Identification of communities is significant in understanding the structures and functions of networks. Since some nodes naturally belong to several communities, the study of overlapping communities has attracted increasing attention recently, and many algorithms have been designed to detect...

The paper discusses the new concept of ‘Multinational Investment Projects' (MIPs) and its application in the context of international business operations in China. The petrochemical industry in China is used as the industrial context in which we investigate the interplay between the Chinese...

Many complex systems can be investigated using the framework of temporal networks, which consist of nodes and edges that vary in time. The community structure in temporal network contributes to the understanding of evolving process of entities in complex system. The traditional method on dynamic...

Identifying influential nodes that lead to faster and wider spreading in complex networks is of theoretical and practical significance. The degree centrality method is very simple but of little relevance. Global metrics such as betweenness centrality and closeness centrality can better identify...

We develop a probabilistic consumer choice framework based on information asymmetry between consumers and firms. This framework makes it possible to study market competition of several firms by both quality and price of their products. We find Nash market equilibria and other optimal strategies...

Identifying influential spreaders is crucial for understanding and controlling spreading processes on social networks. Via assigning degree-dependent weights onto links associated with the ground node, we proposed a variant to a recent ranking algorithm named LeaderRank (Lü et al., 2011)....