影響技術移轉訂價之關鍵因素—以國內濺鍍靶材為例

Finding Key Factors of Effecting Pricing in Technology Transfer—A Case Study of Domestic Sputtering Targets

蕭羽辰(Yu-Chen Hsiao)

指導教授 ： 胡宜中

中原大學/商學院/企業管理研究所/碩士(2009年)

https://doi.org/10.6840/cycu200901377

摘要

半導體以及光電產業是推動台灣經濟發展的核心產業，在近十年以來隨著全球市場的成長而蓬勃發展，其中的關鍵性材料薄膜濺鍍靶材佔生產成本一半以上。且隨著薄膜濺鍍應用領域不斷的擴展，濺鍍靶材之種類及使用量也隨之增加。若國內中下游產業能夠技術移轉靶材技術製造方法不僅能帶動國內靶材產業、降低成本，對靶材及技術上的需求也能夠不完全的依賴國外靶材廠商。
靶材技術移轉伴隨著技術價格之訂定，一般針對技術本身、策略因素、競爭關係及議價能力等各項會影響訂價之因素做整體考量，而技術提供者以及接受者會分別就其所重視之因素進行交易談判。雙方應互相了解彼此所重視之因素，有助於縮短雙方對於價格訂定之差距。故本研究建立影響靶材技術訂價因素之研究架構，並探討其中技術提供者方及接受者方所重視之關鍵因素。
由於因素之間存在相互關聯性，故本研究建構出網路型式的層級架構，在架構中反應出構面間以及準則間相互影響的實際狀況，之後使用網路分析程序法進行構面及準則重要性之評估。在網路分析程序法中，以成對比較進行構面/準則的重要性評估，但傳統的成對比較所使用的九點尺度語意值無法顯示受訪者的主觀認知。而且成對比較通常有不一致性的現象產生。針對前者我們使用模糊數表達每一個語意值，針對後者則以乘法遞移性為基礎，提出具一致性之模糊乘法偏好關係；另以加法遞移性為基礎，產生具一致性之模糊加法偏好關係。在問卷填答上，將由原先的n(n-1)/2題大幅縮減至(n-1)題，可減輕受訪者的負擔。
研究發現具一致性之模糊乘法偏好關係與模糊加法偏好關係的準則權重排序在統計上無顯著差異。因此在結果的後續分析上，皆以模糊乘法偏好關係為基礎。研究結果顯示，技術提供者認為影響訂價最重要之關鍵因素為技術面中的技術被模仿的容易程度、革新速率以及複雜程度，其次為市場面中的市場需求穩定度。而技術接受者則認為影響訂價最重要之關鍵因素為技術接受者資源優勢面中的技術接受者運用技術能力，其次為技術面中的技術被模仿的容易程度、革新速率以及複雜程度。這顯示買賣雙方皆重視技術是否具競爭能力，並且為訂價交易上之具共識性因素。

關鍵字

模糊乘法偏好關係 ； 模糊加法偏好關係 ； 技術移轉訂價 ； 濺鍍靶材技術 ； 網路分析程序法

並列摘要

The semiconductor and the electro-optical industry are the core industries that promote the economic development in Taiwan. They develop as the global market growth for nearly ten years. One of the crucial materials is the thin film sputtering target. Its cost of production proportion has occupied for more than 50%. As the application domain of sputtering increases, the types and the amount of using of the sputtering targets will also increase. If domestic middle and lower reaching industries can transfer the technology of manufacture method of targets, it will not only push forward the domestic target industry, but will also decrease the cost of productions, the need of targets and related technology and avoid too much relying on the foreign target enterprise.
Transferring the technology of target depends on the technology pricing. In general, technology pricing will in view of factors that affect the price including technology, strategy, competition relations and bargaining ability. Technical providers and acceptors will carry on the transaction negotiations according the important factors on their point of view. The technology providers and acceptors should understand the factors that they respect with each other. It will contribute to shorten the providers’ and acceptors’ cognitive gap of pricing. Therefore, this study builds the framework of pricing factors of target. Besides, it confers the key factors that were respected by technology providers and acceptors.
This study builds the hierarchical framework of the network for the connection of factors. In the framework, it reflects the influence between the factors and sub-factors in real condition. Afterwards using analytic network process (ANP) to evaluate the importance of each factor and sub-factor. It uses pair-wise comparison to evaluate the importance. It could not show the survey candidates’ subjective cognitive if using traditional nine points scales of linguistic values in pair-wise comparison. In addition, it usually results the inconsistency. To solve the first problem, we use the fuzzy number to express each linguistic value. To solve the second problem, we create the fuzzy multiplicative preference relations with consistency base on the multiplicative transitivity; besides, we bring the fuzzy additive preference relations with consistency base on the additive transitivity. The number of questions that a survey candidate should answer in the questionnaire would contract from n(n-1)/2 to (n-1). This could lighten the load of survey candidates’.
We find the sequence is insignificant in statistics in this study. The sequence was computed from the weights of each sub-factor using the fuzzy multiplicative preference relations and the fuzzy additive preference relations with consistency. Therefore, the final analysis was base on the fuzzy multiplicative preference relations. The result shows that technology providers consider that the most important factor is the essence of technology. The key sub-factors are the degree of copying, the rate of innovation, the complex degree; moreover, the stable degree in the market. On the other hand, the technology acceptors believe that the key factor is the superiority resourced of technology acceptors. The key sub-factors are the ability of using technology, moreover, the degree of copying, the rate of innovation, and the complex degree. It shows both the sellers and buyers would pay attention to the competition ability about the technology, which are the consensual factors in the bargain of pricing.

並列關鍵字

Fuzzy additive preference relations ； Sputtering target ； Technology transfer pricing ； Analytic network process ； ANP ； Fuzzy multiplicative preference relations

參考文獻

曾國雄，謝嘉鴻，黃明居，2007，「模糊AHP與非加法型模糊積分法於工程承包廠商評選之研究」，科技管理學刊，12卷1期，頁29-54。

劉江彬，張孟元，2002，「技術及專利價值評估模式之研究」，台大管理論叢，13卷1期：頁37-84。

Abdelkader Djeflat. 1988. The management of technology transfer. View and experiences of developing Countries, 3(1/2): 149-165.

Abdi, M. R. 2009. Fuzzy multi-criteria decision model for evaluating reconfigurable machines. Production Economics, 117(1): 1-15.

Ayağa, Z. and Özdemir, R. G. 2009. A hybrid approach to concept selection through fuzzy analytic network process. Computers & Industrial Engineering, 56(1): 368–379.