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Titel
An experimental study on the effects of communication, credibility, and clustering in network games / Gary Charness (University of California at Santa Barbara, IZA and CESifo Munich), Francesco Feri (Royal Holloway University of London and University of Trieste), Miguel A. Meléndez-Jiménez (Universidad de Málaga), Matthias Sutter (Max Planck Institute, University of Cologne, University of Innsbruck and IZA) ; IZA Institute of Labor Economics
VerfasserCharness, Gary ; Feri, Francesco ; Meléndez-Jiménez, Miguel A. ; Sutter, Matthias
KörperschaftForschungsinstitut zur Zukunft der Arbeit
ErschienenBonn, Germany : IZA Institute of Labor Economics, May 2019
Ausgabe
Elektronische Ressource
Umfang1 Online-Ressource (54 Seiten) : Diagramme
SerieDiscussion paper ; no. 12347
URNurn:nbn:de:hbz:5:2-190633 
Zugriffsbeschränkung
 Das Dokument ist öffentlich zugänglich im Rahmen des deutschen Urheberrechts.
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An experimental study on the effects of communication, credibility, and clustering in network games [0.74 mb]
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Zusammenfassung (Englisch)

The effectiveness of social interaction depends strongly on an ability to coordinate actions efficiently. In large networks, such coordination may be very difficult to achieve and may depend on the communication technology and the network structure. We examine how pre-play communication and clustering within networks affect coordination in a challenging experimental game on eight-person networks. Free-form chat is enormously effective in achieving the nonequilibrium efficient outcome in our game, but restricted communication (where subjects can only indicate their intended action) is almost entirely ineffective. We can rationalize this result with a novel model about the credibility of cheap-talk messages. This credibility is much larger with freeform message communication than with restricted communication. We are the first to model this credibility and show, both theoretically and experimentally, an interaction effect of network structure and communication technologies. We also provide a model of message diffusion, which indeed predicts that diffusion will be more rapid without clustering and is consistent with our data.