Title :
Incorporating cultural factors in a decision making model for the planning of U.S. military operations
Author :
Hamel, Rob ; Schafer, Mary ; Lee, Raymond ; Stewart, Roger ; Gippetti, Michael ; Touati, Harrison ; Adamshick, Andrew
Author_Institution :
Syst. Eng., Univ. of Virginia, Charlottesville, VA, USA
Abstract :
U.S. military decision making and operational planning often does not account for cultural factors. A review of past military operations shows that in many cases failure to account for a region´s cultural factors resulted in failure to achieve success in strategic mission objectives. Further analysis showed a significant increase in success rates for operations that accounted for cultural factors. This work aims to improve U.S. military decision making and operational planning by automating the collection of cultural data into a Cultural Factor Identification Tool (CFIT). The cultural data in CFIT is focused primarily at the country level and is gathered through open-source methods. These methods include collecting articles related to different countries and incidents and then parsing them to find frequencies of keywords. This frequency counts provide the input data for three different predictive approaches for generating factor specific, culture metrics. When converted into these metrics, cultural factors can be integrated within more sophisticated predictive models. Whether used within a larger model or on its own, the CFIT has the potential to significantly improve the quality of military decision making.
Keywords :
cultural aspects; decision making; military systems; operations research; planning; US military decision making model; US military operation planning; cultural factor identification tool; culture metrics; military decision making quality; open-source methods; operational planning; predictive approaches; region cultural factors; sophisticated predictive models; strategic mission objectives; Cultural differences; Data models; Decision making; Graphical user interfaces; Measurement; Predictive models; Vectors;
Conference_Titel :
Systems and Information Design Symposium (SIEDS), 2012 IEEE
Conference_Location :
Charlottesville, VA
Print_ISBN :
978-1-4673-1285-1
DOI :
10.1109/SIEDS.2012.6215140