Conventions, Information Asymmetry, and Intergenerational Information Flow: Theory and Experiment in Liberia

Author(s):  
Jimmy Lee
1995 ◽  
Vol 42-43 ◽  
pp. 277-286 ◽  
Author(s):  
G. Ananthakrishna ◽  
S.J. Noronha

2013 ◽  
Vol 50 (5) ◽  
pp. 627-643 ◽  
Author(s):  
Danny T. Wang ◽  
Flora F. Gu ◽  
Maggie Chuoyan Dong

In a distribution network, a punishment event not only affects the disciplined distributor but also changes the attitudes and behaviors of others in the network (i.e., observers). By moving beyond a dyadic view of punishment, this article considers the effects of punishment on observers and integrates insights from social learning, fairness heuristic, and social network theories. The resulting framework of the observer effects of punishment in a distribution network, empirically tested with a survey in China, reveals two mechanisms through which punishment leads to reduced observer opportunism: (1) a direct deterrence effect and (2) a trust-building process. Moreover, two information-related constructs moderate the observer effects differently. The disciplined distributor's relational embeddedness, which motivates greater information flow to observers, aggravates the problem of information asymmetry against the manufacturer, making punishment less deterrent for observers. In contrast, the manufacturer's monitoring capability, which reduces information asymmetry, strengthens observer effects. The authors discuss both theoretical and managerial implications of using punishment to achieve collaboration from a wide network of channel members.


Entropy ◽  
2013 ◽  
Vol 15 (1) ◽  
pp. 327-360 ◽  
Author(s):  
X. Liang
Keyword(s):  

1970 ◽  
Vol 32 (2) ◽  
pp. 322-338 ◽  
Author(s):  
John M. Orbell

2012 ◽  
Vol 26 (31) ◽  
pp. 1250183
Author(s):  
CHEN-XI SHAO ◽  
HUI-LING DOU ◽  
BING-HONG WANG

The concept of information asymmetry in complex networks is introduced on the basis of information asymmetry in economics and symmetry breaking. Information flowing between two nodes on a link is bidirectional, whose size is closely related to traffic dynamics on the network. Based on asymmetric information theory, we proposed information flow between network nodes is asymmetrical. We designed two methods to calculate the amount of information flow based on two mechanisms of complex network. Unequal flow of two opposite directions on the same link proved information asymmetry exists in the complex network. A complex network evolution model based on symmetry breaking is established, which is a truthful example for complex network mimicking nature. The evolution mechanism of symmetry breaking can best explain the phenomenon of the weak link and long tail theory in complex network.


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