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Call Me if You Can – An Experimental Investigation of Information Sharing in Knowledge Networks

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  • Helbach, Christoph
  • Keldenich, Klemens
  • Rothgang, Michael
  • Yang, Guanzhong

Abstract

In the public promotion of R&D cluster and network formation, the following situation typically arises: An initial network structure has developed over a long time span and policy measures affect the structure of links between the actors. This new network structure influences the effectiveness of the information flow in a way that is not clear from the beginning. As analyzing the effects of a change in the network structure is difficult in the field, this paper uses a laboratory experiment to analyze how information is distributed in four different network structures. Networks are modeled as five-actor groups. Every individual represents a node and possesses some private information. The experimental results suggest that the different network structures do indeed influence the way information is exchanged. Both too many possible links (causing a coordination problem) and too few possible links (introducing bottlenecks) are harmful. The participants in all network structures learn over time and achieve a faster exchange of information in the later rounds. These results suggest that when influencing communication structures, one has to be careful to balance the positive and negative effects of adding more communication possibilities.

Suggested Citation

  • Helbach, Christoph & Keldenich, Klemens & Rothgang, Michael & Yang, Guanzhong, 2012. "Call Me if You Can – An Experimental Investigation of Information Sharing in Knowledge Networks," Ruhr Economic Papers 332, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
  • Handle: RePEc:zbw:rwirep:332
    DOI: 10.4419/86788381
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    More about this item

    Keywords

    Network; communication; laboratory experiment; information flow;
    All these keywords.

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D70 - Microeconomics - - Analysis of Collective Decision-Making - - - General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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