Knowledge sharing in an organization

Managers are always seeking effective policies that encourage employees to share their knowledge with others in an organization. The appropriate organizational incentives are difficult to investigate due to human factors and other institutional complexities affecting sharing behaviors of individuals. Conducting laboratory or field experiments to evaluate the effectiveness of various organizational incentive policies is unrealistic. This work proposes a novel agent-based modeling approach to simulate the actions of knowledge sharing between actors in an organization. Several human and institutional factors in this artificial world were manipulated to understand knowledge sharing. The simulation results produce the following interesting findings. (1) The initial state of actors' action affects the knowledge-sharing action regardless of the adopted strategy. (2) Poorer collective capability among the population lowers the knowledge sharing behaviors. (3) The incentive policy has restricted effects for increasing the sharing action. Rewarding each knowledge-sharing action is more effective than the periodic organizational incentives to encourage actors' knowledge sharing behaviors.