›› 2014, Vol. 23 ›› Issue (7): 70206-070206.doi: 10.1088/1674-1056/23/7/070206

• GENERAL • 上一篇    下一篇

Co-evolution of the brand effect and competitiveness in evolving networks

郭进利   

  1. Business School, University of Shanghai for Science and Technology, Shanghai 200093, China
  • 收稿日期:2013-12-05 修回日期:2014-01-01 出版日期:2014-07-15 发布日期:2014-07-15
  • 基金资助:
    Project supported by the National Natural Science Foundation of China (Grant Nos. 70871082 and 71301104) and the Shanghai First-class Academic Discipline Project, China (Grant No. S1201YLXK).

Co-evolution of the brand effect and competitiveness in evolving networks

Guo Jin-Li (郭进利)   

  1. Business School, University of Shanghai for Science and Technology, Shanghai 200093, China
  • Received:2013-12-05 Revised:2014-01-01 Online:2014-07-15 Published:2014-07-15
  • Contact: Guo Jin-Li E-mail:phd5816@163.com
  • About author:02.50.-r; 89.75.-k; 89.75.Hc; 89.65.-s
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant Nos. 70871082 and 71301104) and the Shanghai First-class Academic Discipline Project, China (Grant No. S1201YLXK).

摘要: The principle that ‘the brand effect is attractive’ underlies the preferential attachment. Here we show that the brand effect is just one dimension of attractiveness. Another dimension is competitiveness. We firstly introduce a general framework that allows us to investigate the competitive aspect of real networks, instead of simply preferring popular nodes. Our model accurately describes the evolution of social and technological networks. The phenomenon that more competitive nodes become richer can help us to understand the evolution of many competitive systems in nature and society. In general, the paper provides an explicit analytical expression of degree distributions of the network. In particular, the model yields a nontrivial time evolution of nodes' properties and the scale-free behavior with exponents depending on the microscopic parameters characterizing the competition rules. Secondly, through theoretical analyses and numerical simulations, we reveal that our model has not only the universality for the homogeneous weighted network, but also the character for the heterogeneous weighted network. Thirdly, we also develop a model based on the profit-driven mechanism. It can better describe the observed phenomenon in enterprise cooperation networks. We show that the standard preferential attachment, the growing random graph, the initial attractiveness model, the fitness model, and weighted networks can all be seen as degenerate cases of our model.

关键词: complex network, weighted network, scale-free network, competitive network

Abstract: The principle that ‘the brand effect is attractive’ underlies the preferential attachment. Here we show that the brand effect is just one dimension of attractiveness. Another dimension is competitiveness. We firstly introduce a general framework that allows us to investigate the competitive aspect of real networks, instead of simply preferring popular nodes. Our model accurately describes the evolution of social and technological networks. The phenomenon that more competitive nodes become richer can help us to understand the evolution of many competitive systems in nature and society. In general, the paper provides an explicit analytical expression of degree distributions of the network. In particular, the model yields a nontrivial time evolution of nodes' properties and the scale-free behavior with exponents depending on the microscopic parameters characterizing the competition rules. Secondly, through theoretical analyses and numerical simulations, we reveal that our model has not only the universality for the homogeneous weighted network, but also the character for the heterogeneous weighted network. Thirdly, we also develop a model based on the profit-driven mechanism. It can better describe the observed phenomenon in enterprise cooperation networks. We show that the standard preferential attachment, the growing random graph, the initial attractiveness model, the fitness model, and weighted networks can all be seen as degenerate cases of our model.

Key words: complex network, weighted network, scale-free network, competitive network

中图分类号:  (Probability theory, stochastic processes, and statistics)

  • 02.50.-r
89.75.-k (Complex systems) 89.75.Hc (Networks and genealogical trees) 89.65.-s (Social and economic systems)