An Information Foraging Model of Knowledge Creation and Spillover Dynamics in Open Source Science

Abstract

Motivation and problem-domain preferences of scientists can affect aggregate level emergence and growth of problem domains in science. An agent-based model based on information foraging and expectancy theory is introduced to examine the impact of rationality and openness on the growth and evolution of scientific domains. To promote reproducibility of the simulation, a standard documentation protocol is used to specify the conceptual model. In the presented virtual socio-technical model, scientists with different preferences search for problem domains to contribute knowledge, while considering their motivational gains. Problem domains become mature and knowledge spills occur over time to facilitate creation of new problem domains. Experiments are conducted to demonstrate emergence and growth of clusters of domains based on local interactions and preferences of scientists. Based on findings, potential avenues of future research are delineated.