陸軍自92年推動軍機策略性商維，積極運用國內資源，建立後勤維修管道，雖在縮短後勤回應時間略有成效，然實證結果仍無法滿足戰備整備需求。隨著新一代兵力維持費需求日增與國防預算分配額度逐年降低的趨勢，如何運用有限的資源，或建立更具效益的資源管理機制，已成為未來建軍所必須重視的課題。國防部自93年引進效益後勤觀念，期間多以教育訓練與學術研討為主。自98年運用先導專案結合國軍現行委商制度，期以適裁建立委商新模式，試行結果：有關「需求轉化為績效指標」、「成本分析之範疇、方式與蒐集來源」及「採購合約之妥慎訂定」等3項步驟，仍應持續精進汲取美方作業經驗。
為使效益後勤運用更趨成熟，本研究將賡續以「性能績效表現為基礎的固定價款」合約型態作為探討方向，針對「性能績效表現」的衡量準則，找出最適之效益量測模式，獲致成果如下：(1)找出最適後勤回應時間，修訂商維合約標的；(2)設立期望目標值，建立合約商獎勵報酬模式；(3)提供最小可接受門檻值，作為商維合約退場機制選項；期能導入軍機商維合約，以強化資源策略管理運用，完備國軍委商作業新模式。

Summary
This study investigates the principles of measuring performance to construct the optimal performance measure model base on a fixed-price contract with an aim to enhance the utility of aircraft contracts and thus have better outsourcing operations. The results show that: (1) The optimal logistic response time can be obtained to reuse the outsourcing contract, (2) The contractor reward pattern can be established to achieve expected goals, and (3) The minimum acceptable threshold can be determined for the decision of terminating the contract.
Keyword：Performance-based Logistic、Performance Measure Index、Multidimensional Reward Model
Introduction
The Ministry of National Defense has operated a mentor program with the military outsourcing contracts and intended to propose a new approach since 2009. The trial results indicate that the U.S. operation experiences should be consulted with regard to “To transform military demand into the performance index”, ”The range, methods and sources of the cost analysis”, and ”Formulating the purchasing contracts careful”. This study aims to construct an optimal performance measure model based on the performance measure indices to improve performance-based logistics and enhance management of resource strategies.
Materials and Methods
According to the multidimensional reward model (Sols et al., 2007b), this study denotes “Operational Availability (Ao)” and “Mission Capable Rate (MC rate)” as and , respectively, which are the two key performance measure indices to investigate the optimal logistic response time. The key measure index, , is assigned with a corresponding weight, , and then, the entirety system performance is denoted as .
As the measure index, , exceeds the corresponding target value, and the measure index, , is between the corresponding target value and minimum threshold, the compensation coefficient, C, becomes a decision variable, which determines the amount of rewards for the contractor. C must satisfy the requirement of minimizing the cost and maximizing the benefit.
After the entire system performance is measured by both the indices, Ao and , the three measurable attribute, “Operational Availability”, “Mission Capable Rate” and “Performance Reward” can be determined. With regard to the different expected values, the overall performance and rewards, , can be obtained , and according to the results of SMARTER-ROC analysis, the optimal logistical response time can be determined.
Results and Discussion
The results of sensitivity analysis indicate that the compensation coefficient, C, is a critical factor, and its value should be set between 0.560766 and 0.666667. This study suggests that the degree of variations should be indicated in the contract agreements to serve as a basis of altering the compensation coefficient. This study does not investigate the actual cost effectiveness, and which could be considered for further research and the results can be used as an important reference for improving military logistical efficiency in the future.
The results of the SMARTER-ROC analysis indicate that the optimal logistic response time is between 67 and 76 days by reducing 54% to 48% of the former logistical response time, and the mission capable rate is determined as 58.12%. Chapter 3 indicates that the focus of the military outsourcing contract is the maintenance of components in the system. Though the shorter maintenance time is better, completing maintenance within a few days is feasible but costly. Therefore, the related costs must be considered, since pursuit high efficiency requires a huge investment.
Captions
As can be seen in Figure 4-6, as the compensation coefficient, C, increases from 0.560766 to 0.666667, increases steeply and then slowly up to 1.232386, which is the peak value for C.
Table 4-6 shows the comparison of the different weighted values and attributes of programs , , and . The results of the SMARTER-ROC analysis indicate that program is the optimal one.
Conclusion
As Armaments Bureau plans to promote PBL, the successful application of PBL in the U.S. military and other countries should be considered to develop an appropriate PBL strategy for the military. Since the military will continuously purchase new weapon systems in the future, the needs of operation personnel, the nature of individual weapon systems and practical experiences should be considered to derive an optimal PBL strategy for the military.

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