有鑒於企業訂單的不斷湧入，在既有的工廠中，會因為產能的不足，無法承接訂單的所有訂購數量。經過考量後，可能會採取增建廠房或是外包來提升產能，以避免失去訂單，降低獲利。另外一種狀況則是這段期間市場需求降低（如季節性產品），此時擴建的廠房或是額外聘用的員工的產能就會閒置，隨意裁員又會造成許多營運、商譽、形象以及社會問題，造成更大的損失。由於上述種種原因，企業在考慮如何接單的問題上，必須考慮到許多複雜的因素與關係，因此企業需要一套接單決策輔助模式，來幫助企業在制定接單策略時，能夠全面考慮各項因素（顧客關係、獲利率、製造成本等）。
本研究結合了策略地圖與資料包絡分析法，建構一個接單策略評選模式。利用策略地圖分析企業整體的策略與流程，並根據策略地圖分析結果，展開與建立績效評估指標，再根據管理上的實際意義，給予各項評估指標適當的權重範圍。由於本研究的規劃時程屬於中長期規劃，因此必須判斷下個規劃期市場的需求屬於淡季或旺季，以制定相對應可能的接單策略，接著利用資料包絡分析法的數學模式，進行客觀的接單策略效率評比，評選出整體效率最佳的接單策略。最後考慮到中長期規劃時程內績效評估指標可能有所變動，進行敏感度分析，以了解在評估指標改變時，最佳接單策略是否有所改變。
為了驗證方法的實用性，本研究以國內某手機零組件製造公司之接單策略制定為例，依照上述之方法流程，選出整體效率最佳的接單策略。

In facing the growth of customer orders, a company usually need to face the problem that it cannot accept all the orders because of the lack of capacity. In order to avoid the lost orders and profit, some solutions may be to expanse the capacity, to work overtime, to outsource and so on. The other situation is that the market demand is less than the supply capacity, and so some capacity or employees are idled. Under this situation, the arbitrary lay-off of employees may result in bigger problems such as affecting the daily operations, corporate goodwill and image and so on. Based on the above reasons, a company has to consider a lot of complicated factors and relationships in conducting order acceptance. Therefore, it is desirable to develop an order acceptance decision-support model to evaluate the overall factors in conducting the order acceptance task.
This research has combined the strategy map and the data envelopment analysis method to construct an order acceptance decision-support model. First we analyze the overall corporation strategy and the core processes with the strategy map to construct performance indices, than certain weight is assigned for each performance index based on its practical meaning of management. The next step is to develop possible order acceptance policies (i.e. the decision making units, DMUs) according to the demand forecast, and than evaluate the overall efficiency for each DMU with the data envelopment analysis method to find the DMU which has the best overall efficiency. Finally, by performing sensitivity analysis, a company can find out the allowable variation range of each DMU and its performance evaluation index.
A case study of a cell phone component manufacturer is conducted to verify the feasibility of the proposed methodology. The results show that it can be used to find the most desirable order acceptance policy.

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