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Information Propagation Model in Consumer Decision-Making
Corresponding Author(s) : Tao Yin
Asian Journal of Chemistry,
Vol. 26 No. 11 (2014): Vol 26 Issue 11
Abstract
Since different kinds of consumers have different characteristics in the information propagation, the entire consumer populations can be divided into four classes. And based on those characteristics, with analyzing interactions among those various classes of consumers, we build a decision-making information propagation model (CPUN). Though exploring its system dynamics characteristics, we get the existence conditions of the equilibrium points of the model and the spread threshold. We analyze and find that it plays an important role in increasing user density under the equilibrium state of consumer information propagation system that we increase the proportion of consumers’ second buying and the proportion of consumers who turn from potential consumers.
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- I.N. Athanasiadis and P.A. Mitkas, Comput. Sci. Eng., 7, 65 (2005); doi:10.1109/MCSE.2005.21.
- D.C. Plez and F.M. Andrews, Scientists in Organizations: Productive Climates for Research and Development, John Wiley & Sons, New York (1996).
- K. Xue and X. Chen, J. Quarterly, 106, 87 (2010).
- J. Zhu, Journalism & Commun., 6, 34 (2010).
- A. Sudbury, Appl. Prob., 22, 443 (1985); doi:10.2307/3213787.
- D.H. Zanette, Phys. Rev. E Stat. Nonlin. Soft Matter Phys., 64, 050901 (2001); doi:10.1103/PhysRevE.64.050901.
- Y. Moreno, M. Nekovee and A.F. Pacheco, Phys. Rev. E, 69, 066130 (2004); doi:10.1103/PhysRevE.69.066130.
- T. Zhou, B.H. Wang, X.P. Han and M.S. Shang, Eng., 25, 742 (2010).
- X.G. Gong and R.R. Wang, J. System Simulation, 20, 6511 (2008).
- C.Y. Liu, X.F. Hu, G.Y. Si and P. Luo, J. System Simulation, 18, 3608 (2006); doi:10.3969/j.issn.1004-731X.2006.12.070.
- L. Li, J.H. Sun and Z.J. Zhou, Syst. Eng., 27, 1 (2009).
- Y. Bai and J.L. Liu, Stat. Decis., 16, 31 (2009).
- T.Y. Yu, R.B. Xiao and X.G. Gong, Eng.-Theory Pract., 30, 919 (2010).
- T. Zhou, Z.Q. Fu, Y.W. Niu, D. Wang, Y. Zeng, B.H. Wang and P.L. Zhou, Prog. Nat. Sci., 15, 513 (2005); doi:10.3321/j.issn:1002-008X.2005.05.001.
References
I.N. Athanasiadis and P.A. Mitkas, Comput. Sci. Eng., 7, 65 (2005); doi:10.1109/MCSE.2005.21.
D.C. Plez and F.M. Andrews, Scientists in Organizations: Productive Climates for Research and Development, John Wiley & Sons, New York (1996).
K. Xue and X. Chen, J. Quarterly, 106, 87 (2010).
J. Zhu, Journalism & Commun., 6, 34 (2010).
A. Sudbury, Appl. Prob., 22, 443 (1985); doi:10.2307/3213787.
D.H. Zanette, Phys. Rev. E Stat. Nonlin. Soft Matter Phys., 64, 050901 (2001); doi:10.1103/PhysRevE.64.050901.
Y. Moreno, M. Nekovee and A.F. Pacheco, Phys. Rev. E, 69, 066130 (2004); doi:10.1103/PhysRevE.69.066130.
T. Zhou, B.H. Wang, X.P. Han and M.S. Shang, Eng., 25, 742 (2010).
X.G. Gong and R.R. Wang, J. System Simulation, 20, 6511 (2008).
C.Y. Liu, X.F. Hu, G.Y. Si and P. Luo, J. System Simulation, 18, 3608 (2006); doi:10.3969/j.issn.1004-731X.2006.12.070.
L. Li, J.H. Sun and Z.J. Zhou, Syst. Eng., 27, 1 (2009).
Y. Bai and J.L. Liu, Stat. Decis., 16, 31 (2009).
T.Y. Yu, R.B. Xiao and X.G. Gong, Eng.-Theory Pract., 30, 919 (2010).
T. Zhou, Z.Q. Fu, Y.W. Niu, D. Wang, Y. Zeng, B.H. Wang and P.L. Zhou, Prog. Nat. Sci., 15, 513 (2005); doi:10.3321/j.issn:1002-008X.2005.05.001.