An analytic approach to measure information aggregation and evaluate the stability of informational cascades under incomplete information settings

Informational cascades describe a situation in which people observe the actions of others and then make the same choice, regardless of their own information. Behavioral conformity prevents information aggregation (Bikhchandani et al., 1992). However, under incomplete information settings, individual’s information is a sample of the whole information pool as we are facing information more than we can handle in daily business routine. As we can rule out the possibility that predecessors get enough information to shatter a cascade if cascade continues, it is reasonable to consider there is information injected into cascade even when decision-maker follows predecessor’s behavior. Taking this belief into consideration, we analyze the threshold point of convergence /deviation, and propose a model to measure Information aggregation and evaluate the stability of informational cascades under incomplete information settings. This model helps to optimize sequential decision-making process by utilizing the statistical aspects of informational cascades.

[1]  Nicolas Melissas,et al.  Herd behaviour as an incentive scheme , 2005 .

[2]  R. Boyd,et al.  The evolution of conformist transmission and the emergence of between-group differences. , 1998 .

[3]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[4]  W. Edwards,et al.  Decision Analysis and Behavioral Research , 1986 .

[5]  S. Bikhchandani,et al.  You have printed the following article : A Theory of Fads , Fashion , Custom , and Cultural Change as Informational Cascades , 2007 .

[6]  S. Zamir,et al.  Formulation of Bayesian analysis for games with incomplete information , 1985 .

[7]  Bin Gu,et al.  Informational Cascades and Software Adoption on the Internet: An Empirical Investigation , 2008, MIS Q..

[8]  S. Bikhchandani,et al.  Learning from the behavior of others : conformity, fads, and informational cascades , 1998 .

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

[10]  Christian Pierdzioch,et al.  Housing Starts in Canada, Japan, and the United States: Do Forecasters Herd? , 2012 .

[11]  I. Welch,et al.  Rational herding in financial economics , 1996 .

[12]  Glenn J. Browne,et al.  Information Cascades in the Adoption of New Technology , 2002, ICIS.

[13]  E. Rogers.  Diffusion of Innovations , 1962 .

[14]  E. Rogers,et al.  Diffusion of Innovations, 5th Edition , 2003 .

[15]  J. Neumann,et al.  Theory of games and economic behavior , 1945, 100 Years of Math Milestones.

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

[17]  A. Mas-Colell,et al.  Microeconomic Theory , 1995 .

[18]  Ward Farnsworth.  The Legal Analyst: A Toolkit for Thinking about the Law , 2007 .

[19]  Dorothea Kübler,et al.  Information Cascades in the Labor Market , 2003 .

[20]  D. Hirshleifer,et al.  COOPERATION IN A REPEATED PRISONERS' DILEMMA WITH OSTRACISM , 1989 .