Objective: This research is to visualize the patent citation network of patent pledge financing project, identify the patent characteristic parameter, the conventional network parameters and initially define the original creativity (OC) and irreplaceability (IR) of patent citation network, and explore the significant influential factors of patent pledge financing. Research Method: This research adopts social network analysis method to build 376 patent citation networks of patent pledge financing projects in Tianjin City from 2010 to 2015. The visualization of patent citation network is accomplished by software Gephi. Determining the patent characteristic parameter, such as backward citation, forward citation, claim numbers, family size, patent age etc., conventional network parameters, such as average degree (AD), average path length (APL), average clustering coefficient (ACC), network density (DEN), network diameter (ND), patent portfolio (PP), total backward citation (TBC), total forward citation (TFC), innovative network parameters, original creativity (OC), irreplaceability (IR), multiple regression analysis is applied to explore the significant variables for patent pledge financing. Result: This research has built 376 patent citation network of patent pledge financing project, determine variables of conventional parameters and network parameters, as independent variables of the multiple regression model, and the logarithmic of patent pledge financing value as dependent variables. In model with only conventional parameters, variables are significant at 5% confidence level except patent age. In model with only network parameters, variables are all significantly influence the logarithmic of patent pledge financing value at 1% confidence level. When all parameters are put in one model, network variables are still significant at 1% confidence level, but most of conventional parameters are not significant any more at 1% confidence level. Conclusion: Patent citation network maps out the technology of patent pledge financing. Comparing with other research of patent valuation based on patent citation network, this research directly takes patent financing amount as the representative of patent value and introduce network parameters as the independent variables of patent pledge financing regression model. Network parameters have significant influence on vi patent pledge financing value at 1% confidence level. And parameters of original creativity and irreplaceability show patent portfolio’s position in technology flow as well make significant effect on the patent pledge financing value at 1% confidence level. Network diameters are more powerful than conventional patent parameters influencing the patent pledge financing value.

目的：本研究旨在構建專利質押融資項目的專利引證網絡，使專利技術流動、 技術格局可視化。確定專利引證網絡的主要參數并創新性地提出專利的原創性、 不可替代性參數。建立專利引證網絡參數作為自變量的專利質押融資模型。 研究方法：本研究採用社會網絡分析方法，構建2010-2015年天津市質押融資項 目的專利引證網絡，該網絡的可視化由軟件 Gephi 完成。確定了平均度、平均 路徑長度、平均聚類係數、網絡密度、網絡直徑、原創性、不可替代性、專利 組合、總引證專利數、總被引證專利數作為專利質押融資模型的自變量，以專 利質押融資額的對數值作為因變量，建立專利質押融資模型，模型的建立由軟 件 EViews 完成。 結果：本研究通過在國家知識產權局中檢索得到了各單個種子專利的傳統屬性 指標，通過繪製了 376 個專利質押融資項目的專利引證網絡，得到項目層面上 的專利引證網絡屬性指標，通過合理的定義確定了原創性及創新的不可替代性 指標。在只有傳統屬性指標的回歸模型中，引證專利數、被引證專利數、同族 專利數、是否首次質押等自變量在 5%的置信水平，對單個專利融資額的對數值 有顯著影響；專利年齡的影響則不具顯著性。在只有網絡參數的模型中，所有 網絡參數在 1%的置信水平具有顯著性。在同時具有傳統參數和網絡參數的模型 中，網絡參數在 1%的置信水平依然具有顯著性，但絕大部分傳統參數在 1%的 置信水平不具顯著性。 結論：專利引證網路體現了專利質押融資項目中出質專利所處的技術格局以及 技術流動，本研究繪製了 376 個專利質押融資項目的專利引證網絡。與其它基 於專利引證網絡的專利價值評估研究相比，本研究直接採用專利的質押融資額 作為價值的代表，並且引入了專利引證網絡參數作為專利質押融資模型的自變 量。專利引證網絡的整體網絡參數對專利質押融資額有顯著的影響。專利引證 網絡的原創性及創新的不可替代性參數顯示了種子專利組合在技術流動中的地 位，對專利質押融資額有顯著影響。專利引證網絡參數對專利質押融資的影響 比傳統指標參數更強。