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危機管理學刊

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篇名 運用系統動態學探討國軍組織精簡政策對動員教育召集訓練師資供需之研究─以後備指揮部為例
卷期 13:2
並列篇名 The System Dynamics Approach to the Training Instructor Supply and Demand of the Military Mobilization and Muster-call Training after Military Organization Downsizing in R.O.C –A Case Study of The Reverse Command
作者 劉培林李庭閣吳文淵
頁次 087-101
關鍵字 系統動態學後備指揮部動員教育召集System DynamicsThe Reverse CommandMilitary Mobilization and Muster-call
出刊日期 201609

中文摘要

隨著科技的進步及戰爭型態的改變,國軍 推動各項組織精簡政策,歷經「精實案」、「精進 案」及「精粹案」,未來更計畫推行「勇固案」, 國軍依不同階段有不同的建軍規劃,目標是打造 小而精、小而強、小而巧的專業化部隊,預計兵 力將精簡至約17 萬人,但在人員不斷的精簡 下,後備指揮部擔任教育召集訓練的教官師資人 數卻逐年下降,但每年的召訓梯次及應召員的人 數卻沒有明顯減少,導致教官與應召員供需失 衡,如何在組織人力精簡的同時兼顧任務遂行, 應是值得探討的議題。
本研究以後備指揮部的動員教育召集訓練師資為研究對象,運用系統動態學為方法論進行影響教官教學品質、額外工作量、應召員鑑測成績及供需比之關鍵因素分析,建構動態分析模型,並運用此模型進行政策分析與模擬,探討不同政策(教官編制縮減幅度、班級授課人數、教官補充時間及任務支援比率)對教學品質、鑑測成績、額外工作量及供需比之影響趨勢,作為高階管理者制定相關政策之參考,其相關政策建議將於文內探討。

英文摘要

Along with the advances in technology and changing patterns of war, Taiwan’s military had implemented the policy of organizational streamlining. After the “Jingshih Program”, “Jingjin Program”, and “Jingtra Program”, Taiwan’s military now planning to implement the “Yungu Program” to create a small but excellent, powerful, and clever professional army and expected to streamline the number of people about 170,000. Under the situation of streamlining, the teachers of education and mobilization recall are unbalanced of supply and demand. Therefore, how to do best use of resources and planning appropriate policies to meet the needs of training is an important issue to study.
This research with the Reserve Command of MND for individual case, and established a dynamic system model to analyze the factor of teaching quality, extra workload ,call members’ identification scores and supply and demand of trainers. Then construct a dynamic analysis model and use it to analyze the policy. By discussing the influences of teaching quality, test results, additional workload and the impact of supply and demand ratio trend to provide the top managers suggestion when they formulate relevant policies. Relevant policy recommendations will be revealed in paper discusses.

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