Google matrix of business process management
arXiv:1009.2631 · doi:10.1140/epjb/e2010-10710-y
Abstract
Development of efficient business process models and determination of their characteristic properties are subject of intense interdisciplinary research. Here, we consider a business process model as a directed graph. Its nodes correspond to the units identified by the modeler and the link direction indicates the causal dependencies between units. It is of primary interest to obtain the stationary flow on such a directed graph, which corresponds to the steady-state of a firm during the business process. Following the ideas developed recently for the World Wide Web, we construct the Google matrix for our business process model and analyze its spectral properties. The importance of nodes is characterized by Page-Rank and recently proposed CheiRank and 2DRank, respectively. The results show that this two-dimensional ranking gives a significant information about the influence and communication properties of business model units. We argue that the Google matrix method, described here, provides a new efficient tool helping companies to make their decisions on how to evolve in the exceedingly dynamic global market.
submitted to European Journal of Physics B
References in corpus (9)
- Diffusion of scientific credits and the ranking of scientists
- Spectral centrality measures in complex networks
- Two-dimensional ranking of Wikipedia articles
- Spectral properties of the Google matrix of the World Wide Web and other directed networks
- Delocalization transition for the Google matrix
- Google matrix, dynamical attractors and Ulam networks
- Google matrix and Ulam networks of intermittency maps
- Towards Google matrix of brain
- Fractal Weyl law for Linux Kernel Architecture