Yuan Lin, Sumit Roy, and I have authored a paper that examines the use of network entropy and mutual information to measure the agility of networked organizational structures. The paper will appear in Applied Mathematics and Computation.
While the agility of networked organizational structures is important for organizational performance, studies on how to evaluate it remain scant, probably because the difficulty in measuring network evolution. In this conceptual paper, we propose two measures – network entropy and mutual information – to characterize the agility of networked organizational structure. Rooted in graph theory and information theory, these two measures capture network evolution in a comprehensive and parsimonious way. They indicate the uncertainty (or disorder) at the network level as well as the degree distribution at the individual level. We also propose an algorithm for applying them in the scenario of adding links to a network while holding the number of nodes fixed. Both simulated and real networks are used for demonstration. Implications and areas for future research are discussed in the end.
Lin, Y., Desouza, K.C., and Roy, S. “Measuring Agility of Networked Organizational structures via Network Entropy and Mutual Information,” Applied Mathematics and Computation, Forthcoming.