EMERGENT SOCIAL LEARNING NETWORKS IN ORGANIZATIONS WITH HETEROGENEOUS AGENTS
Myong-Hun Chang ()
Additional contact information
Myong-Hun Chang: Department of Economics, Cleveland State University, Cleveland, OH 44140, USA
Advances in Complex Systems (ACS), 2011, vol. 14, issue 02, 169-199
Abstract:
Two distinct learning mechanisms are considered for a population of agents who engage in decentralized search for the common optimum. An agent may choose to learn via innovation (individual learning) or via imitation (social learning). The agents are endowed with heterogeneous skills in engaging in the two modes of learning. When the agents choose imitation, they also choose whom to learn from. This leads to theemergenceof a social learning network among agents in the population. This paper focuses on the impact the endowed learning skills have on the individual's choice of learning mechanism as well as the micro and macro structure of the evolving network. Finally, it explores the impact the degree of environmental volatility has on the structure of such networks.
Keywords: Social learning networks; innovation; imitation; organizational learning; heterogeneous agents (search for similar items in EconPapers)
Date: 2011
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0219525911002925
Access to full text is restricted to subscribers
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:wsi:acsxxx:v:14:y:2011:i:02:n:s0219525911002925
Ordering information: This journal article can be ordered from
DOI: 10.1142/S0219525911002925
Access Statistics for this article
Advances in Complex Systems (ACS) is currently edited by Frank Schweitzer
More articles in Advances in Complex Systems (ACS) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().