- 學位論文
以網絡觀點分析產業結構對創新績效之影響
The impacts of industrial structure on innovation performance –An industrial network perspective
摘要
在全球化的發展下，比較國際經濟競爭力常從產業創新能力做衡量指標。探討產業創新機制，有助於瞭解創新理論用以解釋不同的分析單位，也對瞭解產業及內部廠商的創新行為有幫助，更可用於擬定經濟發展的政策建言上。過去探討國家或者區域創新系統多放在不同部門對廠商創新的影響，這類討論缺乏將不同產業特性納入考量；探討產業部門之間的創新活動，則是以跨產業部門的廠商來研究知識、技術等資源流動方式，很少從整體市場的角度探討產業不同網絡位置及交易模式與創新績效的關聯。 本研究透過次級資料分析，探討產業交易網絡及交易模式與創新之關聯。以「90年產業關聯表」做交易網絡之資料，另以《科學技術統計要覽》(2005)提供之研發人力、研發經費及中華民國智慧財產局提供專利數做為創新指標。 產業交易關係及網絡結構位置如何影響創新績效？結果指出，在「農林漁牧礦」業中，產業內交易金額與其創新能力相關；在「製造業」中，產業需求/供給交易量及網絡的外向中心性對創新行為有關聯；在未歸類的其他產業中，產業需求/供給交易量及網絡的內向/外向中心性與創新績效相關。另外，產業間交易型態如何影響創新傳染？結果指出，不同創新指標的傳染機制有所不同。在研發經費上，「結構同型」模型的關聯及模型解釋力較高；在研發人力上「凝聚性」與「結構同型」模型的關聯性及解釋力顯著且模型解釋力相似；在創新績效上，結構同型在關聯呈顯著且其模型解釋力較高。結果意涵不同的產業交易型態，會影響不同創新行為傳染模式。
並列摘要
The industrial innovation performance is one of the important indicators in the age of globalization in nowadays. The study of industrial innovation mechanism enhances our understanding of innovation theories, behaviors and strategies for firms within industries, as well as provides practical policy implication for industrial development. Most existing researches employ national or regional innovation theories to examine innovation outcome at firm’s level, industrial characteristics across industries are less mentioned. Furthermore, this is lack of study on innovation performance from the aspect of industrial structural network and transaction patterns among industries. Secondary data analysis is employed to examine the relations between industrial network structure and innovation performance. The data of industrial network are collected from the Input-Output Industrial Relation Table of Taiwan (2001). Innovation performance are measured by human resource, expenditures, and patent, where data are collected from the Indicators of Science and Technology, Taiwan and the website of Intellectual Property Office by the Ministry of Economic Affairs, ROC. The results indicate while the amount of transaction within industries is highly correlated with innovation performance in agriculture, forestry, fishery, animal husbandry and mining industries, the amount of demand /supply and out-degree centrality are correlated with innovation performance in manufacture industries. In terms of the relations between transaction pattern and innovation contagion, the results suggest that structural equivalent model provides a better model fit than cohesion model in the R&D budgets. Structural equivalence and cohesion models show equivalent explanation power on the human resource of innovation. For patent performance, structural equivalence model shows a better fit than cohesion model. In all, this study verifies innovation performance is shaped by transaction pattern and structural network.