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In This Article

  • Summary
  • Abstract
  • Introduction
  • Protocol
  • Representative Results
  • Discussion
  • Acknowledgements
  • Materials
  • References
  • Reprints and Permissions

Summary

The Collective Trust Game is a computer-based, multi-agent trust game based on the HoneyComb paradigm, which enables researchers to assess the emergence of collective trust and related constructs, such as fairness, reciprocity, or forward-signaling. The game allows detailed observations of group processes through movement behavior in the game.

Abstract

The need to understand trust in groups holistically has led to a surge in new approaches to measuring collective trust. However, this construct is often not fully captured in its emergent qualities by the available research methods. In this paper, the Collective Trust Game (CTG) is presented, a computer-based, multi-agent trust game based on the HoneyComb paradigm, which enables researchers to assess the emergence of collective trust. The CTG builds on previous research on interpersonal trust and adapts the widely known Trust Game to a group setting in the HoneyComb paradigm. Participants take on the role of either an investor or trustee; both roles can be played by groups. Initially, investors and trustees are endowed with a sum of money. Then, the investors need to decide how much, if any, of their endowment they want to send to the trustees. They communicate their tendencies as well as their final decision by moving back and forth on a playfield displaying possible investment amounts. At the end of their decision time, the amount the investors have agreed upon is multiplied and sent to the trustees. The trustees have to communicate how much of that investment, if any, they want to return to the investors. Again, they do so by moving on the playfield. This procedure is repeated for multiple rounds so that collective trust can emerge as a shared construct through repeated interactions. With this procedure, the CTG provides the opportunity to follow the emergence of collective trust in real time through the recording of movement data. The CTG is highly customizable to specific research questions and can be run as an online experiment with little, low cost equipment. This paper shows that the CTG combines the richness of group interaction data with the high internal validity and time-effectiveness of economic games.

Introduction

The Collective Trust Game (CTG) provides the opportunity to measure collective trust online within a group of humans. It generalizes the original Trust Game by Berg, Dickhaut, and McCabe1 (BDM) to the group level and can capture and quantify collective trust in its emergent qualities2,3,4, as well as related concepts such as fairness, reciprocity, or forward-signaling.

Previous research mostly conceptualizes trust as a solely interpersonal construct, for example, between a leader and a follower5,....

Protocol

Data collection and data analysis in this project have been approved by the Ethics Committee of the Georg-Elias-Müller Institute for Psychology of the University of Göttingen (proposal 289/2021); the protocol follows the guidelines on human research of the Ethics Committees of the Georg-Elias-Müller-Institute for Psychology. The CTG software can be downloaded from the OSF project (DOI 10.17605/OSF.IO/U24PX) under the link: https://s.gwdg.de/w88YNL.

1. Prepare technica.......

Representative Results

This paper presents results of a pilot study conducted with the CTG with 16 participants (five men, 11 women; Age: M = 21, SD = 2.07). According to Johanson and Brooks42, this sample size is sufficient in a pilot experiment, especially when paired with a qualitative approach to reach a high information density about participants' subjective experience during the experiment. It is recommended that whenever researchers intend to adapt the CTG to their specific research idea, fo.......

Discussion

The CTG provides researchers with the opportunity to adapt the classic BDM1 for groups and observe emergent processes within the groups in depth. While other work23,24,25,26 has already attempted to adapt the BDM1 to group settings, the only way to access group processes in these studies are laborious group interaction analyses of video-taped disc.......

Acknowledgements

This research did not receive any external funding.

....

Materials

NameCompanyCatalog NumberComments
Data Analysis Software and PackagesRversion 4.2.1 (2022-06-23 ucrt)R Core Team R: A Language and Environment for Statistical Computing. at [https://www.R-project.org/]. R Foundation for Statistical Computing. Vienna, Austria. (2020).
Data Analysis Software and PackagesR Studioversion 2022.2.3.492 "Prairie Trillium"RStudio Team RStudio: Integrated Development Environment for R. at [http://www.rstudio.com/]. RStudio, PBC. Boston, MA. (2020).
Data Analysis Software and Packagesggplot2version 3.3.6Wickham, H. ggplot2: Elegant Graphics for Data Analysis. at [https://ggplot2.tidyverse.org]. Springer-Verlag New York. (2016).
Data Analysis Software and Packagescowplotversion 1.1.1Wilke, C.O. cowplot: Streamlined Plot Theme and Plot Annotations for “ggplot2.” at [https://CRAN.R-project.org/package=cowplot]. (2020).
OnlineQuestionnaireToolLimeSurveyCommunity Edition Version 3.28.16+220621 Any preferred online questionnaire tool can be used. LimeSurvey or SoSciSurvey are recommended.
Notebooks or PCsDELLLatitude 7400Any laptop that is able to establish a stable Remote Desktop Connection can be used.
Participant Management SoftwareORSEEversion 3.1.0It is recommended to use ORSEE (Greiner, B. [2015]. Subject pool recruitment procedures: Organizing experiments with ORSEE. Journal of the Economic Science Association, 1, 114–125. https://doi.org/10.1007/s40881-015-0004-4), but other software options might be available.
Program to Open RemoteDesktop ConnectionRemote Desktop Connection (Program distributed with each Windows 10 installation.)The following tools are recommended: RemoteDesktopConnection (for Windows), Remmina (for Linux), or Microsoft Remote Desktop (for Mac OS).
Server to run RemoteDesktop EnvironmentVMware vSphere environment based on vSphere ESXiversion 6.5Ideally provided by IT department of university/institution.
VideoConference PlatformBigBlueButtonVersion 2.3It is recommend to use a platform such as BigBlueButton or other free software that does not record participant data on an external server. The platform should provide the following functions: 1) possibility to restrict access to microphone and camera for participants, 2) hide participant names from other participants, 3) possibility to send private chat message to participants.
Virtual Machine running Linux-InstallationXubuntuversion 20.04 "Focal Fossa"Other Linux-based systems will also be possible.

References

  1. Berg, J., Dickhaut, J., McCabe, K. Trust, reciprocity, and social history. Games and Economic Behavior. 10 (1), 122-142 (1995).
  2. Costa, A. C., Fulmer, C. A., Anderson, N. R. Trust in work teams: An integrative review, multilevel mo....

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