從技術知識進步鏈辨識技術機會之研究：以telematics為例

從全球技術發展的視角，針對特定或專業領域的技術資料，以技術網絡分析觀點進行各種由淺入深的知識（shallow to deep knowledge）挖掘，不僅是組織因應外部環境動態變化、洞察機先與掌握策略性知識重要的來源，也是經營決策者改善創新績效與降低投資風險，終日不可迴避的管理議題。是以，本文依研究目的與專利檢索策略，從USPTO專利資料庫搜尋與關鍵字相關的所有專利形成分析資料集，並以文件中「引用參考（reference cited）」欄位的列舉資料進行相關專利的連結，進而構成一個專利引用網絡（patent citation network）。其後，也以此網絡為分析基礎，提出一個專利組合層級且具理論基礎的技術知識進步鏈分析（technological knowledge progress chain analysis; TKPCA）架構或模型；其分析結果，不僅可藉此辨識具潛在性的關鍵技術功能或技術組合的發展機會，其分析模型也可增補於先前研究的不足。另外，本研究也選擇「telematics」領域的專利，作為TKPCA模型檢驗的分析標的，同時，基於分析需求，TKPCA的架構，也包含了基礎性技術群聚分析（BTKCA）、新穎性技術群聚分析（NTKCA）與鏈接群聚知識重覆分析（LCKRA）三個子模組。最後，從telematics專利資料的三階段分析過程中，也分別發現了很多有用且有價值的技術發展情報與知識。本研究認為，這些發現對於telematics領域未來整體發展的創新促進與企業研發活動的投入和佈局，將會產生很重要的影響。

關鍵字

專利引用；基礎性技術知識；新穎性技術知識；重覆分析；深層知識

並列摘要

Purpose-The purpose of this study is to propose a dense network framework of technological knowledge progress chain analysis (TKPCA) on the basis of patent citation and to mine a variety of shallow-to-deep knowledge as an identification of developing potential technology opportunities. Design/methodology/approach-The ＂telematics＂ is the target for technological analysis in this study. Meanwhile, it is also used as the keyword to undertake patent retrieval from USPTO. Afterwards, an affiliated network (PCAN) will be set up as the analytic information database for TKPCA, including 3 sub-modules, BTKCA (basic technological knowledge clusters analysis), NTKCA (novelty technological knowledge clusters analysis), and LCKRA (linking clusters knowledge redundancy analysis). Findings-(1)From the findings of BTKCA, it appears that the basic technology of telematics consists of nine patent clusters; there are 4 main directions of technology development among network categories formed by these clusters. (2)From the findings of NTKCA, it appears the novelty technology of telematics consists of seven patent clusters in total. Among them, three clusters are involved and developed the most positively and intensively by manufactures whilst the rest 4 technology clusters are developing individually. (3)From the findings of LCKRA, the electronic image display technology has the most significant impact on novelty technology development as well as the innovative focus from the manufacturers' R&D. Furthermore, the values could be provided for R&D engineers to grasp the whole picture of telematics and to use as significant reference while assessing the potential opportunities and development. Research limitations/implications-The specialization growing technology is the main research subject regarding TKPCA in this study rather than emerging technology. Therefore, TKPCA does not consider the possible impact from non-patent literature citation, which could be improved in the future research. Moreover, the findings stated in this article mainly are searched with ＂telematics＂ keyword, so the outcome may differ accordingly once the keyword range changes. Practical implications - (1)The findings from BTKCA for business-level decision-maker are not only the imperative references to scheme an integrated function for a new product, but a very important technological information to predict whether it could become a welcome merchandise or not. (2)The findings from NTKCA for functional-level R&D manager present not only the imperative reference information to assess the timing of R&D projects, but a very important assessment information to identify the potential opportunities for technology R&D. (3) The findings from LCKRA for the operational-level engineers include not only the imperative evaluation information for R&D development method and direction, but an indispensable knowledge and insight into the development on key technologies. Originality/value-(1) TKPCA is a new concept and approach to extract a variety of technology knowledge simultaneously by the way from shallow to deep and multilayer; it is also an analysis framework, which can integrate common knowledge discussed rarely in traditional research. (2)The outcome of TKPCA cannot only speed up the evolution of overall technical specialization but also enhance the organization's short-term innovation performance, which is difficult to obtain through knowledge discovery in databases.