本研究旨在歷程性探討學習進展式激勵對企業組織成員學習與創新表現的影響，並發展學習進展式激勵成為動態、即時化學習診斷工具。依據文獻探討得知，組織成員因應探索型創新與開發型創新情境，需要調適探索型學習與開發型學習運用，而提升創新表現。因此，學習進展式激勵係以極大化學習進展酬賞為基礎概念，激勵組織成員持續追求極大化的探索型與開發型學習進展。本研究設計模擬創新情境的數字預測實驗，實施學習進展式激勵於40家台灣企業之154位工程人員，探討社會關係、學習類型、產業類別三個因子對於成員學習與創新表現的影響，發現學習進展式激勵能夠促進組織成員持續追求極大化學習進展，並依照創新情境而動態調適探索型學習與開發型學習運用，導致持續提升創新效率的創新表現。
對於創新情境之變動目標，普遍為企業組織使用的條件式酬賞缺乏有效激勵，本研究針對此缺失，發展進展趨動性學習進展式激勵，以極大化學習誤差距﹙學習進展﹚取代條件式酬賞的極小化固定目標誤差。為求實現學習進展式激勵成為動態、即時化學習診斷工具，本研究發展學習進展式激勵之量化機制與學習進展比率曲線之視覺化圖示機制，於實驗歷程中將組織成員的學習記錄轉化為量化的學習進展數據，再以學習進展比率曲線展示探索型學習進展與開發型學習進展的歷程性演變發展。透過多元線性迴歸處理特定群組之學習進展比率曲線，成為代表特定群組學習進展演變的學習進展比率特徵曲線，搭配質性的小組訪談記錄，成為本研究的分析資料。本研究結論如下：
﹙一﹚ 學習進展式激勵能夠有效提升組織成員學習與創新表現。
﹙二﹚ 學習進展式激勵促進形成學習進展式創新循環。
﹙三﹚ 學習類型、產業類別、社會關係三個因子對於組織成員學習與創新表現具有個別獨立與交互作用影響。
﹙四﹚ 學習進展式創新循環產生創新四階段循環、學習均衡、學習導航、學習氛圍建構的學習特性。
﹙五﹚ 依據學習特性對於學習與創新表現的影響，對企業組織提出提升學習與創新表現的指南。
﹙六﹚ 學習進展比率特徵曲線，成為人性化之動態、即時化學習診斷工具。

This study is a process-phase research to explore the influence of Learning Progress Motivation (LPM) on corporate organizational members’ learning and innovation performance. Furthermore, LPM is developed to be a user-friendly tool in dynamic real-time learning diagnosis. In order to enhance innovation performance, organizational members need to adapt the utilization of exploratory and exploitative learning with exploratory and exploitative innovation according to literature review. Hence, LPM is designed to motivate organizational members pursuing both maximal exploratory and exploitative learning progress based on the concept of Maximal Learning Progress (MLP) reward. The experiment of number anticipation was designed to simulate innovation contexts, which was applied on 154 engineers from 40 firms in Taiwan. The influence on subjects’ learning and innovation performance through three factors in terms of social relationship, learning style and industrial attribution was studied. The findings indicated that LPM motivated organizational members pursuing MLP continuously and adapting the utilization of exploratory and exploitative learning according to innovation contexts, which resulted in enhancing innovation performance by continuously improving innovation efficiency.
The contingent reward, which is widely applied by corporations, is weak in motivating people under changing target condition. The progress-driven LPM was developed to improve such weakness by using maximal learning error rate (learning progress) to replace minimal learning error used by contingent reward. In order to realize LPM as a dynamic real-time learning diagnosis tool, the LPM quantitative mechanism and visualized graphic technique were developed to convert subjects’ learning records into quantitative data and transform it into LPM curve format. The LPM characteristic curve was generated through processing LPM curves by multi-factor linear regression, which represented the development between exploratory and exploitative learning progress of a specific cluster.
Through the analysis of LPM characteristic curves and group interview reports, the findings are:
1.LPM enhances organizational members’ learning and innovation performance.
2.LPM facilitates learning progressive innovation cycle.
3.Social relationship, learning style and industrial attribution influence organizational members’ learning and innovation performance independently and crossly.
4.Learning progressive innovation cycle possesses learning characteristics in terms of four-step innovation cycle, steady-state learning condition, learning navigation effect, and learning environment construction.
5.The learning and innovation performance guidelines for corporations are developed according to the influence of learning characteristics.
6.LPM characteristic curve is developed to be a user-friendly tool in learning diagnosis.

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