Community by design: Prioritizing the factors that drive knowledge use in online question & answers platforms

The question of how knowledge assets are utilized in the context of online communities is the primary impetus of this research. Using a multilevel approach, this paper investigates factors that influence the use of knowledge in an online question and answer platform (OQA). It focuses on three levels including informational, individual, and community, and reviews interactions across each level. The study tests the multilevel model with data from StackOverflow.com, a renowned online community for programmers to exchange knowledge assets, especially questions and answers about coding issues. Traditional hierarchical regression analysis proved insufficient to explicate the complexity associated with human decision-making processes with respect to asset utilization. However, a machine learning technique with a Chi-square automatic interaction detection algorithm provided a richer understanding of the relative importance of factors and their thresholds for influencing knowledge asset use.