Agent-based modeling for the study of diffusion dynamics

Diffusion is the process in which the successful introduction of new products and practices into society along with invention. Many studies of the diffusion of individual innovations exist, and exhibit some commonalities such as the famous S-shaped diffusion curve. New ideas, products, and innovation often take time to diffuse, a fact that is often attributed to some form of heterogeneity among people. Then a basic puzzle posed by innovation diffusion is why there is often a long lag between an innovation's first appearance and the time when a substantial number of people have adopted it. There is an extensive theoretical and empirical literature on this phenomenon and the mechanisms that might give rise to it. The diffusion process enhances an innovation via the feedback of information about its utility across different users that can be used to improve it. This aspect is similar to the micro-macro loop which is essential part of emergent dynamics.

[1]  D. North.  Competing Technologies , Increasing Returns , and Lock-In by Historical Events , 1994 .

[2]  D. Watts,et al.  Influentials, Networks, and Public Opinion Formation , 2007 .

[3]  Peter Convey,et al.  Adaptation and evolution , 2007 .

[4]  A. Banerjee,et al.  A Simple Model of Herd Behavior , 1992 .

[5]  Jason Brownlee,et al.  Complex adaptive systems , 2007 .

[6]  Glenn Ellison.  Learning, Local Interaction, and Coordination , 1993 .

[7]  Dunia López-Pintado,et al.  Contagion and coordination in random networks , 2006, Int. J. Game Theory.

[8]  Moshe Levy,et al.  Microscopic Simulation of Financial Markets: From Investor Behavior to Market Phenomena , 2000 .

[9]  Frank M. Bass,et al.  A New Product Growth for Model Consumer Durables , 2004, Manag. Sci..

[10]  Bhaskar Chakravorti.  The Slow Pace of Fast Change: Bringing Innovations to Market in a Connected World , 2003 .

[11]  Chrysanthos Dellarocas,et al.  The Digitization of Word-of-Mouth: Promise and Challenges of Online Feedback Mechanisms , 2003, Manag. Sci..

[12]  Leeat Yariv,et al.  Diffusion, Strategic Interaction, and Social Structure , 2011, Handbook of Social Economics.

[13]  Mark E. J. Newman,et al.  The Structure and Function of Complex Networks , 2003, SIAM Rev..

[14]  J. Kurths,et al.  Network synchronization, diffusion, and the paradox of heterogeneity. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[15]  Fang Wu,et al.  Management fads, pedagogies, and other soft technologies , 2009 .

[16]  David P. Myatt,et al.  Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning , 2009 .

[17]  H. Young,et al.  Innovation Diffusion in Heterogeneous Populations , 2006 .

[18]  E. Rogers,et al.  COMPLEX ADAPTIVE SYSTEMS AND THE DIFFUSION OF INNOVATIONS , 2005 .

[19]  Susan H. Xu,et al.  Technology diffusion by learning from neighbours , 2004, Advances in Applied Probability.

[20]  A. Barabasi,et al.  Scale-free characteristics of random networks: the topology of the world-wide web , 2000 .

[21]  Nicole Immorlica,et al.  The role of compatibility in the diffusion of technologies through social networks , 2007, EC '07.

[22]  K. Dessouky,et al.  Network synchronization , 1985, Proceedings of the IEEE.

[23]  Akira Namatame.  Adaptation and Evolution in Collective Systems , 2006, Advances in Natural Computation.

[24]  B. Huberman,et al.  Social Structure and Opinion Formation , 2004, cond-mat/0407252.

[25]  N. Rosenberg.  Factors affecting the diffusion of technology , 1972 .

[26]  Bronwyn H Hall,et al.  Innovation and Diffusion , 2004 .

[27]  Moshe Levy,et al.  Microscopic Simulation of Financial Markets , 2000 .