在目前電子產品的生命週期汰換越來越快速，為維持具有競爭力的成本條件，委外的趨勢必不可擋 。而對於以OEM/ODM為主的台灣代工環境，生產力(Productivity) 又是企業主須要兼顧的指標；在企業主以人力精簡為考量時，通常採行的方案有裁員、將正職員工轉聘為派遣人力、工作外包、減薪、減少工時、強制休假等選項，無非要保持彈性，以期能在景氣回升之際做好準備。在這些項目中，通常派遣人力在直接人員的人數與工時又占工廠運作時成本的最大區塊，因此，本研究選定如何對派遣直接人員人力指標中產生的離職傾向(Turn over trend)進行分析。
本文借由對科學園區契約從業人員的在職離職狀況，以資料庫知識探索(Knowledge discovery in database, kdd) 的過程中決策樹的技術，運用群集與關聯法則等方式，配合三年期間所探討的派遣離職人力對於招募、工作安排與滿意度及離職率間的關連性予以佐證。提出不同的分類方式並以離職率為考量權重來分析出易離職群。同時為反應成長趨勢與景氣波動，加上三年來的臺灣景氣綜合指數，進一步了解派遣人員的離職與公司股價與經濟景氣間的關係，並以科學園區特定產業中的代表性廠商進行個案研究方式，實際了解：招募管道方面，透過公司內部員工介紹的派遣人員離職率較低；派遣人員會受工作時段安排的不同而有離職率差異的影響；從契約工的年齡分佈與年資級距的角度，其越資淺者，離職率較高；派遣人員經過試用錄用後於轉正職人員，其離職率較低；這些易離職群中，皆以當月經濟領先指標變動的狀況，來作為契約人員離職前的重要參考。

The life cycle in electronic product is getting faster. In order to keep the cost advantage, the enterprise must try to outsource. But regarding by the OEM/ODM primarily Taiwan generation of labor environment, the productive forces (Productivity) also is the target which business owner must have to give dual attention to. In these items, usually dispatches the manpower occupies the factory operation with the man-hour the cost biggest sub-area, therefore, this research designated how to dispatches in the direct personnel manpower target to produce the tendency (Turn over trend) to carry on the analysis.
This article borrows in office by dispatched-workers turn over condition to the science park area contract jobholders, as a means of materials storehouse knowledge exploration (knowledge discovery in database, kdd ) in the process the decision making tree's technology, which finds: recruits the pipeline aspect, dispatched worker turn over trend which the penetration company interior staff introduced to be lower; Dispatched worker make the difference with the time interval arrangement differently to have the different turn over trend ; the more junior of dispatched worker which turn over trend is higher than senior. Dispatches worker to hire after the test to transfer to the regular duty DL, it turn over trend is lower. These are easy to leave job in the group, all by the same month. All the turn over rate dispatched worker shows that would take the served company stock price as economy leading target change condition index before they leave.

Keyword: knowledge discovery in database (kdd), data mining, dispatched workers, turn over trend

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