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智慧資本與動態能耐對研發團隊創新績效的影響 / The Impact of Intellectual Capital and Dynamic Capabilities on R&D Teams’ Innovative Performance林良陽, Lin,Liang-Yang Unknown Date (has links)
研究智慧資本領域的學者認為,智慧資本是組織競爭優勢的主要來源,而且也會影響組織績效(智慧資本愈高,其組織績效愈好)。但是,智慧資本與創新績效之間是否存在有正向關係,卻值得進一步探討。本研究認為,在動態環境下,智慧資本觀點並無法適當地解釋,為何組織有能力回應快速變動的外在環境,以產生較好的創新績效。智慧資本領域的學者與專家鮮少對「『靜態的』智慧資本」與「『動態的』運用智慧資本能力」進行區辨;而本研究認為這是兩種不相同的概念。本研究目的即希望瞭解研發團隊「運用」智慧資本對其創新績效的影響。
另一方面,為了解釋為何某些企業在快速變動與無法預期的市場中依然可以保有其競爭優勢,某些學者擴張資源基礎觀點到動態市場中,並提出「動態能耐」觀點(Teece, Pisano, and Shuen, 1997)。本研究主張,研發團隊的動態能耐除了直接影響創新績效之外,也是其「運用」智慧資本的關鍵因素。動態能耐對組織績效與創新績效的關連,雖有學者著墨;但,其實證研究並不多見,有待相關學者提出更多的貢獻。再則,動態能耐是一複雜的概念,若要對其進行衡量,應該要進一步釐清該構念,甚至建構適合的衡量指標,提出較為完整的、且符合信度與效度的衡量量表,方能正確地衡量動態能耐。
本研究同時採用質化與量化的研究方法。質性研究是從動態能耐相關文獻出發,在釐清各個學者對動態能耐的定義後,萃取出動態能耐之不同構面與架構,再經由各項假說之推演,提出本論文之初步研究架構。之後,選取N大學無線奈米生醫研究團隊為個案,深入瞭解該團隊兩項突破式創新計畫,分別是「抗SARS一號」與「無線奈米生醫感測晶片」研發計畫,用以觀察該團隊如何回應變動的外在環境,來說明智慧資本與研發團隊的動態能耐對其創新績效的影響。透過不同階段的觀察,進行分析與歸納,並找出其共同的特性,以瞭解本研究架構的初步解釋力,並進一步依個案研究的新發現修正各項假說,最後提出本研究之實證研究架構。
在量化研究方面,首先,為了能精確地衡量動態能耐概念,本研究依照Hinkin(1998)量表發展步驟,以五階段三個樣本群來發展動態能耐的衡量量表。其次,在發展出符合信度、內容效度、模型適配度、收斂效度、鑑別效度的動態能耐衡量量表後,以第三群樣本進行本研究之假說檢定,以確認智慧資本與研發團隊的動態能耐對其創新績效的影響關係。
研究發現,動態能耐是一個多面向多層次構念,可以以三構面八因子共19題項的問卷來衡量,三構面是指結合能耐、吸收能耐與彈性。在假說檢定部分,本研究共提出9項假說,結果有7項假說受到支持,另有2項假說未獲得支持。結果驗證本研究的主要論點,亦即智慧資本對研發團隊創新績效的影響並不顯著;而研發團隊如何運用智慧資本的能耐(亦即動態能耐),顯著地影響其創新績效。此外本研究發現,結合能耐是中介變項,它完全中介了吸收能耐對創新績效的影響;吸收能耐也是中介變項,它完全中介了人力資本以及關係資本對結合能耐的影響;而彈性則是交互變項,它會正向地強化各項智慧資本對吸收能耐的影響。最後,本研究也得到兩項特別的觀察,一是,具有動態能耐的研發團隊在研發能量提升上的兩種向度,二是,它是一種「彈性球體」的組織型態,方得以快速地回應外在環境的改變。 / The scholars who studied the field of intellectual capital (IC) argued that IC was the main source of organizational competitive advantages. Besides, they thought that the better the IC a company has, the better the business can have the ability to generate innovative performance. However, the relationship between IC and innovative performance needs to be explored further, because of being inconsistent with some practical cases. This research proposed that the view of IC could not explain appropriately why organizations could generate better innovative performance in the dynamic environment. Besides, the scholars who studied IC seldom distinguished “static IC” from “dynamic ability for utilizing IC”. Whereas, this research proposed that these two constructs were different concepts, and would like to explore the impact of utilizing IC on innovative performance.
On the other hand, in order to explain why some enterprises could keep their competitive advantages in the rapidly changing environment, some scholars proposed the viewpoints of dynamic capabilities (DCs). This research argues that it has a directly significant effect of DCs on innovative performance, and DCs are the critical factors for utilizing IC. This research proposes that DCs are complex constructs. Therefore, we should clarify these constructs and provide an appropriate measurement tool with reliability and validity, if we would like to measure them.
This research adopted qualitative and quantitative researches simultaneously to demonstrate these arguments. After clarifying the definition of DCs and extracting the components of DCs from the literature review, this research deduced several hypotheses and formed the research framework. This research selected the research team of N University for developing wireless nano-bio systems as a case, and thoroughly explored two of its radically innovative projects, including Anti-SARS R&D project and sensor chip for wireless nano-biotach R&D project. Through observing their response to the rapidly changing external environment, this research illustrated the impact of IC and DCs of R&D team on its innovative performance. By the two-stage observation, analysis and induction of this case, we could understand the preliminary power in explaining this research model, and amend the hypotheses.
As for quantitative research, first, according to the scale developing steps, suggested by Hinkin (1998), this research developed the measurement tool of DCs with five stages and three samples to measure the concept of DCs precisely. Secondly, after developing the measurement scale of DCs, which surpassed the acceptable level for reliability, content validity, goodness of fit, convergent validity and discriminate validity, this research utilized the third sample testing the hypotheses to confirm the relationships among IC, DCs, and innovative performance of the R&D teams.
The results showed that the concept of DCs is a multi-level and multi-dimension construct, which is composed of combinative capabilities, absorptive capacity and flexibility. In addition, it can be measured by three-dimension and eight-factor scale with nineteen items. As for the hypothesis testing, there were nine hypotheses in this research. Seven of them were supported, however, two of them were not supported. The results confirmed the main arguments of this research. That is, it doesn’t have a significant effect of IC on R&D team’s innovative performance. However, it does have a significant effect of DCs on R&D team’s innovative performance. In addition, the results showed that combinative capabilities and absorptive capacity are mediators. The combinative capabilities fully mediated the effect of absorptive capacity on innovative performance. The absorptive capacity also fully mediated the effects of human capital and relationship capital on the combinative capabilities. Meanwhile, the results showed that flexibility is a moderator, which enhanced the effects of different ICs on absorptive capacity. Finally, this research got two special observations. First, there are two dimensions of R&D energy promotion for R&D teams with DCs. Secondly, it is a type of “flexible sphere organization” for the R&D teams with DCs, so that they can respond to the rapidly changing external environment.
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