provide access to methodology from the fields of virtual reality,
human computer interaction, and immersive visualization. The VR Group operates one the
largest VR labs in the world. Equipment and facilities range from small, desktop-scale
systems to the large facilities such as the aixCAVE, a 30 sqm visualization chamber which
makes it possible to interactively explore virtual environments. More information about the
VR Group:
http://www.itc.rwth-aachen.de/cms/IT-Center/Forschung-Projekte/~eubl/Virtuelle-
Realitaet/?lidx=1


Experimental Economics in Virtual Reality

Publikationsserver der RWTH Aachen University

Recent developments in virtual reality (VR) technology have the potential to revolutionize the way

economists do experimental research. With Oculus’ light and affordable head mounted display

(HMD) human subjects can literally move and use objects in virtual spaces and interact with others.

This technology as well as surround-screen projection systems like CAVEs (Cruz-Neira et al. 1994),

allow the experimenter to observe economically relevant behavior and social interaction in a highly

immersive and at the same time tightly controlled virtual environment. More than other disciplines, economics focuses on the evaluation of counterfactual scenarios which help to analyze strategic decisions and their efficiency effects. In this note, by means of three examples, we illustrate how experiments in highly IVEs can add value to experimental economics and benefit economic research

Munich RePEc Personal Archive

Munich Personal RePEc ArchiveExperimental Economics in VirtualRealityGürerk, Özgür and Bönsch, Andrea and Braun, Lucas andGrund, Christian and Harbring, Christine and Kittsteiner,Thomas and Staffeldt, AndreasRWTH Aachen UniversityDecember 2014Online at https://mpra.ub.uni-muenchen.de/62073/MPRA Paper No. 62073, posted 13 Feb 2015 20:53 UTCExperimental Economics in Virtual Reality 1Experimental Economics in Virtual RealityOculus and Co. will establish a new experimental method in economic researchÖzgür Gürerk1,*, Andrea Bönsch2, Lucas Braun1, Christian Grund1, Christine Harbring1, ThomasKittsteiner1, and Andreas Staffeldt11: School of Business and Economics, RWTH Aachen University2: Virtual Reality Group, RWTH Aachen UniversityDecember 2014*: Corresponding author: Özgür Gürerk, Professor of Experimental Economics, RWTH Aachen University,Templergraben 64, 52062 Aachen, Germany, ozgur.gurerk@rwth-aachen.de, www.expecon.de.Recent developments in virtual reality (VR) technology have the potential to revolutionize the wayeconomists do experimental research. With Oculus’ light and affordable head mounted display(HMD) human subjects can literally move and use objects in virtual spaces and interact with others.This technology as well as surround-screen projection systems like CAVEs (Cruz-Neira et al. 1994),allow the experimenter to observe economically relevant behavior and social interaction in a highlyimmersive and at the same time tightly controlled virtual environment.Previous applications of VR in (experimental) economics were mainly limited to research in lowimmersive virtual worlds, e.g. Second Life (see e.g., Chesney et al. 2009, Füllbrunn et al. 2011), whereimmersion, i.e., the feeling of “being there”, is perceived only indirectly through mouse-controlledavatars, i.e., virtual representations of human subjects. While virtual worlds have some remarkableresearch potential (Bainbridge 2007), they also have very important drawbacks for experimentalresearch, e.g., the loss of control over subjects’ characteristics (Duffy 2011). This led economists onlyrecently to begin utilizing controlled virtual world experiments (Twieg and McCabe 2014).Blascovich et al. (2002) suggested the use of immersive virtual environments (IVEs) as amethodological tool in (social) psychology. They, together with others, discovered that humansindeed perceive highly IVEs as „real“. This phenomenon is referred to as presence (Sanchez-Vives etal. 2005). Due to high costs, however, for a decade, social science research using VR was limited tofew labs and small sample sizes. Recently, affordable HMDs and other periphery devices acceleratedresearch in social sciences, such as social psychology to study social evaluation situations (Schmid etal. 2013), in clinical psychology for treatment of social disorders (Falconer et al. 2014), or in linguisticsfor understanding the role of gestures in human communication (Staum Casasanto et al. 2010).More than other disciplines, economics focuses on the evaluation of counterfactual scenarios whichhelp to analyze strategic decisions and their efficiency effects. Counterfactuals, however, are noteasily observable, not even in field experiments. On the other hand, counterfactual scenarios in theconventional lab settings are often perceived as “sterile environments” since they are not embeddedin a natural frame (Harrison and List 2004). Experiments in highly IVEs could fill a gap by enabling usto test counterfactuals in an exactly controlled but more realistic setup. One could also test settingsthat would be very costly or simply impossible to implement in the field, e.g., due to physicalrestrictions or ethical reasons. In the next paragraphs, by means of three examples, we illustrate howexperiments in highly IVEs can add value to experimental economics and benefit economic research.Experimental Economics in Virtual Reality 2Naturalistic representation: Eliciting (risk) preferencesPreferences expressed and economic decisions taken by human subjects can depend on perceptionsof the external context and environment in which a decision problem is presented. A subject whoexperiences “physical” presence in VR may automatically suppress that she is participating in anexperiment displaying a more “natural” behavior. Economists have used the passive observation of3D modeled wildfires on monitors to evaluate subjects’ perception of risks, and driving simulators toelicit risk preferences. By applying a low IVE to a context of evaluation choices, they combine “thestrengths of the artefactual controls of laboratory experiments with the naturalistic domain of fieldexperiments or direct field studies” (Fiore et al. 2013). These advantages are very likely to be morepronounced in highly IVEs.Tracking & realistic interactive tasks: Breaking the limits of real effort experiments in the labVR labs allow subjects to perform more natural tasks than in traditional labs where this is confined toa 2D computer screen. Furthermore, tracking in VR enables measuring a subject’s position,orientation, and movements in space. In a current study conducted in the CAVE of the RWTH AachenUniversity, we capture exact measures of subject’s effort not in only one but in several dimensions(Gürerk et al. 2014). In our setup, the subject is inside a virtual production hall. There, she physicallyworks at a virtual conveyor belt sorting out virtual cubes with a defect. To check for defects, thesubject can literally grasp and rotate the cubes. We are able to measure performancemultidimensionally by taking the number of not rejected cubes with various types of defects, thenumber of rejected cubes without defects, the number of grasps and the duration of grasps intoaccount. We can evaluate how subjects make the trade-off between quantity and quality as afunction of the economic incentives provided. Other dimensions of tracking such as precision ofgrasps, body movement and eye tracking can also be included.Panel a: aixCAVE Panel b: HMDFigure 1: Panel a: Subject interacting with a virtual cube in the aixCAVE of the RWTH Aachen University.Panel b: Person with HMD grasping a virtual object.Experimental Economics in Virtual Reality 3The magic of co-presence: Solving the reflection puzzle through human-avatar interactionUsing avatars in social interactions creates the opportunity to analyze causal relationships betweensimultaneously observed individuals’ (or groups’) behavior, which in traditional experiments isseverely hampered due to the well-known reflection problem (Manski 1995). In the setup explainedabove, we could introduce a computer-controlled avatar who works at a parallel conveyor belt and isobservable by the human subject. The avatar exhibits different working behavior from slow to fast orprecise to careless, respectively. Since the avatar is not influenced by the human subject, we can ruleout the identification problem enabling us to observe non-confounded peer effects of the avatars’work speed and work care on the human subject’s performance. As a further related idea, physicallyor behaviorally pre-programmed avatars may help overcome cultural barriers when conductingexperiments with participants coming from different parts of the world.ChallengesThe main challenge in conducting experimental research within IVEs is the trade-off between costsand internal as well as external validity. Using more costly VR systems like a CAVE instead of a low-cost HMD usually increases the immersion, as subjects can perceive their complete (physical) body,especially their interacting hands. Furthermore, an avatar's realistic visualization and movementscrucially affect its acceptance by the subjects. Modeling natural interaction patterns of avatars usedto be a fundamental technological issue, but recent developments in optical tracking technologybrought improvements with affordable prices.ConclusionCurrently, experts as Jaron Lanier or entrepreneurs as Mark Zuckerberg expect a great future for VRin entertainment as well as in transforming human communication and collaboration in sharedvirtual spaces, e.g., virtual shopping or doctor visits. We believe the new possibilities have also greatpotential to take experimenting in economics to the next level, by enabling us to elicit preferencesmore reliably, by leading to a better understanding of the relation between incentives and effort, andby the investigation of economic (and social) interactions in a way never possible before.ReferencesBainbridge, W. S. 2007. The scientific research potential of virtual worlds. Science 317, 472–476.Blascovich, J., Loomis, J., Beall, A.C., Swinth, K.R., Hoyt, C.L., and Bailenson, J.N. 2002. Immersive VirtualEnvironment Technology as a Methodological Tool for Social Psychology. Psychol. Inq. 13, 103–124.Cruz-Neira, C., Sandin, D. J. & DeFanti, T. A. 1993. Surround-screen projection-based virtual reality: the designand implementation of the CAVE. Proceedings of the ACM SIGGRAPH ’93 Conference on Computer Graphics,135–142.Chesney, T., Chuah, S.-H., & Hoffmann, R. 2009. Virtual world experimentation: An exploratory study. Journalof Economic Behavior & Organization, 72(1), 618–635.Duffy, John. Trust in Second Life. 2011. Southern Economic Journal 78, 53-62.Falconer CJ, Slater M, Rovira A, King JA, Gilbert P, et al. 2014. Embodying Compassion: A Virtual RealityParadigm for Overcoming Excessive Self-Criticism. PLoS ONE 9(11): e111933.Fiore, S. M., Harrison, G. W., Hughes, C. E. & Rutström, E. E. 2009. Virtual experiments and environmentalpolicy - Frontiers of Environmental and Resource Economics. J. Environ. Econ. Manage. 57: 65–86.Experimental Economics in Virtual Reality 4Füllbrunn, S., Richwien, K. & Sadrieh, A. 2011. Trust and Trustworthiness in Anonymous Virtual Worlds. J.Media Econ. 24, 48–63.Gürerk, Ö., Grund, C., Harbring, C., Kittsteiner, T., Staffeldt., A., 2014. Real Effort on the Holodeck: ExperimentalEconomics in Virtual Reality. http://ssrn.com/abstract=2544739.Harrison, G. W. & List, J. A. 2004. Field Experiments. J. Econ. Lit. 42, 1009–1055.Manski, C. F. Identification of Endogenous Social Effects: The Reflection Problem. 1993. Rev. Econ. Stud. 60,531–542.Sanchez-Vives, M. V. & Slater, M. 2005. From presence to consciousness through virtual reality. Nat. Rev.Neurosci. 6, 332–339.Schmid, P. C. & Schmid Mast, M. 2013. Power increases performance in a social evaluation situation as a resultof decreased stress responses. Eur. J. Soc. Psychol. 43, 201–211.Staum Casasanto, L., Jasmin, K., & Casasanto, D. 2010. Virtually accommodating: Speech rate accommodationto a virtual interlocutor. In S. Ohlsson, & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference ofthe Cognitive Science Society, pp. 127-132. Austin, TX: Cognitive Science Society.Twieg, P. B. and McCabe, K. A. 2014. The Determinants of Territorial Property Rights in a Spatial CommonsExperiment. SSRN: http://ssrn.com/abstract=2503260.AppendixProject ProfilesExperimental Economics in VR, School of Business and Economics, RWTH Aachen UniversityExperimental Economics in VR is one of the key projects of the “Business & Behavioral Metrics Lab”of the “Interdisciplinary Management Factory” at the School of Business and Economics. TheBusiness & Behavioral Metrics Lab, founded in 2012, aims at the development of a series oftechniques for a radically new concept in experimental economic research. The idea is to analyze andquantify individual behavior in organizations and markets that is supported with new technologicalmeasuring methods, e.g., virtual reality experiments, under controlled laboratory conditions.Different work environments in organizations will be replicated as realistically as possible throughcollaboration with other disciplines and their technical expertise. More information about the project“Experimental Economics in VR”: http://www.expecon.rwth-aachen.de/go/id/ffma/Virtual Reality Group, IT Center, RWTH Aachen UniversitySince its inception in 1998, the VR Group has focused on two aspects: to conduct application-oriented research in and provide access to methodology from the fields of virtual reality, humancomputer interaction, and immersive visualization. The VR Group operates one the largest VR labs inthe world. Equipment and facilities range from small, desktop-scale systems to the large facilitiessuch as the aixCAVE, a 30 sqm visualization chamber which makes it possible to interactively explorevirtual environments. More information about the VR Group:http://www.itc.rwth-aachen.de/cms/IT-Center/Forschung-Projekte/~eubl/Virtuelle-Realitaet/?lidx=1

Experimental economics uses controlled and incentivized lab and field experiments to learn about economic behavior. By means of three examples, we illustrate how experiments conducted in immersive virtual environments emerge as a new methodological tool that can benefit behavioral economic research

MPRA
Munich Personal RePEc Archive
Experimental Economics in Virtual
Reality
O¨zgu¨r Gu¨rerk and Andrea Bo¨nsch and Lucas Braun and
Christian Grund and Christine Harbring and Thomas
Kittsteiner and Andreas Staffeldt
RWTH Aachen University
December 2014
Online at https://mpra.ub.uni-muenchen.de/71409/
MPRA Paper No. 71409, posted 22 May 2016 14:46 UTC
Experimental Economics in Virtual Reality
First Version: December 2014. This Version: May 2016
O¨zgu¨r Gu¨rerk∗† Andrea Bo¨nsch‡ Lucas Braun∗
Christian Grund∗ Christine Harbring∗ Thomas Kittsteiner∗
Andreas Staffeldt∗
Experimental economics uses controlled and incentivized lab and field ex-
periments to learn about economic behavior. By means of three examples,
we illustrate how experiments conducted in immersive virtual environments
emerge as a new methodological tool that can benefit behavioral economic
research.
1 Introduction
Recent developments in virtual reality (VR) technology have the potential to revolution-
ize the way social scientists do experimental research. With light and affordable head
mounted displays (HMD), such as Oculus’ Rift or HTC’s Vive, human subjects can be
“immersed” into virtual environments. When combining this technology with tracking
devices, subjects can literally move and use objects in virtual spaces, or – given multi-
ple connected setups – interact with other subjects in virtual reality. This technology
as well as surround-screen projection systems like CAVEs (Cruz-Neira, Sandin, & De-
Fanti, 1993) allow the experimenter to observe economically relevant behavior and social
interaction in a natural, and at the same time tightly controlled virtual environment.
Jim Blascovich et al. suggested the use of immersive virtual environments as a
methodological tool in social psychology, and conducted some of the very first exper-
imental studies (Loomis, Blascovich, & Beall, 1999; Blascovich et al., 2002). Their
∗School of Business and Economics, RWTH Aachen University
†Corresponding author: O¨zgu¨r Gu¨rerk, RWTH Aachen University, Templergraben 64, 52062 Aachen,
Germany, ozgur.gurerk@rwth-aachen.de, www.vrexperiments.net.
‡Visual Computing Institute, RWTH Aachen University
1
research, together with other scholars’ contributions, show that humans indeed perceive
immersive virtual environments as natural. This phenomenon of feeling “being there” in
the virtual environment is referred to as presence (Slater, Usoh, & Steed, 1994). While
presence describes a subjective experience, immersion refers to the technological aspects
of the virtual environment, such as the resolution and the “field of view” of the displays,
the quality of the tracking system etc.
Due to high costs, however, until recently, social science research using virtual reality
was limited to few labs and small sample sizes. Recently, affordable HMDs and other
periphery devices, for example the Microsoft kinect for full body tracking or the LEAP
motion controller for hand tracking, have become available and accelerated research. A
study by Bombari et al.(2015) discusses the unique added value of VR technology for
social interaction research and reviews the recent literature in this field.
Previous applications of virtual reality in experimental economics were mainly limited
to research in desktop virtual worlds like Second Life (Chesney, Chuah, & Hoffmann,
2009; Atlas & Putterman, 2011; Fiedler, Haruvy, & Li, 2011; Fu¨llbrunn, Richwien, &
Sadrieh, 2011; Greiner, Caravella, & Roth, 2014). In virtual worlds, however, the degree
of immersion is low, as visual information is mediated through 2D monitors, and the
interaction with objects and other users is executed through mouse-controlled avatars
(virtual representations of humans). While virtual worlds have some remarkable research
potential (Bainbridge, 2007; Haruvy, 2011), they also have very important drawbacks for
experimental research, as the loss of control over subjects’ characteristics (Duffy, 2011).
This led economists only recently to begin utilizing controlled virtual world experiments
(Twieg & McCabe, 2014). A paper by (Harrison, Haruvy, & Rutstro¨m, 2011) discusses
the key concepts behind the experiments in virtual worlds and virtual reality.
2 Experimental Economics in Immersive Virtual Environments
More than other disciplines, economics focuses on the evaluation of counterfactual sce-
narios which help to analyze strategic decisions and their efficiency effects. Counterfac-
tuals, however, are not easily observable, not even in field experiments. On the other
hand, counterfactual scenarios in the conventional lab settings are often perceived as
“sterile environments” since they are not embedded in a natural frame (Harrison & List,
2004). Experiments in immersive virtual environments could fill a gap by enabling us
to test counterfactuals using setups that are as controlled as in the conventional labs,
but perhaps even more realistic. One could also test settings that would be very costly,
or simply impossible to implement in the field, due to physical restrictions or ethical
2
reasons.
In the next sections, by means of three examples, we illustrate the added value of
experiments in immersive virtual environments and how they may benefit behavioral
economic research.
2.1 Naturalistic representation: Eliciting (risk) preferences
Preferences expressed and economic decisions taken by human subjects can depend on
perceptions of the external context and environment in which a decision problem is pre-
sented. A subject who experiences a strong presence in virtual reality may automatically
suppress that she is participating in an experiment, and display a more natural behavior.
Glenn Harrison et al. conducted experiments in virtual reality, utilizing driving sim-
ulators to elicit subjects’ risk preferences (Dixit, Harrison, & Rutstro¨m, 2013), or using
flat monitors to show subjects 3D modeled wildfires, in order to evaluate their risk
perception (Fiore, Harrison, Hughes, & Rutstro¨m, 2009). The latter study finds that
subjects’ beliefs about risks are closer to actual risks when they are exposed to 3D ani-
mated wildfires compared to when they see still pictures of the same 3D animation. By
applying virtual reality to a context of evaluation choices, “the strengths of the artefac-
tual controls of laboratory experiments with the naturalistic domain of field experiments
or direct field studies” could be combined (Fiore et al., 2009).
2.2 Tracking & realistic interactive tasks: Breaking the limits of real effort
experiments in the lab
In immersive virtual environments, subjects can perform more natural tasks than in
traditional labs where this is confined to a 2D computer screen. Furthermore, tracking
in virtual reality enables measuring a subject’s position, orientation, and movements in
space. In a novel real effort experiment conducted in the aixCAVE of the RWTH Aachen
University, we capture exact measures of subject’s effort not in only one but in several
dimensions (Gu¨rerk, Grund, Harbring, Kittsteiner, & Staffeldt, 2014).
In our setup, the subject is inside a virtual production hall. There, she physically
works at a virtual conveyor belt, sorting out virtual cubes with a defect. To check for
defects, the subject can literally grasp and rotate the cubes with the own hand. We are
able to measure performance multidimensionally by taking the number of not rejected
cubes with various types of defects, the number of rejected cubes without defects, the
number of grasps and the duration of grasps into account. We can evaluate how subjects
make the trade-off between quantity and quality as a function of the economic incentives
3
(a) aixCAVE (b) HMD
Figure 1: (a) Subject interacting with a virtual cube in the aixCAVE of the RWTH
Aachen University. (b) A participant of the Econ. Science Assoc. Meeting
trying our demo with a HMD, Dallas, October 2015.
provided. Other dimensions of tracking such as precision of grasps, body movement and
eye tracking could also be included.
Using a variant of the immersive virtual environment introduced above, (DeHoratius,
Gu¨rerk, Honhon, & Hyndman, 2015) investigate whether and how product similarity
affects execution failures in a retail setting when workers must identify and sort products
based on their observable characteristics. Introducing a clear visual cue to distinguish
the products improves execution when the products are dissimilar (by lowering sorting
mistakes) and, even more so, when they are similar (both by reducing sorting mistakes
and the number of products unsorted).
2.3 The magic of co-presence: Solving the reflection puzzle through human-avatar
interaction
Using virtual humans in social interactions (Schroeder, 2010) creates the opportunity to
analyze causal relationships between simultaneously observed individuals’ (or groups’)
behavior, which in traditional experiments is severely hampered due to the well-known
reflection problem (Manski, 1993). In the setup explained in the section before, we
introduce a computer-controlled virtual human who works at a parallel conveyor belt
and is observable by the human subject (Gu¨rerk, Kittsteiner, Bo¨nsch, & Staffeldt, 2015).
The virtual co-worker exhibits different working behavior from slow to fast, respectively.
4
Figure 2: Subject working in the aixCAVE of the RWTH Aachen University in the pres-
ence of a virtual human.
Since the human subject cannot influence the virtual co-worker, we can rule out the
identification problem. This enables us to observe non-confounded peer effects of the
virtual human’s work speed and work care on the human subject’s performance.
As a further related idea, physically or behaviorally pre-programmed virtual humans
may help overcome cultural barriers when conducting experiments with participants
coming from different parts of the world.
3 Challenges
One of the challenges in conducting experimental research within immersive virtual
environments is the trade-off between costs and internal as well as external validity.
Using more costly virtual reality systems like a CAVE instead of a low-cost HMD usually
increases the presence, as subjects can perceive their complete (physical) body, especially
their interacting hands.
Furthermore, virtual humans’ realistic visualization and movements crucially affect its
acceptance by the subjects and how humans interact with them (Kasap & Magnenat-
Thalmann, 2007). Modeling natural interaction patterns of virtual humans used to be a
fundamental technological issue, but recent developments in optical tracking technology
brought improvements with affordable prices.
As more and more research is conducted in immersive virtual environments, scholars
5
must also investigate possible (lasting) effects of the VR technology on subject’s behavior
(in real life). A recent study covers this important topic (Madary & Metzinger, 2016),
making recommendations for a good scientific practice for VR research with humans.
4 Conclusion
Currently, experts as Jaron Lanier who popularized the term “virtual reality”, or en-
trepreneurs as Mark Zuckerberg expect a great future for virtual reality in entertainment
as well as in transforming human communication and collaboration in shared virtual
spaces. In a post dated 25 March 2014, Mark Zuckerberg announces the acquisition of
HMD-maker Oculus VR by Facebook and states: “After games, we’re going to make
Oculus a platform for many other experiences. Imagine enjoying a court side seat at a
game, studying in a classroom of students and teachers all over the world or consulting
with a doctor face-to-face – just by putting on goggles in your home.”1
We believe the new possibilities have also great potential to take experimenting in
economics to the next level, by enabling us to elicit preferences more reliably, by leading
to a better understanding of the relation between incentives and effort, and by the
investigation of social interactions in a way never possible before.
References
Atlas, S., & Putterman, L. (2011). Trust among the avatars: A virtual world experi-
ment, with and without textual and visual cues. Southern Economic Journal , 78 (1),
63–86.
Bainbridge, W. S. (2007). The scientific research potential of virtual worlds. Science,
317 (5837), 472–476.
Blascovich, J., Loomis, J., Beall, A. C., Swinth, K. R., Hoyt, C. L., & Bailenson, J. N.
(2002). Immersive virtual environment technology as a methodological tool for social
psychology. Psychological Inquiry , 13 (2), 103–124.
Bombari, D., Schmid Mast, M., Canadas, E., & Bachmann, M. (2015). Studying social
interactions through immersive virtual environment technology: virtues, pitfalls, and
future challenges. Frontiers in Psychology , 6 .
Chesney, T., Chuah, S.-H., & Hoffmann, R. (2009). Virtual world experimentation: An
exploratory study. Journal of Economic Behavior & Organization, 72 (1), 618–635.
1Quote taken from the post on: https://www.facebook.com/zuck/posts/10101319050523971
6
Cruz-Neira, C., Sandin, D. J., & DeFanti, T. A. (1993). Surround-screen projection-
based virtual reality: the design and implementation of the cave. In Proceedings of the
20th annual conference on computer graphics and interactive techniques (pp. 135–142).
DeHoratius, N., Gu¨rerk, O¨., Honhon, D., & Hyndman, K. (2015). Understanding the
behavioral drivers of execution failures in retail supply chains: An experimental study
using virtual reality. Chicago Booth Research Paper No. 15-47 .
Dixit, V., Harrison, G. W., & Rutstro¨m, E. (2013). Estimating the subjective risks of
driving simulator accidents. Accident Analysis and Prevention, 62 , 63–78.
Duffy, J. (2011). Trust in second life. Southern Economic Journal , 78 (1), 53–62.
Fiedler, M., Haruvy, E., & Li, S. X. (2011). Social distance in a virtual world experi-
ment. Games and Economic Behavior , 72 (2), 400–426.
Fiore, S. M., Harrison, G. W., Hughes, C. E., & Rutstro¨m, E. (2009). Virtual exper-
iments and environmental policy. Journal of Environmental Economics and Manage-
ment , 57 (1), 65–86.
Fu¨llbrunn, S., Richwien, K., & Sadrieh, A. (2011). Trust and trustworthiness in
anonymous virtual worlds. Journal of Media Economics, 24 (1), 48–63.
Greiner, B., Caravella, M., & Roth, A. (2014). Is avatar-to-avatar communication as
effective as face-to-face Communication?–An ultimatum game experiment in first and
second life. Journal of Economic Behavior and Organization.
Gu¨rerk, O¨., Grund, C., Harbring, C., Kittsteiner, T., & Staffeldt, A.
(2014). Real effort on the holodeck: Experimental economics in virtual reality.
http://ssrn.com/abstract=2544739 .
Gu¨rerk, O¨., Kittsteiner, T., Bo¨nsch, A., & Staffeldt, A. (2015). Avatars as peers at
work: An experimental study in virtual reality. RWTH Aachen University .
Harrison, G., Haruvy, E., & Rutstro¨m, E. (2011). Remarks on virtual world and virtual
reality experiments. Southern Economic Journal , 78 (1), 87–94.
Harrison, G., & List, J. A. (2004). Field experiments. Journal of Economic Literature,
1009–1055.
Haruvy, E. (2011). Challenges and opportunities in economics experiments in virtual
worlds. Southern Economic Journal .
Kasap, Z., & Magnenat-Thalmann, N. (2007). Intelligent virtual humans with auton-
omy and personality: State-of-the-art. Intelligent Decision Technologies, 1 (1), 3–15.
Loomis, J. M., Blascovich, J. J., & Beall, A. C. (1999). Immersive virtual environ-
ment technology as a basic research tool in psychology. Behavior Research Methods,
Instruments, & Computers, 31 (4), 557–564.
7
Madary, M., & Metzinger, T. K. (2016). Recommendations for good scientific practice
and the consumers of VR-Technology. Frontiers in Robotics and AI , 3 .
Manski, C. F. (1993). Identification of endogenous social effects: The reflection prob-
lem. The Review of Economic Studies, 60 (3), 531–542.
Schroeder, R. (2010). Being there together: Social interaction in shared virtual envi-
ronments. Oxford University Press.
Slater, M., Usoh, M., & Steed, A. (1994). Depth of presence in virtual environments.
Presence, 3 (2), 130–144.
Twieg, P. B., & McCabe, K. A. (2014). The determinants of territorial property rights
in a spatial commons experiment. Available at SSRN 2503260 .
8


MPRA
Munich Personal RePEc Archive
Experimental Economics in Virtual
Reality
O¨zgu¨r Gu¨rerk and Andrea Bo¨nsch and Lucas Braun and
Christian Grund and Christine Harbring and Thomas
Kittsteiner and Andreas Staffeldt
RWTH Aachen University
December 2014
Online at http://mpra.ub.uni-muenchen.de/62073/
MPRA Paper No. 62073, posted 13. February 2015 20:53 UTC
Experimental Economics in Virtual Reality 1
Experimental Economics in Virtual Reality
Oculus and Co. will establish a new experimental method in economic research
Özgür Gürerk1,*, Andrea Bönsch2, Lucas Braun1, Christian Grund1, Christine Harbring1, Thomas
Kittsteiner1, and Andreas Staffeldt1
1: School of Business and Economics, RWTH Aachen University
2: Virtual Reality Group, RWTH Aachen University
December 2014
*: Corresponding author: Özgür Gürerk, Professor of Experimental Economics, RWTH Aachen University,
Templergraben 64, 52062 Aachen, Germany, ozgur.gurerk@rwth-aachen.de, www.expecon.de.
Recent developments in virtual reality (VR) technology have the potential to revolutionize the way
economists do experimental research. With Oculus’ light and affordable head mounted display
(HMD) human subjects can literally move and use objects in virtual spaces and interact with others.
This technology as well as surround-screen projection systems like CAVEs (Cruz-Neira et al. 1994),
allow the experimenter to observe economically relevant behavior and social interaction in a highly
immersive and at the same time tightly controlled virtual environment.
Previous applications of VR in (experimental) economics were mainly limited to research in low
immersive virtual worlds, e.g. Second Life (see e.g., Chesney et al. 2009, Füllbrunn et al. 2011), where
immersion, i.e., the feeling of “being there”, is perceived only indirectly through mouse-controlled
avatars, i.e., virtual representations of human subjects. While virtual worlds have some remarkable
research potential (Bainbridge 2007), they also have very important drawbacks for experimental
research, e.g., the loss of control over subjects’ characteristics (Duffy 2011). This led economists only
recently to begin utilizing controlled virtual world experiments (Twieg and McCabe 2014).
Blascovich et al. (2002) suggested the use of immersive virtual environments (IVEs) as a
methodological tool in (social) psychology. They, together with others, discovered that humans
indeed perceive highly IVEs as „real“. This phenomenon is referred to as presence (Sanchez-Vives et
al. 2005). Due to high costs, however, for a decade, social science research using VR was limited to
few labs and small sample sizes. Recently, affordable HMDs and other periphery devices accelerated
research in social sciences, such as social psychology to study social evaluation situations (Schmid et
al. 2013), in clinical psychology for treatment of social disorders (Falconer et al. 2014), or in linguistics
for understanding the role of gestures in human communication (Staum Casasanto et al. 2010).
More than other disciplines, economics focuses on the evaluation of counterfactual scenarios which
help to analyze strategic decisions and their efficiency effects. Counterfactuals, however, are not
easily observable, not even in field experiments. On the other hand, counterfactual scenarios in the
conventional lab settings are often perceived as “sterile environments” since they are not embedded
in a natural frame (Harrison and List 2004). Experiments in highly IVEs could fill a gap by enabling us
to test counterfactuals in an exactly controlled but more realistic setup. One could also test settings
that would be very costly or simply impossible to implement in the field, e.g., due to physical
restrictions or ethical reasons. In the next paragraphs, by means of three examples, we illustrate how
experiments in highly IVEs can add value to experimental economics and benefit economic research.
Experimental Economics in Virtual Reality 2
Naturalistic representation: Eliciting (risk) preferences
Preferences expressed and economic decisions taken by human subjects can depend on perceptions
of the external context and environment in which a decision problem is presented. A subject who
experiences “physical” presence in VR may automatically suppress that she is participating in an
experiment displaying a more “natural” behavior. Economists have used the passive observation of
3D modeled wildfires on monitors to evaluate subjects’ perception of risks, and driving simulators to
elicit risk preferences. By applying a low IVE to a context of evaluation choices, they combine “the
strengths of the artefactual controls of laboratory experiments with the naturalistic domain of field
experiments or direct field studies” (Fiore et al. 2013). These advantages are very likely to be more
pronounced in highly IVEs.
Tracking & realistic interactive tasks: Breaking the limits of real effort experiments in the lab
VR labs allow subjects to perform more natural tasks than in traditional labs where this is confined to
a 2D computer screen. Furthermore, tracking in VR enables measuring a subject’s position,
orientation, and movements in space. In a current study conducted in the CAVE of the RWTH Aachen
University, we capture exact measures of subject’s effort not in only one but in several dimensions
(Gürerk et al. 2014). In our setup, the subject is inside a virtual production hall. There, she physically
works at a virtual conveyor belt sorting out virtual cubes with a defect. To check for defects, the
subject can literally grasp and rotate the cubes. We are able to measure performance
multidimensionally by taking the number of not rejected cubes with various types of defects, the
number of rejected cubes without defects, the number of grasps and the duration of grasps into
account. We can evaluate how subjects make the trade-off between quantity and quality as a
function of the economic incentives provided. Other dimensions of tracking such as precision of
grasps, body movement and eye tracking can also be included.
Panel a: aixCAVE Panel b: HMD
Figure 1: Panel a: Subject interacting with a virtual cube in the aixCAVE of the RWTH Aachen University.
Panel b: Person with HMD grasping a virtual object.
Experimental Economics in Virtual Reality 3
The magic of co-presence: Solving the reflection puzzle through human-avatar interaction
Using avatars in social interactions creates the opportunity to analyze causal relationships between
simultaneously observed individuals’ (or groups’) behavior, which in traditional experiments is
severely hampered due to the well-known reflection problem (Manski 1995). In the setup explained
above, we could introduce a computer-controlled avatar who works at a parallel conveyor belt and is
observable by the human subject. The avatar exhibits different working behavior from slow to fast or
precise to careless, respectively. Since the avatar is not influenced by the human subject, we can rule
out the identification problem enabling us to observe non-confounded peer effects of the avatars’
work speed and work care on the human subject’s performance. As a further related idea, physically
or behaviorally pre-programmed avatars may help overcome cultural barriers when conducting
experiments with participants coming from different parts of the world.
Challenges
The main challenge in conducting experimental research within IVEs is the trade-off between costs
and internal as well as external validity. Using more costly VR systems like a CAVE instead of a low-
cost HMD usually increases the immersion, as subjects can perceive their complete (physical) body,
especially their interacting hands. Furthermore, an avatar's realistic visualization and movements
crucially affect its acceptance by the subjects. Modeling natural interaction patterns of avatars used
to be a fundamental technological issue, but recent developments in optical tracking technology
brought improvements with affordable prices.
Conclusion
Currently, experts as Jaron Lanier or entrepreneurs as Mark Zuckerberg expect a great future for VR
in entertainment as well as in transforming human communication and collaboration in shared
virtual spaces, e.g., virtual shopping or doctor visits. We believe the new possibilities have also great
potential to take experimenting in economics to the next level, by enabling us to elicit preferences
more reliably, by leading to a better understanding of the relation between incentives and effort, and
by the investigation of economic (and social) interactions in a way never possible before.
References
Bainbridge, W. S. 2007. The scientific research potential of virtual worlds. Science 317, 472–476.
Blascovich, J., Loomis, J., Beall, A.C., Swinth, K.R., Hoyt, C.L., and Bailenson, J.N. 2002. Immersive Virtual
Environment Technology as a Methodological Tool for Social Psychology. Psychol. Inq. 13, 103–124.
Cruz-Neira, C., Sandin, D. J. & DeFanti, T. A. 1993. Surround-screen projection-based virtual reality: the design
and implementation of the CAVE. Proceedings of the ACM SIGGRAPH ’93 Conference on Computer Graphics,
135–142.
Chesney, T., Chuah, S.-H., & Hoffmann, R. 2009. Virtual world experimentation: An exploratory study. Journal
of Economic Behavior & Organization, 72(1), 618–635.
Duffy, John. Trust in Second Life. 2011. Southern Economic Journal 78, 53-62.
Falconer CJ, Slater M, Rovira A, King JA, Gilbert P, et al. 2014. Embodying Compassion: A Virtual Reality
Paradigm for Overcoming Excessive Self-Criticism. PLoS ONE 9(11): e111933.
Fiore, S. M., Harrison, G. W., Hughes, C. E. & Rutström, E. E. 2009. Virtual experiments and environmental
policy - Frontiers of Environmental and Resource Economics. J. Environ. Econ. Manage. 57: 65–86.
Experimental Economics in Virtual Reality 4
Füllbrunn, S., Richwien, K. & Sadrieh, A. 2011. Trust and Trustworthiness in Anonymous Virtual Worlds. J.
Media Econ. 24, 48–63.
Gürerk, Ö., Grund, C., Harbring, C., Kittsteiner, T., Staffeldt., A., 2014. Real Effort on the Holodeck: Experimental
Economics in Virtual Reality. http://ssrn.com/abstract=2544739.
Harrison, G. W. & List, J. A. 2004. Field Experiments. J. Econ. Lit. 42, 1009–1055.
Manski, C. F. Identification of Endogenous Social Effects: The Reflection Problem. 1993. Rev. Econ. Stud. 60,
531–542.
Sanchez-Vives, M. V. & Slater, M. 2005. From presence to consciousness through virtual reality. Nat. Rev.
Neurosci. 6, 332–339.
Schmid, P. C. & Schmid Mast, M. 2013. Power increases performance in a social evaluation situation as a result
of decreased stress responses. Eur. J. Soc. Psychol. 43, 201–211.
Staum Casasanto, L., Jasmin, K., & Casasanto, D. 2010. Virtually accommodating: Speech rate accommodation
to a virtual interlocutor. In S. Ohlsson, & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of
the Cognitive Science Society, pp. 127-132. Austin, TX: Cognitive Science Society.
Twieg, P. B. and McCabe, K. A. 2014. The Determinants of Territorial Property Rights in a Spatial Commons
Experiment. SSRN: http://ssrn.com/abstract=2503260.
Appendix
Project Profiles
Experimental Economics in VR, School of Business and Economics, RWTH Aachen University
Experimental Economics in VR is one of the key projects of the “Business & Behavioral Metrics Lab”
of the “Interdisciplinary Management Factory” at the School of Business and Economics. The
Business & Behavioral Metrics Lab, founded in 2012, aims at the development of a series of
techniques for a radically new concept in experimental economic research. The idea is to analyze and
quantify individual behavior in organizations and markets that is supported with new technological
measuring methods, e.g., virtual reality experiments, under controlled laboratory conditions.
Different work environments in organizations will be replicated as realistically as possible through
collaboration with other disciplines and their technical expertise. More information about the project
“Experimental Economics in VR”: http://www.expecon.rwth-aachen.de/go/id/ffma/
Virtual Reality Group, IT Center, RWTH Aachen University
Since its inception in 1998, the VR Group has focused on two aspects: to conduct application-
oriented research in and provide access to methodology from the fields of virtual reality, human
computer interaction, and immersive visualization. The VR Group operates one the largest VR labs in
the world. Equipment and facilities range from small, desktop-scale systems to the large facilities
such as the aixCAVE, a 30 sqm visualization chamber which makes it possible to interactively explore
virtual environments. More information about the VR Group:
http://www.itc.rwth-aachen.de/cms/IT-Center/Forschung-Projekte/~eubl/Virtuelle-Realitaet/?lidx=1


Munich Personal RePEc ArchiveExperimental Economics in VirtualRealityGürerk, Özgür and Bönsch, Andrea and Braun, Lucas andGrund, Christian and Harbring, Christine and Kittsteiner,Thomas and Staffeldt, AndreasRWTH Aachen UniversityDecember 2014Online at https://mpra.ub.uni-muenchen.de/66617/MPRA Paper No. 66617, posted 14 Sep 2015 19:21 UTCExperimental Economics in Virtual Reality 1Experimental Economics in Virtual RealityOculus and Co. will establish a new experimental method in economic researchÖzgür Gürerk1,*, Andrea Bönsch2, Lucas Braun1, Christian Grund1, Christine Harbring1,Thomas Kittsteiner1, & Andreas Staffeldt11: School of Business and Economics, RWTH Aachen University2: Virtual Reality Group, RWTH Aachen UniversityAbstract: Experimental economics uses controlled and incentivized lab and field experimentsto learn about economic behavior. By means of three examples, we illustrate how experimentsconducted in immersive virtual environments can benefit (experimental) economic research.*: Corresponding author: Özgür Gürerk, Professor of Experimental Economics, RWTHAachen University, Templergraben 64, 52062 Aachen, Germany, ozgur.gurerk@rwth-aachen.de, www.expecon.de.Recent developments in virtual reality (VR) technology have the potential to revolutionize theway economists do experimental research. With Oculus’ light and affordable head mounteddisplay (HMD) human subjects can literally move and use objects in virtual spaces andinteract with others. This technology as well as surround-screen projection systems likeCAVEs (Cruz-Neira et al., 1993), allow the experimenter to observe economically relevantbehavior and social interaction in a highly immersive and at the same time tightly controlledvirtual environment.Experimental Economics in Virtual Reality 2Previous applications of VR in (experimental) economics were mainly limited to research inlow immersive virtual worlds, e.g. Second Life (see e.g., Chesney et al., 2009; Füllbrunn etal., 2011), where immersion, i.e., the feeling of “being there”, is perceived only indirectlythrough mouse-controlled avatars, i.e., virtual representations of human subjects. Whilevirtual worlds have some remarkable research potential (Bainbridge, 2007), they also havevery important drawbacks for experimental research, e.g., the loss of control over subjects’characteristics (Duffy, 2011). This led economists only recently to begin utilizing controlledvirtual world experiments (Twieg & McCabe, 2014).Blascovich et al. (2002) suggested the use of immersive virtual environments (IVEs) as amethodological tool in (social) psychology. They, together with others, discovered thathumans indeed perceive highly IVEs as “real”. This phenomenon is referred to as presence(Slater et al., 1994). Due to high costs, however, for a decade, social science research usingVR was limited to few labs and small sample sizes. Recently, affordable HMDs and otherperiphery devices accelerated research in social sciences, such as social psychology to studysocial evaluation situations (Schmid et al., 2013), in clinical psychology for treatment ofsocial disorders (Falconer et al., 2014), or in linguistics for understanding the role of gesturesin human communication (Staum Casasanto et al., 2010).More than other disciplines, economics focuses on the evaluation of counterfactual scenarioswhich help to analyze strategic decisions and their efficiency effects. Counterfactuals,however, are not easily observable, not even in field experiments. On the other hand,counterfactual scenarios in the conventional lab settings are often perceived as “sterileenvironments” since they are not embedded in a natural frame (Harrison & List, 2004).Experiments in highly IVEs could fill a gap by enabling us to test counterfactuals in anexactly controlled but more realistic setup. One could also test settings that would be verycostly or simply impossible to implement in the field, e.g., due to physical restrictions orExperimental Economics in Virtual Reality 3ethical reasons. In the next paragraphs, by means of three examples, we illustrate howexperiments in highly IVEs can add value to experimental economics and benefit economicresearch.Naturalistic representation: Eliciting (risk) preferencesPreferences expressed and economic decisions taken by human subjects can depend onperceptions of the external context and environment in which a decision problem is presented.A subject who experiences “physical” presence in VR may automatically suppress that she isparticipating in an experiment displaying a more “natural” behavior. Economists have usedthe passive observation of 3D modeled wildfires on monitors to evaluate subjects’ perceptionof risks, and driving simulators to elicit risk preferences. By applying a low IVE to a contextof evaluation choices, they combine “the strengths of the artefactual controls of laboratoryexperiments with the naturalistic domain of field experiments or direct field studies” (Fiore etal., 2013). These advantages are very likely to be more pronounced in highly IVEs (cf.Cummings & Bailenson, 2015).Tracking & realistic interactive tasks: Breaking the limits of real effort experiments inthe labVR labs allow subjects to perform more natural tasks than in traditional labs where this isconfined to a 2D computer screen. Furthermore, tracking in VR enables measuring a subject’sposition, orientation, and movements in space. In a current study conducted in the CAVE ofthe RWTH Aachen University, we capture exact measures of subject’s effort not in only onebut in several dimensions (Gürerk et al., 2014). In our setup, the subject is inside a virtualproduction hall. There, she physically works at a virtual conveyor belt sorting out virtualcubes with a defect. To check for defects, the subject can literally grasp and rotate the cubes.We are able to measure performance multidimensionally by taking the number of not rejectedExperimental Economics in Virtual Reality 4cubes with various types of defects, the number of rejected cubes without defects, the numberof grasps and the duration of grasps into account. We can evaluate how subjects make thetrade-off between quantity and quality as a function of the economic incentives provided.Other dimensions of tracking such as precision of grasps, body movement and eye trackingcan also be included.Panel a: aixCAVE Panel b: HMDFigure 1: Panel a: Subject interacting with a virtual cube in the aixCAVE of the RWTHAachen University. Panel b: Person with HMD grasping a virtual object.The magic of co-presence: Solving the reflection puzzle through human-avatarinteractionUsing virtual humans in social interactions (Schroeder, 2011) creates the opportunity toanalyze causal relationships between simultaneously observed individuals’ (or groups’)behavior, which in traditional experiments is severely hampered due to the well-knownreflection problem (Manski, 1993). In the setup explained in the section before, we introducea virtual co-worker, i.e., a computer-controlled avatar who works at a parallel conveyor beltExperimental Economics in Virtual Reality 5and is observable by the human subject (Gürerk et al., 2015). The virtual co-worker exhibitsdifferent working behavior from slow to fast or precise to careless, respectively. Since thehuman subject cannot influence the virtual co-worker, we can rule out the identificationproblem. This enables us to observe non-confounded peer effects of the avatars’ work speedand work care on the human subject’s performance. As a further related idea, physically orbehaviorally pre-programmed avatars may help overcome cultural barriers when conductingexperiments with participants coming from different parts of the world.Figure 2: Subject working in the aixCAVE of the RWTH Aachen University in thepresence of a virtual co-worker.ChallengesThe main challenge in conducting experimental research within IVEs is the trade-off betweencosts and internal as well as external validity. Using more costly VR systems like a CAVEinstead of a low-cost HMD usually increases the immersion, as subjects can perceive theircomplete (physical) body, especially their interacting hands. Furthermore, an avatar's realisticExperimental Economics in Virtual Reality 6visualization and movements crucially affect its acceptance by the subjects. Modeling naturalinteraction patterns of avatars used to be a fundamental technological issue, but recentdevelopments in optical tracking technology brought improvements with affordable prices.ConclusionCurrently, experts as Jaron Lanier or entrepreneurs as Mark Zuckerberg expect a great futurefor VR in entertainment as well as in transforming human communication and collaborationin shared virtual spaces, e.g., virtual shopping or doctor visits. We believe the newpossibilities have also great potential to take experimenting in economics to the next level, byenabling us to elicit preferences more reliably, by leading to a better understanding of therelation between incentives and effort, and by the investigation of economic (and social)interactions in a way never possible before.ReferencesBainbridge, W. S. (2007). The scientific research potential of virtual worlds. Science 317,472–476.Blascovich, J., Loomis, J., Beall, A.C., Swinth, K.R., Hoyt, C.L., and Bailenson, J.N. (2002).Immersive Virtual Environment Technology as a Methodological Tool for Social Psychology.Psychol. Inq. 13, 103–124.Chesney, T., Chuah, S.-H., & Hoffmann, R. (2009). Virtual world experimentation: Anexploratory study. Journal of Economic Behavior & Organization, 72(1), 618–635.Cruz-Neira, C., Sandin, D. J. & DeFanti, T. A. (1993). Surround-screen projection-basedvirtual reality: the design and implementation of the CAVE. Proceedings of the ACMSIGGRAPH ’93 Conference on Computer Graphics, 135–142.Experimental Economics in Virtual Reality 7Cummings, J. J., & Bailenson, J. N. (2015). How Immersive Is Enough? A Meta-Analysis ofthe Effect of Immersive Technology on User Presence. Media Psychology, 0(0), 1–38.Duffy, John. Trust in Second Life. (2011). Southern Economic Journal 78, 53-62.Falconer CJ, Slater M, Rovira A, King JA, Gilbert P, et al. (2014). Embodying Compassion:A Virtual Reality Paradigm for Overcoming Excessive Self-Criticism. PLoS ONE 9(11):e111933.Fiore, S. M., Harrison, G. W., Hughes, C. E. & Rutström, E. E. (2009). Virtual experimentsand environmental policy - Frontiers of Environmental and Resource Economics. J. Environ.Econ. Manage. 57: 65–86.Füllbrunn, S., Richwien, K. & Sadrieh, A. (2011). Trust and Trustworthiness in AnonymousVirtual Worlds. J. Media Econ. 24, 48–63.Gürerk, Ö., Grund, C., Harbring, C., Kittsteiner, T., & Staffeldt., A., (2014). Real Effort onthe Holodeck: Experimental Economics in Virtual Reality. http://ssrn.com/abstract=2544739.Gürerk, Ö., Kittsteiner, T., Bönsch, A., & Staffeldt., A., (2015). Avatars at Work: Do PeerEffects Really Exist? RWTH Aachen University.Harrison, G. W. & List, J. A. (2004). Field Experiments. J. Econ. Lit. 42, 1009–1055.Manski, C. F. Identification of Endogenous Social Effects: The Reflection Problem. (1993).Rev. Econ. Stud. 60, 531–542.Slater, M., Usoh, M., & Steed, A. (1994). Depth of presence in virtual environments.Presence, 3(2), 130–144.Schroeder, R. (2011). Being There Together: Social interaction in shared virtualenvironments. Oxford University Press.Experimental Economics in Virtual Reality 8Schmid, P. C. & Schmid Mast, M. (2013). Power increases performance in a social evaluationsituation as a result of decreased stress responses. Eur. J. Soc. Psychol. 43, 201–211.Staum Casasanto, L., Jasmin, K., & Casasanto, D. (2010). Virtually accommodating: Speechrate accommodation to a virtual interlocutor. In S. Ohlsson, & R. Catrambone (Eds.),Proceedings of the 32nd Annual Conference of the Cognitive Science Society, pp. 127-132.Austin, TX: Cognitive Science Society.Twieg, P. B. and McCabe, K. A. (2014). The Determinants of Territorial Property Rights in aSpatial Commons Experiment. SSRN: http://ssrn.com/abstract=2503260.AppendixProject ProfilesExperimental Economics in VR, School of Business and Economics, RWTH AachenUniversityExperimental Economics in VR is one of the key projects of the “Business & BehavioralMetrics Lab” of the “Interdisciplinary Management Factory” at the School of Business andEconomics. The Business & Behavioral Metrics Lab, founded in 2012, aims at thedevelopment of a series of techniques for a radically new concept in experimental economicresearch. The idea is to analyze and quantify individual behavior in organizations and marketsthat is supported with new technological measuring methods, e.g., virtual reality experiments,under controlled laboratory conditions. Different work environments in organizations will bereplicated as realistically as possible through collaboration with other disciplines and theirtechnical expertise. More information about the project “Experimental Economics in VR”:http://www.expecon.rwth-aachen.de/go/id/ffma/Experimental Economics in Virtual Reality 9Virtual Reality Group, IT Center, RWTH Aachen UniversitySince its inception in 1998, the VR Group has focused on two aspects: to conduct application-oriented research in and provide access to methodology from the fields of virtual reality,human computer interaction, and immersive visualization. The VR Group operates one thelargest VR labs in the world. Equipment and facilities range from small, desktop-scalesystems to the large facilities such as the aixCAVE, a 30 sqm visualization chamber whichmakes it possible to interactively explore virtual environments. More information about theVR Group:http://www.itc.rwth-aachen.de/cms/IT-Center/Forschung-Projekte/~eubl/Virtuelle-Realitaet/?lidx=1

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