投資人在投資決策之過程中，所分析之資料可分為財務性與非財務性資訊兩大類，然而受限於傳統財務資料格式之不一致，可能需花費額外之財力與物力來處理，甚至浪費精力於資料的重新輸入。另一方面，非財務資訊在投資決策過程中日益重要，但其龐大的資訊揭露量卻往往徒增投資人閱讀與搜尋上之不便，甚至降低了可閱讀性。
有鑑於上述兩大投資分析不便之處，本研究運用文字探勘(Text mining)技術，嘗試處理股東會年報中與企業策略相關之非財務性資訊，以協助閱讀者有效率地分析、整理這些半結構化，甚至是非結構化文字資訊。另一方面，本研究利用可延伸企業報導語言(eXtensible Business Reporting Language, XBRL)不受軟體平台限制，可於網路上自由下載流通等特性，作為財務資訊之資料來源，同時建立一種新的分析模式，透過連結機制之設計以連接非財務性與財務性資訊，並運用ROMC系統分析法與雛型系統設計法完成本企業策略分析決策支援系統，希冀能協助投資人能於短時間內瞭解並印證標的公司之產業發展與競爭策略，提升決策品質。 / There are two main data types in investment decision process: financial and non-financial. Because the inconsistent of data type in traditional financial data, investors may have more additional costs to solve this problem. In addition, non-financial data become more and more important in investment decision process, but huge amount of non-financial disclosure may reduce the readability and increase the difficulty of searching.
To solve the above problems, we try to use text mining technology to handle the semi-structured or unstructured non-financial data related to business strategies in the annual reports of public companies effectively and efficiently. In addition, we use XBRL (eXtensible Business Reporting Language) to be our financial data resources because of its interoperability and re-usability. We also develop a new analytic method to link financial and non-financial data together. Finally, we use two system methodologies: R.O.M.C. and prototyping to design and build our business strategy analysis decision support system in order to help investors understand and prove strategies in companies, and improve the decision quality which they make.
| Identifer | oai:union.ndltd.org:CHENGCHI/G0094353014 |
| Creators | 連子杰, Lien,Tzu-Chieh |
| Publisher | 國立政治大學 |
| Source Sets | National Chengchi University Libraries |
| Language | 中文 |
| Detected Language | English |
| Type | text |
| Rights | Copyright © nccu library on behalf of the copyright holders |
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