專家決策支援系統（Expert Decision Support System）是一種結合專家 系統與決策支援系統功能於一體的電腦化資訊系統；它同時具備有處理定 性資料與定量資料的能力，可以進行各種知識法則的推論及數量模式的執 行與分析，以完整的支援問題之求解過程。 / The expert decision support system(EDSS) is a computer-based nformation system which integrates functions of the expert systemnd the decision support system. EDSS, which is capable ofrocessing symbolic and numerical data, provides the

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.

人身風險管理為個人或家庭控制身體及財務損失機會，轉移風險獲得安全保障的管理方法與流程，其中人身保險為最常使用之風險移轉及理財工具．人身保險供需雙方所面臨的問題及作業程序包括消費者的保險需求預估、保險商品選擇..等。以及保險經營者的保險行銷、核保處理、保險精算、契約保全管理、理賠處理、資金運用等，其問題解決與程序處理之效率與效益，取決於人身保險相關資料、模式及知識之有效整合與運算。 　　本研究的目的即在探討人身風險管理中供給面之保險經營者及需求面之投保消費者之間的整合作業程序與互動關係，並提出一個專家決策支援系統架構來引導人身風險管理資訊系統之建構與應用，以支援供需兩個構面的資訊與決策需求。一個利用軟體整合方法所建立的人身保險選擇原型系統，將用來作為本研究的可行性驗證。資訊之組織、呈現及交談式操作介面，則採用超媒體方法，以提昇系統的執行及使用績效。 / Persnoal risk managment is a systematic approach for designing and managingpersonal or family security plans to control the risks of health and financiallosses. Enrolling in some personal insurance program is the most popular me-thod adopted by people for risk and financial management.The decision problemsand operational processes related to both sides of providers and consumers inthe personal insurance industry include requirment analysis and productselection for the customers and marketing, underwriting, actuarial, constractadministration, claims processing, and financial investment for the insurancecompanies.To carry out these procedures and solve the target problems effici-ently and effectively require the proper integration and process of associateddata, model, and knowledge. 　　The goal of this paper is to propose an integrated process for personalrisk management while takes into account both functions and interactions ofinsurance provid ers and customers, as well as to present a conceptual expertdecision support system architecture for guiding the system design andimplementation to satisfy various informationand decision needs from bothparties. Also provided in this paper is a software integration approachfor constructing a prototyped system focusing on personal insurance policyselection. Hypermedia concept and technology is used for informationsystem performances.

傳統的資產負債管理(Asset-Liability Management，ALM)研究大多強調數量分析方法，並未考慮資料來源的問題。然而在銀行實務上，資產負債管理人員卻必須根據現有內外部資料來釐定資產負債組合的整体政策。在決策支援系統中，模式整合的功能包含模式之組合及連結等，可用以整合數量分析模式與相關資料。本研究運用人工智慧技術來探討資產負債管理中模式整合之問題。藉此可以明瞭ALM的分析流程，以作為銀行人員訓練之參考。另一方面由於應用黑板架構發展系統，也可以提供一個有彈性的整合環境，以反應使用者需求及資料異動狀況，亦可彈性新增、刪除及修改模式整合過程中的資料結構與知識內涵，以為未來連接理論技巧與實務環境之參考。 / The computer support for Asset Liability Management (ALM) in the literature emphasizes on the mathematical analysis and does not address the data source problems. In the practical banking environment, however, ALM decisions are made based on the dynamic internal and external data changes. Therefore, an ideal ALM decision support system has to consider the integration of data sources and mathematical analysis. Traditional Decision Support Systems (DSS) rely on the expert's assistance to understand the problem and formulate or integrate appropriate models. There is a growing recognition that incorporates Artificial Intelligence techniques (Al) into the DSS can enhance the acceptance of these decision aids by management. 　　This paper intends to develop an Intelligent Decision Support System (TDSS) and addresses the model integration concept for the ALM. In the paper, model integration is defined as a series of processes from which important decision making information is inferred through automatic data model mapping and mathematical model conversion. The investigation of model integration concept helps the ALM analysis process understanding which can be useful for baaldng personnel training. On the other hand, the IDSS provides a flexible integration environment in which the system can flexibly response to the user's analysis request with the updated data situations. Since the blackboard architecture used for the system development supports the modularization structure, its inherent maintainability aLows a flexible update of the domain knowledge and data structure, and can therefore serve as a testbed to evaluate the potential integration approaches of various ALM data and mathematical models.

智慧型決策支援系統(Intellignet Decision Support Systems)的特點是可以同時處理定性和定量資料於同一個系統中，以同時執行各種知識推論及數量模式之運算。黑板架構(Blackboard Architecture)的做法是將決策支援求解過程的資料、模式和知識運用情形記錄於一共同工作區─稱之為黑板(Blackboard)，將模式及知識記錄在所謂的知識源(Knowledge Sources)中，並提供較有彈性之控制機制，應可提供較佳的解釋功能。以黑板架構為基礎的智慧型系統多應用在科學及工程方面，在管理方面卻寥寥無幾；管理問題多半屬於半結構性或非結構性，良好的解釋應為智慧型決策系統之重要功能。本研究擬就銀行業之授信審查做為本系統之專業領域知識(Domain Knowledge)，運用黑板架構中的階層化問題表現方式及模組化知識源分類之特性，建立提供完善解釋功能之智慧型授信決策支援系統。 / Incorporating artificial intelligence (AI) technique is critical to improve the functionality of decision support systems. Explanation function for consultation-based systems has been emphasized in the literature and should be considered important in developing intelligent decision support systems. Blackboard architecture can support a well-organized explanation facility due to its structurization of problem solving space, modularization of domain knowledge, and flexibility of reasoning control. Applying blackboard systems to managerial domain gets attention recently. Since most managerial consultation problems are unstructured or semi-structured, good explanation facility should be able to enhance the consultation effectiveness. The thesis investigates the potential of developing an explanation facility on the blackboard architecture using the loan evaluation as an example. During the interactive consultation process, the system can answer questions such as "What?", "Why?", "How?", and "Where?" with a friendly user interface. In terms of contribution, the inclusion of explanation facility can potentially increase the willingness and confidence of decision makers in using intelligent decision support systems. On the other hand, applying the graphic user interface to the development of explanation facility based on the blackboard architecture can make the reasoning process transparent and enhance the acceptance of this AI technique to managerial problem solving.

本研究以過去類似研究的發展經驗為基礎，參照國內企業界的特殊決策環境及決策型態，並考量行銷問題的特質，建立一套整合性行銷系統模擬架構( 以蒙特卡羅模擬法為基本架構，以行銷系統模式為核心 )，協助決策者評估╱選擇新產品上市時之最適競爭性行銷策略，以提高新產品上市後的成功率。本研究從決策者立場的角度來建構整個架構，採用「互動式漸進法」讓決策者能共同參與模式之建構，並透過「結構式詢問法」輸入資料卷協助決策者在問題答覆的過程中，將系統行為的隱性心智模式轉化成顯性數理模式，使本模擬架構能成為實用的電腦輔助工具，縮短行銷科學與行銷實務的距離。本研究在國內行銷實務及學術界中尚屬較新的嚐試， 希望能對國內企業界有實質的貢獻。本模擬架構，經簡易解析問題測試後，確認邏輯上具正確性及可行性。並以羽田公司小型轎跑車之新品牌－經典祥瑞－進行實例研究，實地瞭解羽田公司在評估╱選擇新品牌競爭性行銷策略的實務經驗，藉此細部調整系統模式及增益此架構之實用性。實例研究結果確認本模擬架構確可提供決策者完整的數量化決策資訊，作為決策者在其可容忍風險及行銷目標之考慮下，選擇最適行銷策略之決策參考。

產業的成熟與市場的飽和，使得產業的競爭變得愈來愈以成本和服務為導向，而激烈的市場競爭促使服務價格降低求存，以致物流業的服務素質及水準只能「將貨就價」，然而消費者意識的抬頭與服務科學的興起，使得服務品質的管理日益重要。因此，國際快遞物流企業要在提升服務及降低成本的驅動下，透過結合物流產業相關科技優勢與運用服務科學思維，找出顧客對產品及服務的喜好以增進服務效益，進而創新服務。 本研究以層級分析法(AHP)之操作步驟，找出對映客戶需求的四個服務品質構面及衡量構面的十二個準則，在建立一顧客喜好因素架構後，訪談某國際快遞物流前四十大客戶，以Expert Choice的整體階層不一致性判斷值(Overall Inconsistency Index, O.I.I)進行效度檢驗，通過一致性之問卷為32份。研究分析結果發現影響國際快遞物流顧客的喜好之準則，其權重依序是「誠實值得信賴」、「容易使用」及「遞送速度」，構面則以反應性及關懷性最為客戶所重視，並且從驚喜性構面發現，客戶在意的是持續性的改進與穩定的提供服務，而不喜歡沒有系統的改變與創新。在統計分析中，客戶重視程度離散度較大的有「遞送速度」及「誠實值得信賴」兩準則，顯示有特別重視此兩項因素之樣本群，而某些喜好因素間具有中度相關之關聯。 接著本研究為落實服務科學之思維與方法，將影響客戶喜好因素之架構結合決策支援系統，以決策支援系統的三個主要元件，資料庫、模式庫、對話管理提出概念設計，以重要性-績效矩陣(IPA)作為改善服務之排序參考，以及使用品質機能展開(QFD)作為在設計與創新服務的過程中納入客戶需求之方法；此外，也使用權重及客戶滿意度作為瞭解客戶對國際快遞物流服務之偏好程度及對方案之態度參考，使國際快遞物流企業能更有效率的提供滿足客戶個人偏好的服務。 / The maturity of industries and the saturation of markets make industrial competition more and more cost-oriented and service-oriented. To survive the keen market competition, the logistic industry has no choice but to reduce price, which leads to a lower level of service quality. With the uprising consumer awareness and service science, the management of service quality becomes more and more important. Driven by the need of higher service quality and lower cost, international logistic enterprises should combine relevant technical advantage and service science intellect to meet consumer demand, increase service efficiency, and innovate service. This research utilizes AHP method to create 4 service quality dimensions corresponding to customer demand and 12 criteria to measure these dimensions. After the establishment of customer preference framework, interview with 40 largest customer of a certain international logistic company and then examine the validity by the O.I.I. of Expert Choice. There are 32 questionnaires pass the consistency check. Analysis found that the weight of criteria which effect customer preference in sequence is “Integrity / trust worthiness”, “Easy to use”, and “speed of delivery”. As to dimensions, customers value “Respond” and “ Understand me” most. From the “Surprise” dimension we found customer need continuous improvement and steady service. Unsystematic changes and innovates are not preferred. In statistic analysis, “Speed of delivery” and “Integrity / trust worthiness” two dimensions have greater level of scatter on customer emphasis, which indicates there are some samples have special emphasis on these two factors and some factors have mid-level correlation. To practice the intellect and method of service science, this research combines the framework of factors that affect customer preference and decision support system. Concept designed by the 3 main part of a DSS : Database, Model base, and Dialog management, use IPA as the reference of service sequence improvement, and utilize QFD to bring in customer demand in the design and innovation of service. In addition, use weight and customer satisfaction as refer to understand international logistic service preference level and attitude toward programs. To bring more efficient and customer preference satisfied services.

各國政府為提高國際競爭優勢，紛紛積極推動「電子化政府」。我國電子化政府建設自八十六年起開始推動，迄今已經行政院擴大為e-Taiwan計畫。電子化政府推動之業務電腦化，帶動政府業務資訊系統的快速發展，其彙集而成之大型資料庫，為政府統計工作帶來莫大的發展契機。 本研究從電子化政府的過程、內政業務行政程序、知識挖掘及採勘方法，提出參考資料模型，可能的統計軟體工具以及電子化政府中知識發現的實驗架構。再者，本研究藉臺閩地區外籍與大陸配偶結婚登記資料集，運用各種群集分析如K-means、ANN、TwoStep等，並利用我國人口數時間序列採用多模式方法進行人口預測，並將前述分析結果回饋資料庫，最後，作者實現一個知識發現系統雛型，其中包含了前端資料庫、資料集、知識庫以及EIS使用介面。 本研究成果總結如下：(1)資料挖掘工作產出之知識，除真實呈現社會現象外，亦作為政府政策之指南；(2)在本研究發展之系統中，新興資料挖掘技術及傳統資料分析方法，二者相輔相成；(3)某些資料挖掘技術適合相符的資料型態，例如文中人口預測資料較適合指數平滑法勝於ANN，亦即，我們可以籍由多模式分析比較其結果，來達到更佳的效果；(4)藉由知識庫模型的建立達成知識創造、共享與管理的目標；(5)資料挖掘工作可以回饋改善資訊系統或業務缺失。 / In order to enhance international competitive advantages, most of the government authorities over the world are engaging in realizing their e-Government platforms. The ROC Government began to develope its e-Government- Infrastructure since 1997, and up-to-date is expanding the e-Taiwan Project as a whole by Executive Yuan. The computerization of administration processes within various government agencies push forward fast development of administration information systems via handling administrative works and lead to utmost opportunities for the government statistics by means of very large databases. Starting from a survey on developements of e-Government, administrative processes for interior affairs, and knowledge mining as well as discovery techniques, this study brings out reference data models, potential statistical softwaretools, and an experimental framework as a whole for knowledge discovery in the context of e-Government. In the next step, this study experiments with applying clustering techniques such as K-means, ANN, and Twostep on datamart regarding marriage of foreigners ( including citizens from Mainland China ) in Taiwan, and with employeeing multi-modes approach on population forecasting. The results of aforementioned analysises are feed into backend database. At last, this author carries out a prototype of knowledge discovery system which includes front-end data base, data marts, knowledge base and interfaces to EIS. The results of the research can be summarized as following: 1.Knowledge derived by means of data mining is capable to represent social events / affairs as well as to serve as a kind of guideline for developing government ploicies. 2. The modern data-ming techniques and classical data-analysis approaches complement with each other in the system developed in this research. 3. Certain mining technique is suitable of corresponding data pattern, for example, expotential smoothing is more suitable for our population data than ANN, which means that we may often achieve better result by multi-mode analysis and comprison with the outputs of different modes. 4. Knowledge creation, sharing, and management can be achieved by means of the knowledge discovery processes on the framework developed in this research. 5. We can figure out errorful raw data in the mining output and feedback to the data source to improve its quality.

KPI(Key Performance Index)是一個落後指標，需要一套更及時的領先指標，以動態和系統化的角度，及時展現每一位員工的執行績效和顧客滿意度指標，以數位化看板的概念報導員工對公司的貢獻度和顧客對服務的接受度，因為預先管控和報導，可以確保KPI 的達成，在服務品質的改善和顧客滿意度提升，有很大的助益。. 本研究希望發展出一套具體的線上及時管控指標，讓系統整合公司可以提升顧客信賴和持續服務品質改善，而將重點發展方向轉移到提供更好的內容、產品、服務、系統的品質，以及合理的價格。 因此採用平衡計分卡的四大構面為面向，ITIL服務生命週期之IT服務管理為主軸，參考PZB三位教授之服務品質概念性模式和SERVQUAL量表衡量構面及項目，配合系統整合公司的運作，歸納出一個服務品質改善架構流程圖，並以其為基礎發展一套服務品質改善的及時管控指標；運用商業智慧、數位儀表版等工具設計以支援主管決策管控和員工績效的報導系統。