Designing a Decision Support Prototype System for Forecasting National Defense Personnel Maintenance Expenditure:An Application of System Dynamics

• Main Authors: SU KUO-HAO, 蘇國豪
• Other Authors: Wang Wei-Kang
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/64005947415792196088

碩士 === 國防管理學院 === 國防財務資源研究所 === 95 === The high proportion of the personnel expenses of the defense budget is getting more controversial in these years. Through the military downsizing projects such as “Jingshi Program”, “Jingjin Program” to decrease the quantity of the army, the personnel maintenance expenditure is still increasing rather than decreasing. This research proposes a decision support system prototype for forecasting national defense personnel maintenance expenditure. The purpose is to construct a database, model base and knowledge base of the decision support system to deal with the problem that personnel maintain expenditure decision making through the network interface, and application of system dynamics in the model base. Another objective of this study is to simulate the manpower policy in the future, and to offer the change situation immediately. This decision support system converts numerical data into information that can be used to evaluate possible situations and accordingly proposes the suggestions or actions. This research uses system dynamics in the model base, constructing system dynamics model regarding the trends of personnel maintenance expenditure forecasting. The simulation includes “reduction of the number of military personnel”, “adjustment of salary levels”, “officers, noncommissioned officers, soldiers proportion”, “voluntary policy”, and “GDP share of national defense budget proportion” etc. The policy simulations are under different levels. The conclusion of this research shows that “All voluntary” and “officers, noncommissioned officers, soldiers proportion” could cause personnel maintenance expenditure proportion remains high. If the GDP proportion increasing, it can solve the pressure with insufficient budget. This research tries to use DSS to combine the system dynamics, not only provide policymaker with practice, and improve decision efficiency. The research can yet be regarded as the method that can be adopted to conduct solutions in the practice and research domain in the future.