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標題: 不確定情況下產品創新研發管道最佳化之研究
Structuring Optimal R&D Pipeline for Product Innovation under Uncertainty
作者: 王瑞德
關鍵字: 應用研究;Product innovation;工業工程類;產品創新;風險管理;實質選擇權;管道管理;管理彈性;蒙特卡羅模擬;基因演算法;R&D Pipeline;Managerial flexibility;Risk management;Real options;Monte Carlo simulation;Genetic algorithms
創造高市場價值的創新研發專案,通常有較高的技術與市場不確定性,因此若只發展一種產品技術或概念以取得商機會有較高的失敗風險。為了增加創新產品上市成功的機會,有些產業(如生技製藥、電腦、資訊、通訊等)會同時發展多個產品技術或概念,並延遲選定單一技術及概念的決策,以取得商機。這是因為過早選定產品技術或概念可能會限制未來產品創新的機會,而且同時發展多個產品技術或概念所增加的額外成本,可能被新市場所帶來的超額營收來彌補。研發管道(R&D pipeline)通常可分為數個階段,管理上的挑戰是在高度市場與技術不確定的環境下,各個階段如何決定使用單一方法(技術或概念)或多個方法以提高取得商機的成功機會,以及如何決定何種方法該被挑選與被選入的方法何時該被捨棄,就成為重要的研究課題。本研究將應用實值選擇權概念,發展一個研發管道結構化(pipeline structuring)模式來決定每一研發階段的最佳方法(技術或概念)組合,以提高取得市場商機成功的機會並最大化市場潛在利潤。模式中難以準確估計的不確定參數(如成功機率、發展成本;潛在市場收益等) 將使用合適的機率分配表示。本研究使用Monte Carlo 模擬來分析各階段所選用方法個數對潛在收益與彈性價值的影響。並結合基因演算法與Mote Carlo模擬以求得最佳研發管道,以最大化創新產品成功上市的機會與未來市場收益。最後,本研究方法將用一應用在診斷肝癌疾病的生物標記(biomarkers)研發專案來展示本研究方法的應用價值。本研究貢獻如下,文獻上較少研究探討研發管道最佳化的問題。大多數的研究限制包括假設不同的技術產品或產品概念的成功機率與發展成本皆相同、未考慮放棄選擇權等。本研究所提出方法可解決文獻上的研究限制。另外,本研究方法可協助決策者在不確定情況下進行取捨分析來決定在有限的研發資源及是否採用單一方法或多方法策略,以最大化市場商機成功的機會。最後,本研究可協助高科技產業應用彈性產品開發的觀念有效管理創新產品研發。

An innovative product development project that creates great business opportunitiesusually involves high technology and market uncertainty. It is easy to see that developingonly one technological approach or product concept to capture market opportunity is too risky.To increase flexibility to respond the technology and market uncertainty, some industries (e.g.,computers, information technology & communications, and pharmaceuticals) will considerdeveloping alternative technologies or product concepts at the same time and delay thecommitment to a particular technologies or concepts in order to have a better chance to meetfuture business opportunities. This is because the single decisions committed at the earlyR&D phase may constrain the future opportunity and additional development costs with themultiple alternatives can be compensated by the increased revenue gained by the expandedmarket share.The objective of this research is to develop a pipeline structuring methodology based onthe real options concept to determine an appropriate set of approaches for each stage of R&Dpipeline to increase the success rate of product launch for capturing new business opportunity.Uncertain parameters, such as success probabilities, development costs, and potentialrevenues that are hard to estimate accurately, are represented by appropriate probabilitydistributions. Monte Carlo simulation is used to analyze the potential profit and flexibilityvalue contingent on the number of product concepts or approaches committed to each R&Dstage. Genetic algorithm integrated with Monte Carlo simulation is used to determine theoptimal pipeline structure to maximize probability that potential profit exceeds apredetermined threshold. The proposed methodologies will be illustrated with a biotechR&D project in developing biomarkers techniques for early detection of liver cirrhosis andliver cancer.The potential contributions of this research are summarized as follows. Few studieshave investigated the pipeline structuring problem. The proposed pipeline structuring modelwill resolve the limitations of previous studies; e.g., deterministic parameters, same successprobability and cost, without the abandon options, etc. Next, the proposed methodology canhelp managers make the tradeoff analysis between single-approach development andmulti-approach development under uncertainty and effectively allocate limited R&Dresources on prospective projects to increase the success rate of product innovation. Finally,the proposed methodology will help hi-tech industries better manage their innovative R&Dprojects with the concept of flexible product development
其他識別: NSC97-2221-E005-066
Appears in Collections:科技管理研究所

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