When human networks collide: the degree distributions of hyper-networks

Abstract

The study of service value networks adds a new dimension of investigation to industrial systems: human networks. Existing literature shows humans hyper-network to co-create value within and outside of the traditional structures of an organization or an extended enterprise—such as social networking for innovation and e-commerce for supply chain. Since human networks tend to be composite and multi-dimensional, they need new results to understand how networks collide during economic activities and what new coalesced networks will result. The hyper-network model uniquely describes this multi-layered evolving nature of human networks and reveals some of the basic networking properties either directly from the initial community base networks or directly from the colliding single networks. This article answers an important question about service value networks: What are the connection patterns of a network of networks, such as the distribution of the number of connections at a node—the degree distribution? We develop formulae to determine four prototypical classes of hyper-networks, which constitute a baseline analysis to the new study of network evolution for network science and service science.

Keywords:

• Hyper-networks
• network science
• social networks
• service science

Additional information

Notes on contributors

Wai Kin Victor Chan

Wai Kin (Victor) Chan is an Associate Professor in the Department of Industrial and Systems Engineering at the Rensselaer Polytechnic Institute, Troy, New York. He holds a Ph.D. in Industrial Engineering and Operations Research from University of California, Berkeley. His research interests include discrete-event simulation, agent-based simulation, and their applications in social networks, service systems, transportation networks, energy markets, and manufacturing. He is a member of INFORMS, IIE, and IEEE.

Cheng Hsu

Cheng Hsu received his B.S. in Industrial Engineering from Tunghai University, Taiwan, and M.S., in Industrial and Systems Engineering and Ph.D. in Management Sciences from the Ohio State University, Columbus. He is a Professor of Industrial and Systems Engineering at Rensselaer Polytechnic Institute, Troy, New York. His research and teaching cover the areas of data and knowledge systems, service science, and analytics for design and manufacturing, which has yielded over a hundred of refereed papers in IEEE Transactions; AIS, IE, SME, and INFORMS journals; and other publications. He has also authored six research monographs and one textbook and holds a U.S. patent on natural language database query.