Identifying Cultural Factors Relevant to Human Behavior Modeling and Simulation

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$98,785.00
Award Year:
2005
Program:
SBIR
Phase:
Phase I
Contract:
FA8650-05-M-6585
Agency Tracking Number:
F051-069-1737
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
ANACAPA SCIENCES, INC.
301 East Carrillo Street 2FL, P. O. Box 519, Santa Barbara, CA, 93102
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
053859526
Principal Investigator:
Michael Silver
Senior Scientist
(805) 966-6157
msilver@anacapasciences.com
Business Contact:
Douglas Harris
Chairman
(805) 966-6157
dharris@anacapasciences.com
Research Institution:
n/a
Abstract
Current models used in military simulations generally do not include representations of human behavior that vary realistically between humans of different cultures. This lack of realism has the potential to result in tragic consequences for US military personnel and others through, for example, inappropriate planning or being inaccurately trained to anticipate an opponent's reaction to a particular military action. In Phase I we will gather data from existing studies (translated as necessary when conducted in other cultures) and perform several meta-analyses to quantitatively summarize the influence of cultural variables (e.g., individualism and collectivism) on other high-priority variables of interest to military modelers (e.g., the relationship between stress and team or individual decision-making). The combined effect sizes identified through these meta-analyses will allow the explicit comparison of the relative strengths of selected cultural variables on the effects that are investigated. The results of these meta-analyses would be used in Phase II to develop statistically-valid models of the effects of interest that for the first time accurately take into account cultural variation. Additionally, the quantitative review work conducted in Phase I will result in the identification of existing data gaps and will serve as highly-focused guides to future research on high-priority effects.

* information listed above is at the time of submission.

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