Experimental analysis of self-organizing team's behaviors

This paper is focused on the study of self-organizing team’s behaviors which are dependent on the interaction rules and the decision factors of team members. The self-organizing team’s behavior means that team members work unconditionally with one of the three work attitudes (diligence, average, and shirking). A small-world network is suggested as the basic relationships of team members. Different from the traditional models, Reciprocators encourage their friends if they work diligently and punish them if they shirk work. It is supposed that team member’s decision of choosing work attitude depends on four decision factors, humanity, herd instinct, rationality, and follower tendency. Firstly, all of the four decision factors’ weights are supposed as 0.25. Multiple experiments were conducted to analyze the behavior of a team by a multi-agent experiment system. It is found that, in order to increase the fraction of diligent team members, different strategies should be used under different Reciprocators’ fractions. Increasing Reciprocators’ fraction is beneficial to the increase of diligent members; however, the increase rate will slow down after an inflexion (here it means the inflexion of Reciprocators’ fraction). After the previous experiments study, extended experiments were developed to work on the influence of the four factors’ different weights. A self-adaptive algorithm is suggested to achieve the four decision factors’ weights. The results of self-adaptive algorithm have different influences on the team’s behaviors under different fractions of Reciprocators. Finally, influences of members’ different relationships are studied by other experiments. It is also proved that the fraction of diligent members is not dependent on the structure of team members’ relationships. The results demonstrate that the self-organizing team’s behavior can be significantly influenced by its scenario while managing a self-organizing team. 2009 Elsevier Ltd. All rights reserved.