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題名:從國家創新系統的觀點探討大學智慧資本與成果擴散效益之關聯
作者:江雪嬌
作者(外文):Chiang, Hsueh Chiao
校院名稱:國立政治大學
系所名稱:科技管理研究所
指導教授:李仁芳
學位類別:博士
出版日期:2008
主題關鍵詞:國家創新系統智慧資本創新管理系統結構方程模式National Innovation SystemIntellectual CapitalInnovation Management SystemStructural Equation ModelSEM
原始連結:連回原系統網址new window
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近年來我國在高等教育的學校與人數上均有大幅的成長。而這些豐富的研究人力,需要充沛的研究經費予以支援學術研究工作。實務上,我國於開放高等教育機構的設立後,各界所提供的研發經費並未相對應的增加,各校為因應整體環境趨勢的改變,乃積極研議如何強化學術研究成果的擴散,以提升學術聲望並獲得更多的實質效益。本研究在此情境下,試圖從國內大學之知識創新的實務發展,建構一套研究成果擴散效益的運作模式。
大學知識產業化是知識經濟發展的趨勢,尤其基礎研究是技術發展與應用研究的主要來源。大學知識創新過程是科學知識在創新系統內的生產、運用與擴散的過程。而建立有效的成果管理機制,減少外在環境的不確定性並改善知識流動的效率,是創新系統成功的關鍵。
鑑於大學係國家創新系統的重要成員之一,而創新的效率取決於系統內各成員之財務、知識、人力與法規的交流,即所謂的「三螺旋(Triple Helix)」的觀念。因此,為尋求最佳的創新系統,亟須建立有效的衡量項目,並促使創新成果在市場機制的導引下,獲得知識創新與擴散的經濟效益。如美國為因應創新系統失靈,於1980年以後,研訂一連串的相關法令,透過研發經費的補助、智財權下放與鼓勵設置專責技轉單位等措施,刺激大學將豐富的研究產出移轉到產業界,政府的研究資源分配亦更加重視目標導向與產業導向的發展計畫,結果所獲得的回收遠超過預期,其作法吸引世界各國競相仿效。我國亦於近年來透過相關法令的制定以及經費補助等措施,期望將大學的研究產出從知識的創造轉變為知識的加值與運用,以帶動產業知識化,並促進知識產業化之效益。
因此,欲探討大學的成果擴散效益時,不只是依循過去大多數學者從產學合作的觀點,更應考量政府在創新過程中所扮演的角色與功能,以及將衡量國家創新系統績效之方法運用到大學的成果擴散效益的呈現上,以建立適合我國大學創新成效的衡量模式。
本研究架構從教師的「研究人力」、「研究經費」以及「產學關係」等三構念探究對於「研究產出」以及成果推廣所產生的「擴散效益」之關聯,另外,再從學校的研究成果「管理機制」以及「政府措施」等二構念探究對於其他構念所帶來的影響,以瞭解彼此之關聯,並建立適合我國大學研究投入、產出以及擴散的運作模式。
因此,除了收集國內外的文獻以歸納整理美日等國在大學研究成果擴散效益的探討內容與衡量項目外,並透過問卷調查與實地訪問國內大學教師與研究成果推廣中心(或技轉中心)主管,以瞭解國內大學研究成果的實務運作,以獲得本研究的初步架構,繼而從美日以及我國大學的個案研究,探討國家創新系統的角色所帶來的影響,以強化研究架構之各構念的關聯性。
其次,採取初級資料的收集方法,以國內大學校院教師為問卷調查對象,進行敘述統計以計算樣本的各項指標分布狀況,以信效度指標確認問卷的可靠性與有效性,並運用探索性因素分析來萃取出本研究重要之變數,再以線性結構關係模型分析本研究變數之間的關係,以驗證各構念彼此之間的關聯性。
本研究獲得以下的結論:
一、「研究人力」與其他構念之關聯
「研究人力」對「產學關係」有直接的正向影響,對「研究經費」、「研究產出」與「擴散效益」則有間接的正向影響效果,而且整體的影響效果是顯著的。所以,研究人力是成果散效益的基本要素,配合其他構念的運作可以對研發成果之擴散效益產生正向的影響。
二、「研究經費」與其他構念之關聯
「研究經費」對於「研究產出」與「擴散效益」均沒有顯著的正向影響。顯示一味強調大學研究經費投入的作法無法帶來實質的成效,反而浪費有限的資源,因此,研究經費投入前,宜先制定一套評估機制,充分考量學校的研究人力、以往的研究產出與擴散效益之表現,以有效地配置研究經費。
三、「研究產出」與其他構念之關聯
「研究產出」對於「擴散效益」有直接的正向影響,表示大學教師所創造出來的成果越多,則相對地促使成果擴散的效益越大。此外,研究產出的增加亦可影響其他構念對「擴散效益」的關聯性。因此,為提高擴散效益,學校宜積極鼓勵教師增加研究成果的產出。
四、「產學關係」與其他構念之關聯
「產學關係」除了對「研究產出」與「研究經費」產生直接的正向影響外,亦間接影響「研究經費」與「研究產出」分別對「擴散效益」的關聯性。顯示產學關係可彌補大學與企業的技術落差,提高產業對學校研究成果之需求,促使教師研究產出的擴散效益更佳。
五、「管理機制」與其他構念之關聯
「管理機制」對「產學關係」與「擴散效益」均有直接的正向影響,顯示學校在成果管理與運用的積極作為(如技轉單位的設置、技轉人員的規模與培訓、獎勵措施的制定等)以及促進產學之間的關係可提高研究成果推廣所帶來的效益。
六、政府措施與其他構念之關聯
「政府措施」不但對「擴散效益」有直接的正向影響,亦對「產學關係」有直接的正向影響,此外,對「研究經費」與「研究產出」亦有間接的正向影響。因此,未來應加強我國政府的角色,充分發揮驅動與強化的功能,解決大學研究成果擴散的管制與障礙、營造產學研發資源共享環境以提高大學研究產出的擴散效益。
After the government lifted the restriction on the number of higher education institutes, in the past two decades the number of university in Taiwan has increased dramatically (16 in 1986, and 102 in 2008). The government apparently could not match up this increase, with its slow pace of education budget increase. The shortage of development funds from governmental agency in charge is no doubt obvious for all universities. Therefore, to receive an ample share of governmental education budget has become competitive and even difficult.
As the global economy weighs more on the generation and dissemination of knowledge nowadays, universities seems to see themselves clearer in the business picture for their role on the economic market. University officials and the government both also understand that a productive conversion of university intellectual assets, referring to knowledge-based creation or innovation, to innovation-derived benefit can be crucial for future university development. Thus, not only the university finance will be improved, its academic performance shall also be expected to enhance when this conversion is being well performed productively.
An innovation management system here refers to a university system to manage its intellectual capital, such as support and process infrastructures, in facilitating the conversion process that enable the university to convert its intellectual assets into commercially viable properties. An important aspect of this study is to analyze national and international innovation management systems currently practiced in universities for greatest innovation-derived benefit.
In the current of knowledge–based economic development, the knowledge-based innovations owned by universities is inevitably weighed more than ever in value. Many Universities may fall in a dilemma about how to weigh market–oriented research in comparison with fundamental scientific knowledge, since the latter never the less could lead to market–oriented innovation in the future. Furthermore, to maximize the value of innovation, it is commonly accepted that a proper management for conversion is almost as important as the producing of it. When it comes to determine the value or the benefit the innovations could bring, other than university’s innovation capability, which tends to have the potential to incubate more research outcomes, the performance of innovation management system is one of the most decisive factors. To achieve a good performance, three conditions are proposed to maintain an efficient innovation management system: an effective management mechanism, reduce adverse influences on incubating innovation assets, and increase knowledge sharing.
The maintenance of such a system is then further categorized as seven conceptual indices (CIs) for later evaluation: research manpower, research grant, innovation outcomes, management mechanism, university-industry relations, government policy, and innovation-derived benefit. The first four are regarded as part of intellectual capital, while the other three are considered as strongly linked to the performance of the innovation management system currently being operated in Taiwan’s universities. They will be discussed in connection the first five CIs for their inter-relations.
Since universities is under the scheme of National Innovation Systems (NIS), which covers primarily a finance and service system, a technological innovation system, and a knowledge-based innovation system, any management taking place in a university on each of any sub-system under the NIS will affect the NIS to some extent. By the same token, considering those mentioned above several conceptual indices are proposed to elucidate the results of the evaluation model applied in this study to examine similar management systems in different universities for comparison. This evaluation model is expected to help optimize the current managerial models to best meet the knowledge-based economic development needs and enlarge the innovation-derived benefit from university innovation assets.
Prior to 1980s, the promotion on innovation in the U.S. was generally considered failed. To save the failing systems, the U.S. government announced a series of new regulations to promote the capitalization of academic innovations by universities. Those policy measures mainly included governmental subsidy to research grants, less constraints on intellectual property (IP) licensing, and start-ups for IP transfer. Furthermore, the government diverted more its research support into market-oriented development projects. Since such moves later resulted in a positive outcome beyond expectation, Taiwan as well as some other countries began to replicate those measures in their own countries.
As the sources of future development increasingly depend on the derived benefit from innovation, the success of NSI originated by the U.S. government has indicated a new approach different from previously predominated models of solely university-industry cooperation. The involvement of government role in the NSI has been proved essential for its success. Similarly, the innovation management system being operated with the university intellectual capital to enhance the conversion to innovation-derived benefit is defined as the innovation assets management system (IAMS). It can be considered as a sub-system of the NSI, and the use of the evaluation model to examine the IAMSs can properly shows the difference among all the IAMSs by university.
Furthermore, the evaluation model proposed takes account of surveys including interviews with IP transfer professionals and research professors. Cases of universities practicing the IAMS along with others published in literature are also studied to help access the relations among index items in the model.
The model is constructed with several measures, including Structural Equation Model (SEM), Exploratory Factor Analysis (EFA), and Confirmatory Factor Analysis (CFA), to evaluate the performance of the IAMS on successful conversion from intellectual assets into benefit. The model results are depicted with CIs as the conclusions.
A qualitative survey is carried out on the evaluation of inter-relations among the seven CIs described above with Taiwan’s university educators as respondents. Confidence interval is applied to assure data reliability and validity. Significant model variables are identified using the explorative factor analysis. Finally the linear regression is applied to examine the relations among those CIs.
The results of this study can be concluded as the following:
1.Research manpower
It has positive influence directly towards university-industry cooperation when affecting positively towards research grant, innovation outcomes and innovation-derived benefit. The result suggests that it be the fundamental CI responsible to innovation-derived benefit. And along with other CIs, this CI could result in a comprehensive enhancement on the innovation-derived benefit.
2.Research grant
It shows less significant effect over innovation outcomes and innovation-derived benefit. This conclusion indicates that the scale of innovation outcomes will not necessarily in proportion to the financial investment on research. It is suggested that a comprehensive evaluation on research manpower, innovation capability, and research capacity, etc. should be conducted prior to market-oriented investment on research.
3.Innovation outcomes
This term shows a positive relation with the innovation-derived benefit. It is easy to understand that university educators with more innovation outcomes tend to receive more innovation-derived benefit. Furthermore, increase in innovation outcomes will also help induce stronger links among the other CIs towards the innovation-derived benefit. Thus, encouraging educators for more innovation outcomes is no doubt a good measure for universities.
4.University-industry relations
University-industry relations bear positive influence to innovation outcomes and research grant. It also shows its positive effect on the relations between research grant to innovation-derived benefit and between innovation outcomes to innovation-derived benefit. The role of university-industry relations can be depicted as to lessen the technological gap between university and industry, facilitate the industry need for university innovation outcomes, and multiply innovation-derived benefit.
5.Management mechanism
The management mechanism shows positive influence on university-industry relations and innovation-derived benefit. An effective management mechanism on innovation outcomes would directly lead to excellent benefit derived from innovation outcomes.
6.Government policy
Government policy shows straight links to university-industry relations and innovation-derived benefit. It also indicates an indirect effect on enhancing both research grant and innovation outcomes. In the future, the government should play a key role in promoting universities to practice such a system and help resolve difficulties arisen.
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