The Evolution of ICT Markets: An Agent-Based Model on Complex Networks

被引:0
|
作者
Zhao, Liangjie [1 ]
Wu, Bangtao [1 ]
Chen, Zhong [1 ]
Li, Li [1 ]
机构
[1] Shanghai Jiao Tong Univ, Antai Coll Econ & Management, Shanghai 200052, Peoples R China
来源
COMPLEX SCIENCES, PT 1 | 2009年 / 4卷
关键词
information and communication technology; evolution of market; diffusion of innovations; complex networks; network effects; TELECOMMUNICATION SERVICES; COMPATIBILITY; COMPETITION; STANDARDIZATION; INNOVATION; SUCCESS;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Information and communication technology (ICT) products exhibit positive network effects. The dynamic process of ICT markets evolution has two intrinsic characteristics: (1) customers are influenced by each others' purchasing decision; (2) customers are intelligent agents with bounded rationality. Guided by complex systems theory, we construct an agent-based model and simulate on complex networks to examine how the evolution can arise from the interaction of customers, which occur when they make expectations about the future installed base of a product by the fraction of neighbors who are using the same product in his personal network. We demonstrate that network effects play an important role in the evolution of markets share, which make even an inferior product can dominate the whole market. We also find that the intensity of customers' communication can influence whether the best initial strategy for firms is to improve product quality or expand their installed base.
引用
收藏
页码:569 / 579
页数:11
相关论文
共 50 条
  • [21] Empirical validation of an agent-based model of wood markets in Switzerland
    Holm, Stefan
    Hilty, Lorenz M.
    Lemm, Renato
    Thees, Oliver
    PLOS ONE, 2018, 13 (01):
  • [22] Agent-Based Microgrid Scheduling: An ICT Perspective
    Lezama, Fernando
    Palominos, Jorge
    Rodriguez-Gonzalez, Ansel Y.
    Farinelli, Alessandro
    Munoz de Cote, Enrique
    MOBILE NETWORKS & APPLICATIONS, 2019, 24 (05): : 1682 - 1698
  • [23] Agent-based models of financial markets
    Samanidou, E.
    Zschischang, E.
    Stauffer, D.
    Lux, T.
    REPORTS ON PROGRESS IN PHYSICS, 2007, 70 (03) : 409 - 450
  • [24] Agent-Based Microgrid Scheduling: An ICT Perspective
    Fernando Lezama
    Jorge Palominos
    Ansel Y. Rodríguez-González
    Alessandro Farinelli
    Enrique Munoz de Cote
    Mobile Networks and Applications, 2019, 24 : 1682 - 1698
  • [25] Agent-based modeling of lottery markets
    Chen, SH
    Chie, BT
    PROCEEDINGS OF THE 7TH JOINT CONFERENCE ON INFORMATION SCIENCES, 2003, : 1227 - 1230
  • [26] Agent-Based Social Simulation in Markets
    Bertels, Koen
    Boman, Magnus
    Electronic Commerce Research, 2001, 1 (1-2) : 149 - 158
  • [27] Agent-based modeling of efficient markets
    Lim, SW
    Wong, KYM
    Luo, P
    INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING, 2003, 2690 : 27 - 34
  • [28] Developing an agent-based simulation model of software evolution
    Ali, Shallaw Mohammed
    Doolan, Martina
    Wernick, Paul
    Wakelam, Ed
    INFORMATION AND SOFTWARE TECHNOLOGY, 2018, 96 : 126 - 140
  • [29] The learnable evolution model in agent-based delivery optimization
    Wojtusiak, Janusz
    Warden, Tobias
    Herzog, Otthein
    MEMETIC COMPUTING, 2012, 4 (03) : 165 - 181
  • [30] The learnable evolution model in agent-based delivery optimization
    Janusz Wojtusiak
    Tobias Warden
    Otthein Herzog
    Memetic Computing, 2012, 4 : 165 - 181