2020 Volume 30 Issue 1 Pages 37-44
This study applied the critical mass model to investigate the effects of individual attitudes toward a certain behavior on the ratio of its acceptance in a group or society. Individual attitudes were expressed with a “critical number” representing the difficulty of acceptance. Each of the individuals changed their behavior when the percentage of the other individuals who accepted the behavior was equal to or larger than the critical number. Individuals whose critical numbers were 0 accepted the behavior even if no other individuals accepted it. Those with critical numbers of above 100 did not accept even if all the others accepted the behavior. Most datasets were created by changing each individual’s critical number and the distribution of the critical numbers (uniform or normal distribution). This computer simulation involved two groups: global and local. The global knew behaviors of all involved, while the local only knew about the behaviors of neighbors. This study analyzed the differences between global and local conditions using cellular automata simulation. The results showed that the “local” condition tended to decrease behavior change in a society. In addition, this trend was stronger in the following settings: A) the ratio of individuals whose critical number was 0 was low or B) that of individuals whose critical number was above 100 was low. However, the local condition could increase the behavior change in the case of a normal distribution
