Bounded rationality, social learning and collective behavior: Decisional analysis in a nested world
Refereed conference paper presented and published in conference proceedings

Full Text

Times Cited

Other information
AbstractPeople are usually brought together in a social network to make synergetic decisions. This decision making process often involves information acquisition and social learning, which are essential to overcome individuals' bounded rationality. The performance of a society thus depends on the collective behavior of individuals. Besides information attributes, organizational properties often influenced such a decision process. In this article, we introduce a paradigm -- nested world -- that treats social network as a symbolic system. Based on this paradigm, we developed a research model to investigate how information attributes, social parameters, and their interactions influenced the performance of a social network. This research model was subsequently converted to a computational model for analysis and validation. Our findings suggested that informativeness, network density, social influence, and their interactions had significant influence on the performance of whole society. Besides these findigns, many interesting phenomenon were also observed, including significant social learning curve, U-shape decision speed, threshold of network density, and interchangeability between network density and social influence.
All Author(s) ListHu H., Lai V.S., Jia Y.
Name of Conference32nd International Conference on Information System 2011, ICIS 2011
Start Date of Conference04/12/2011
End Date of Conference07/12/2011
Place of ConferenceShanghai
Country/Region of ConferenceChina
Detailed descriptionorganized by Association for Information Systems,
Volume Number1
Pages680 - 696
LanguagesEnglish-United Kingdom
KeywordsBounded rationality, Decisional analysis, Social learning, Social network

Last updated on 2020-02-09 at 00:41