知識資源是組織競爭優勢的重要來源，而專業服務業則是知識經濟中知識型企業的類型之一，其知識資源的運作是值得深入探討的問題。本研究以組織能力的角度觀察知識整合與維持，探討專業服務業知識整合與組織能力的關係，分析其知識整合與知識維持的模式，以及影響知識整合與知識維持模式之因素。 研究採用個案研究方法，透過資料文獻的收集整理，以及四家個案公司的深度訪談分析，主要得到以下的研究發現。 一、專業服務業的知識整合模式 知識資源整合模式由「整合層次」、「整合機制」、「組織文化」三者觀察，共有三種類型。 1.「有機多元團隊模式」採跨部門整合，組織文化偏有機式。對話溝通與共同語言使用頻繁，專業個人機制常與例規的搭配。跨部門層次知識整合機制非常多元，共同會議具有重要地位，團隊由T型人員擔任整合者角色。 2.「機械流程模式」採跨部門整合，組織文化偏機械式。部門間少有對話溝通，有清楚的工作規則與作業準則。跨部門層次知識整合機制以流程的整合機制為主導。 3.「專業個人主導模式」採部門內整合，具有有機式的組織文化。個人層次的專業個人判斷是完成組織任務的關鍵，專業共同語言體系複雜，對話溝通主要是資訊交流，非任務決策的討論。 二、組織能力任務知識特性與知識整合模式的關係 專業服務業中，組織能力的任務知識特性不同，知識整合模式亦不同。當任務知識複雜性高、內隱性高時，採用「有機多元團隊模式」。當任務知識複雜性高、內隱性低時，採用「機械流程模式」。當任務知識複雜性低、內隱性高時，則採用「專業個人主導模式」。 三、專業服務業的知識維持模式 組織能力的知識資源維持模式可以由「減少依賴策略」、「減少不確定策略」二者觀察，共有三種類型。 1.「知識擴散模式」透過工作過程中的知識交流，以及教育訓練或師徒制的傳承制度，使得知識能擴散開來。不同類型專家各自參與部分任務，透過團隊默契的建立與組織認同，使得知識能夠長期累積與彈性運用。 2.「知識外化模式」將完成任務的主要知識不斷地有系統地紀錄下來，使組織能降低因員工離去而帶走知識的風險。 3.「知識穩定模式」則是組織提供良好的工作環境以及有吸引力的報酬制度，使得關鍵員工願意繼續留在組織中。組織並會致力於專業知識分享之機制，使其減少對少數關鍵專業員工的依賴程度。 四、組織能力任務知識特性與知識維持模式的關係 專業服務業中，組織能力的任務知識特性不同，組織能力的知識維持模式亦不同。當任務知識複雜性高、內隱性高時，採用「知識擴散模式」。當任務知識複雜性高、內隱性低時，採用「知識外化模式」。當任務知識複雜性低、內隱性高時，則是採用「知識穩定模式」。

網際網路蓬勃發展，使得全球創新種子不斷地萌芽，個人或公司可以運用自身的知識能力，透過網際網路，將創新成果呈現在大眾的面前，創造出極高的創新價值。進一步分析網際網路創新的產生，會發現網路上任何創意都必須透過網路技術來加以實現，因此本研究探討組織如何整合技術合創意，結合不同專業的知識，產生創新價值。 本研究從知識管理的理論基礎出發，以台灣兩大搜尋引擎蕃薯藤、奇摩推薦網站以及專業評估選網站”人間煙火”評選的中文推薦網站為研究對象，挑選出台灣經營網路事業具代表性的公司，嘗試從成功企業的經營模式中歸納出台灣網路事業的創新類型以及公司在知識整合機制上的作法。研究發現： 一、網站創新類型可分為漸進式創新與跳躍式創新 二、知識特性不同，公司採用之創新類型不同，知識異質度高，網路創新傾向採用跳躍式創新，知識異質地低，網站創新傾向採用漸進式創新。 三、網站創新所需的知識特性不同，公司所採用的知識整合機制不同 3-1 網站企業所需的知識整合機制包括方向／目標、順序／流程、例規、共同語言、多元專業個人、對話／開會，區分為組織機制、介面溝通機制、多元專業個人機制、團隊運作機制四種類型。 3-2 網站創新所需的知識複雜度高，且知識異質度高，組織傾向採用介面溝通機制、多元專業個人機制與團隊運作機制整合不同專業的知識，介面溝通機制複雜度較高。 3-3 網站創新所需的知識複雜度高，且知識異質度低，組織傾向採用多元專業個人機制與組織機制整合不同專業的知識。 3-4 網站創新所需的知識複雜度低，且知識異質度高，組織傾向採用團隊運作機制與組織機制整合不同專業的知識。 3-5 網站創新所需的知識複雜度低，且知識異質度低，組織傾向採用多元專業個人機制與介面溝通機制整合不同專業的知識，介面溝通機制複雜度較低。 / The relationship between knowledge integration and innovation on the World Wide Web -By Ruo-Jun WUAdvisor: Dr. Se-Hwa WuKeywords: Internet innovation, knowledge heterology, Knowledge integration , mechanisms of knowledge integration 1. Background Internet industry grows rapidly. According the Internet report of Mogan Stanley company, new businesses that are created by or for Internet marketplace will grow very rapidly, at an estimated CAGR of 38% from now until ths year 2000. One of the important factor in the Internet's on-going growth is that there are many original innovations in the Internet. One person or a small company can create high innovative value by their own knowledge through the World Wide Web. Innovation becomes an important ubject i2. Purpose According to the research background ,the research objective of this study are four points: (1) To find the innovation on the World Wide Web and the categorization of innovation on the World Wide Web.(2) To explore the characteristic of knowledge with the innovation on the World Wide Web. (3) To explore the relationship between the characteristic of knowledge and categorization of innovation. (4) To explore the relationship between the characteristic of knowledge and the mechanism of integration knowledge?3. Conceptual FrameworkThe literature on organization knowledge and learning has explored the role of organizations in the acquisition, processing, storage, and application of knowledge(Argyris and Schon 1978,Levitt and March 1988,Ribertwon and Swan and Newell 1996). Demsetz(1991) proposes that efficiency in the acquisition of knowledge requires that individuals specialize in specific areas of knowledge, while the application of knowledge to produce goods and services requires the bringing together of many areas of specialized kGrant's(1996) observations of mechanism of integrating knowledge imply that the difference of knowledge characteristic will influence the method of knowledge management and Lyles and Zander(1992) propose the structure of organization knowledge would play an important role in searching the strategic opportunity. Based on the literature review in the preview paragraph, this study proposes the following framework (shown in figure 1), which is made up of two dimensions: knowledge heterology and knowledge complexity as the variables and in order to discussing the company how to integrate different individual's knowledge and to produce innovation on the World Wide Web. 4. MethodologyThe data were collected through research in both primary and secondary sources. Primary data were then collected about the web site project by contacting directly one of the members of web site team and requesting an interview. Search engine is considered the representative product in the Internet and so six project was picked through the recommendation of search engine to show the operation of successful companies on the World Wide Web5. Conclusion(1) The categorization of innovation in Internet industry included incremental innovation and radical innovation. (2) Organizations are more likely to adopt incremental innovation when the degree of knowledge heterology is low and adopt radical innovation when the degree of knowledge heterology is high. (3) Organization will take different mechanism to integrate knowledge when the characteristic of knowledge with Web innovation is different. 3.1 Organizations take "Rules and Directives, Routines, Sequencing, problem solving, dialogue/meeting, multiskilled individual " as the mechanism of integrating knowledge. These mechanisms can be categorized by four mechanism patterns-Organization mechanism, Team mechanism, Individual mechanism and Communication mechanism. 3.2 Organizations will take Team mechanism, Individual mechanism and Communication mechanism, when the degree of knowledge complexity is high and the degree of knowledge heterology is high. The degree of common language is more complex. 3.3 Organizations will take Organization mechanism and Team mechanism, when the degree of knowledge complexity is low and the degree of knowledge heterology is high. 3.4 Organizations will take Organization mechanism and ndividual mechanism, when the degree of knowledge omplexity is high and the degree of knowledge heterology is low. 3.5 Organizations will take Individual mechanism and Communication mechanism, when the degree of knowledge complexity is low and the degree of knowledge heterology is low. The degree of common language is less complex.

在持續創新的需求下，跨公司合作已成為企業整合應用知識，創新求變的重要策略。本文融合知識基礎觀點和組織學習觀點，指出跨公司合作所帶來的組織創新績效，係因合作夥伴知識整合的結果。因此研究的目的除了要實證知識整合與組織創新績效的關係外，主要在發展一個理論架構，說明影響跨公司合作創新的因素，及這些因素之間的關係。在研究設計上，本文係以我國高科技產業、資訊服務業及金融服務業做為問卷調查的對象，將所收集的資料透過探索性分析與驗證性分析兩階段檢定本文所提出之量測模式與研究假說，結果得到下列結論： 1. 跨公司合作為企業所帶來的創新績效，可以用知識整合的觀點來解釋，當企業知識整合能力越好，跨公司合作創新績效會越好。 2. 知識整合能力受到企業知識吸收能力的影響，吸收能力係企業先前知識的蓄積量，以及應用這些知識的能力之綜合。 3. 知識整合能力亦受到企業與夥伴合作的能力之影響，合作能力包括企業與夥伴建立信任關係，以及溝通、協調的能力。 4. 知識特質受知識整合機制的中介而影響創新績效，跨公司合作所帶來組織的創新績效，主要不受合作所牽涉知識之外顯╱內隱與複雜性特質的影響，必須應知識特質的不同而採取適當的整合機制後，才能因知識整合而產生創新績效。 5. 吸收能力、合作能力與知識整合機制是相互影響的因素，三者形成企業知識整合創新能力的主要構面，是企業追求跨公司合作創新必須重視的要素。 / Inter-firm collaboration has been an important strategy for firms to integrate and apply knowledge among their partners in order to obtain innovation performance under uncertainty circumstances. This study combining the knowledge based view and the organizational learning perspective, considers the innovation performance improvement as the result of knowledge integration. Besides examining the relation between innovation performance and knowledge integration, the purpose of this study is to find the factors influencing inter-firm collaboration performance and the relationships among these factors. The data collecting from Taiwan’s high-tech, information service and finance industry were used in the exploratory and confirmatory phases to evaluate the instruments and test the hypotheses. The conclusions are listed as below: 1. The innovation performance gaining from inter-firm collaboration can be considered as the result of knowledge integration. While the knowledge integration capability of a firm is better, the firm’s innovation performance in inter-firm collaborations will be better too. 2. The knowledge integration capability of a firm is influenced by the absorptive capacity of the firm. And the firm’s absorptive capacity derives from the firm’s prior knowledge accumulation and the capability to apply their knowledge. 3. The knowledge integration capability of a firm is also influenced by their cooperative competency. The cooperative competency is composed of three interrelated facets: trust, communication and coordination. 4. Firm’s innovation performance in an inter-firm collaboration doesn’t directly influenced by the explicit/tacit and complexity characteristics of the knowledge which appeared in the collaboration. To produce innovation performance, knowledge with different characteristics should be integrated by suitable integration mechanisms. 5. Absorptive capacity, corporative competency and knowledge integration mechanism construct firm’s “knowledge integration and innovation capability”, which is important to firm’s innovation performance in inter-firm collaborations.

依財政部保險司每半年對壽險申訴案件的統計觀察，客戶對壽險公司提出申訴的件數有逐年遞增的趨勢，申訴原因多為理賠給付、契約保全服務、業務員招攬、保費收費糾紛、商品條款及法規等爭議。客服員若能於第一時間以專業的知識回應申訴問題，勢必可減少申訴數量。但面對浩瀚的壽險各領域知識，客服中心的成員不易具備所有足以應付客戶問題的知識，實施知識管理將組織內各種知識公開化、標準化、制度化、科技化，已成為刻不容緩的任務。 為解決壽險客服中心因取得壽險專業知識的障礙而無法提供客戶滿意的服務，本研究對客服中心可能應用的各種知識，探討已被發表的知識管理分類、呈現與檢索等應用的相關技術，提出符合客服中心需求的以知識本體為基礎的壽險知識問題檢索架構，除了提供壽險專業知識的建立、搜尋、分享環境，並將原始文件儲存為XML或RDF的語意文件，做為將來跨平台與跨應用系統資料交換的基礎，提升客服中心服務效率、節省客服人力與行政成本，留住忠誠的客戶以達成CRM的目的，進而提升企業競爭力。 / According to the regular semi-annual statistic report from Insurance Department of MOF Taiwan, the complain cases from policy owners are increasing year by year. The reasons of complain are claims, underwriting, policy services, marketing, premium collections, policy clauses and regulations. If the customer service representatives (CSR) could solve the problems at the right time with their domain knowledge of life insurance, the volumes of complain should be descended explicitly. But it is hard to ask a CSR to play the role with variety domain knowledge of life insurance. Implement the knowledge management mechanism to standardize and enrich the organization memory are the first priority in life insurance companies. In order to overcome the barrier of dissatisfaction about customer service, this research try to study the related theories and technologies of knowledge classification, knowledge representation, knowledge acquisition tools, inference and problem solving methods. The results of this research announce an architecture of ontology based customer relationship management for Life Insurance Company to build, represent, search, and share the life insurance domain knowledge. Addition, to save the original semi-structured or unstructured documents into semantic formats of XML or RDF. It could provides the data exchange between heterogeneous databases and platforms. The advantages are more efficiency and cost down for the customer service departments, retain the royalty customers and get more competence advantage for the company.

隨著知識經濟時代的來臨，掌握知識可幫助組織提昇其競爭力，因此對於知識的產生、儲存、應用和整合，已成為熱烈討論的議題，本研究針對知識整合議題進行探討；而在知識呈現方式中，決策樹（Decision Tree）形式知識為樹狀結構，可以用圖形化的方式來呈現，它的結構簡單且易於瞭解，本研究針對決策樹形式知識來探討其知識整合的課題。 本研究首先提出一個合併選擇決策樹方法MODT（Merging Optional Decision Tree），主要是在原始決策樹結構中增加一個選擇連結（Option Link），來結合具有相同祖先（Ancestor）的兩個子樹；而結合方式是以兩兩合併的方式，由上而下比對兩棵決策樹的節點（Node），利用接枝（Grafting）技術來結合兩棵樹的知識。再者利用強態法則（Strong Pattern Rule）概念來提昇合併樹的預測能力。 其次，由於MODT方法在合併兩棵不同根節點的決策樹時，會形成環狀連結的情形而破壞了原有的樹形結構，以及新增的選擇連結會增加儲存空間且不易維護，因此本研究提出決策樹合併修剪方法DTBMPA（Decision-Tree-Based Merging-Pruning Approach）方法，來改善MODT方法的問題，並且增加修剪程序來簡化合併樹。此方法包括三個主要程序：決策樹合併、合併樹修剪和決策樹驗證。其做法是先將兩棵原始樹經由合併程序結合成一棵合併樹，再透過修剪程序產生修剪樹，最後由驗證程序來評估修剪樹的準確度。本研究提出的DTBMPA方法藉由合併程序來擴大樹的知識，再利用修剪程序來取得更精簡的合併樹。 本研究利用實際信用卡客戶的信用資料來進行驗證。在MODT方法的實驗上，合併樹的準確度同時大於或等於兩棵原始樹的比例為79.5%；並且針對兩者的準確度進行統計檢定，我們發現合併樹的準確度是有顯著大於原始樹。而在DTBMPA方法的實驗中，合併樹的準確度優於原始一棵樹的比率有90%，而修剪樹的準確度大於或等於合併樹的比率有80%。在統計檢定中，合併樹和修剪樹的準確度優於一棵樹的準確度達顯著差異。且修剪樹的節點數較合併樹的節點數平均減少約15%。綜合上述，本研究所提之MODT方法和DTBMPA方法皆能使得合併樹的準確度優於一棵樹的準確度，而其中DTBMPA方法可以取得更精簡的合併樹。 此外，就決策樹形式知識整合的應用而言，本研究提出一個決策樹形式知識發掘預測系統架構，其主要的目在於提供一個Web-Based的知識發掘預測系統，以輔助企業進行知識學習、知識儲存、知識整合、知識流通和知識應用等知識管理的功能。期能藉由使用這套系統來發掘企業內部隱含的重要知識，並運用此發掘的知識進行分類和預測工作。它包含三個主要子系統，即知識學習子系統、合併決策樹子系統和線上預測子系統，其中合併決策樹子系統就是應用本研究所提出之決策樹形式知識整合方法來進行知識整合處理。 有關後續研究方面，可針對下列議題進行研究： 一、就決策樹形式知識整合架構中，探討決策樹形式知識清理單元，即前置處理部份的功能設計，期能讓合併樹結合有一定質量的決策樹形式知識。 二、就綜合多個預測值部份，可加入模糊邏輯理論，處理判定結果值之灰色地帶，以提昇合併樹的預測準確度。 三、就決策樹本身而言，可進一步探討結合選取多個屬性來進行往下分群的決策樹。針對分類性屬性的分支數目不同或可能值不同時的合併處理方法；以及數值性屬性選取不同的分割點時的合併處理方法。 四、探討分類性屬性的分支數目不同或可能值不同時之合併處理方法，以及數值性屬性選取不同的分割點時之合併處理方法。 五、對於合併樹的修剪方法，可考量利用額外修剪例子集來進行修剪的處理方法，並比較不同修剪法之修剪效果及準確度評估。 六、探討多次合併修剪後的決策樹之重整課題，期能藉由調整樹形結構來提昇其使用時的運作效率，且期能讓合併樹順應環境變化而進行其知識調整，並進一步觀察合併樹的樹形結構之變化情形。 七、就實際應用而言，可與廠商合作來建置決策樹形式知識發掘預測系統，配合該廠商的產業特性及業務需求來設計此系統，並導入此系統於企業內部的營運，期能藉此累積該企業的知識且輔助管理者決策的制定。 / In the knowledge economy era, mastering knowledge can improve organization competitive abilities. Therefore, knowledge creation, retention, application, and integration are becoming the hottest themes for discussion nowadays. Our research focuses on the discussion of knowledge integration and related subjects. Decision trees are one of the most common methods of knowledge representation. They show knowledge structure in a tree-shaped graph. Decision trees are simple and easily understood; thus we focus on decision-tree-based knowledge in connection with the theme of knowledge integration. First, this research proposes a method called MODT (Merging Optional Decision Tree), which merges two knowledge trees at once and adds an optional link to merge nodes which have the same ancestor. In MODT, we compare the corresponding nodes of two trees using the top-down traversal method. When their nodes are the same, we recount the number of samples and recalculate the degree of purity. When their nodes are not the same, we add the node of the second tree and its descendants to the first tree by the grafting technique. This yields a completely merged decision tree. The Strong Pattern Rule is used to strengthen the forecast accuracy during the merged decision trees. Secondly, when we use the MODT method to merge two trees which have different roots, the merged tree has cyclic link in the root. It makes the merged tree not a tree structure, so we propose another approach called DTBMPA (Decision-Tree-Based Merging-Pruning Approach) to solve this problem. There are three steps in this approach. In the merging step, the first step, two primitive decision trees are merged as a merged tree to enlarge the knowledge of primitive trees. In the pruning step, the second step, the merged tree from the first step is pruned as a pruned tree to cut off the bias branches of the merged tree. In the validating step, the last step, the performance of the pruned tree from the second step is validated. We took real credit card user data as our sample data. In the MODT experiments, the merged trees showed a 79.5% chance of being equal or more accurate than the primitive trees. This research result supports our proposition that the merged decision tree method could achieve a better outcome with regard to knowledge integration and accumulation. In the DTBMPA simulation experiments, the percentage accuracy for the merged tree will have 90% of chance that is greater than or equal to the accuracy for those primitive trees, and the percentage accuracy for the pruned tree will have 80% of chance that is greater than or equal to the accuracy for merged tree. And we also find that the average number of nodes of the pruned tree will have 15% less than that of the merged tree. Eventually, our MODT and DTBMPA methods can improve the accuracy of the merged tree, and the DTBMPA method can produced smaller merged tree. Finally, in respect to the application of the Decision-Tree-Based Knowledge Integration, this research proposes an on-line Decision-Tree-Based knowledge discovery and predictive system architecture. It can aid businesses to discover their knowledge, store their knowledge, integrate their knowledge, and apply their knowledge to make decisions. It contains three components, including knowledge learning system, decision-tree merging system, and on-line predictive system. And we use the DTBMPA method to design the decision-tree merging system. Future directions of research are as follows. 1.Discussing the Decision-Tree preprocessing process in our Decision-Tree-Based Knowledge Integration Architecture. 2.Using the fuzzy theory to improve the accuracy of the merged tree when combining multiple predictions. 3.Discussing the merge of the complicated decision trees which are model trees, linear decision trees, oblique decision trees, regression trees, or fuzzy trees. 4.Discussing the process to merge two trees which have different possible values of non-numeric attributes or have different cut points of numeric attributes. 5.Comparing the performance of other pruning methods with ours. 6.Discussing the reconstruction of the merged trees after merging many new trees, discussing the adaptation of the merged trees to the changing environment, and observation of the evolution of the merged trees which are produced in different time stamp 7.Implementation of the on-line Decision-Tree-Based knowledge discovery in a real business environment.

Peter Drucker於1993 年在其著作中指出，在新的經濟體系裡，知識並不是和人力、資本或土地等並列為製造資源之一，而是唯一有意義的一項資源，在一個以知識為基礎的社會裡，最根本的經濟資源，不再是資本或自然資源，也不再是勞力，取而代之的是知識。既然知識是最重要的一項資產，企業就應該花更多的時間來管理知識，才能為企業帶來創新並創造價值。因此企業如何有效的創造和應用知識，就成為經營管理的主要手段（Soo & Park,1999）。而知識也逐漸被視為一種策略性的資產，知識的取得、整合、儲存、分享和應用為企業建立競爭優勢的必備能力（Zack 1999）。 Grant (1996)進一步提出知識基礎理論，他認為動態競爭環境的成功的要訣，就是將組織能力視為一種知識整合之方法，並且認為知識是組織最重要的策略性資源。不管是任何產品，無形或是有形的產品其背後的基礎都是知識智慧的累積，因此以知識為基礎的創新，是決定企業成功的關鍵因素。 本研究嘗試從知識基礎論的角度出發來探討在不同的創新類型之間，應採用何種的知識流通模式與知識整合機制較容易成功，研究方法採用質性研究之個案訪談法，研究對象為知識密集產業，總共訪談了八位高階主管，並將之整理成四個個案，經由分析歸納後得到以下幾點結論。 一、技術創新所需的知識屬性偏向於專屬性高；管理創新所需的知識屬性偏向於內隱性低。 二、知識屬性會影響創新過程中的知識取得與流通模式。當知識屬性為路徑相依性高時，組織的知識與流通傾向於採用內部自行發展；當知識屬性為路徑相依性低時，組織的知識與流通傾向於採用外部知識來源。 三、知識的取得與流通模式並不會對創新類型造成顯著影響，這是因為知識的取得與流通若要對企業創新造成進一步的影響，尚須配合組織本身的吸收與整合機制以及組織內部知識創造的過程，才能有效的進行企業創新。 四、創新類型與知識屬性會影響創新過程中的知識吸收與整合。當創新類型為技術創新，知識屬性為內隱性高、專屬性高時，組織的知識吸收與整合機制傾向於採用多方面的模式，包括了個人知識整合、團隊交流與文件化；當創新類型為管理創新，知識屬性為內隱性低時，組織的知識吸收與整合機制傾向於採用單方面的模式，而且多為團隊交流。 五、企業所擁有的互補性資產越高越有利於創新，從個案中發現企業若擁有良好的互補性資產，則在取得知識後，越能快速的進行企業創新。 六、不同的創新為企業所帶來的效益也不同，研究發現技術創新（產品創新與製程創新）為企業所帶來的效益通常是局部的；而管理創新（組織創新與策略創新）為企業所帶來的效益通常是全面的。 / Peter Drucker refer to knowledge, not compare with manufacturing resource such as labor or capital or land, is the only meaningful resource in new economy system in his writings in 1993.The fundamental economic resource in knowledge based society is not capital or natural resource or labor but knowledge. The enterprise should spend more time to manage knowledge since knowledge is the most important assets. Thus knowledge could bring innovation and create value for enterprise. Therefore, how to create and apply knowledge effectively has become a major issue for business administration（Soo & Park,1999）. The knowledge has been regard as a strategic asset gradually. The acquisition, integration, accumulation and diffusion of knowledge is a necessary capability of enterprise to build competitive advantage. Grant refer to knowledge based theory further in 1996.He consider the successful method in dynamic competitive environment is to regard organization capability as a method of knowledge integration and knowledge is the most important strategic resource of organization. The fundamental of all product, visible or invisible, is the accumulation of wisdom. Therefore, the knowledge-based innovation is the critical point of enterprise’s success. This thesis try to discuss what kind of knowledge-diffusion model and knowledge-integration model would easily success in different innovation type from knowledge-based theory. The research methodology is case study of quality method and research target is knowledge intensive industry. The research has interviewed eight managers and concluded four case. Finally, we have some conclusion below : 1. The knowledge of technical innovation is partial to high specificity； the knowledge of managerial innovation is partial to low tacit. 2. The character of knowledge would influence knowledge acquisition and flow model. When character of knowledge is partial to high path dependent, the knowledge acquisition and flow model is partial to develop by enterprise itself；When character of knowledge is partial to low path dependent, the knowledge acquisition and flow model is partial to acquire from outside. 3. The knowledge acquisition and flow model would not influence innovation type obviously. If knowledge acquisition and flow model would influence innovation type obviously, it should match up with organization’s absorptive and integrative mechanism. 4. The innovation type and knowledge character would influence knowledge absorption and integration during innovation process. When innovation type is partial to technical innovation and knowledge character is partial to high tacit and high specificity, then organization’s absorption and integrative mechanism will be partial to adopt all-around methods, include personal knowledge integration, organizational communication and documentlization. When innovation type is partial to managerial innovation and knowledge character is partial to low tacit, then organization’s absorption and integrative mechanism will be partial to adopt one-way method, such as organizational communication. 5. The more complementary assets enterprise have, the easier enterprise to innovate. If enterprise have higher complementary assets, then they could proceed innovation immediately after acquire knowledge. 6. The different types of innovation bring different benefit to enterprise. We find technical innovation（product innovation and process innovation）bring partial benefit to enterprise, and managerial innovation （organizational innovation and strategic innovation）bring all-around benefit to enterprise.

在目前的企業環境中，很多企業致力於管理和應用組織知識，來維持他們的核心能力和創造競爭優勢。有效率的管理組織知識，能減少解決問題的時間和成本，並增加組織學習和創新能力。並且，由於累積知識資源的需求，很多企業開始發展知識庫，以儲存組織及個人的知識，用來增加組織整體的效率、支援日常的運作以及企業策略的操作。 知識管理是現代的典範，可用來有效管理組織知識，進而改善組織績效。知識管理的目的是強調管理知識的流動及流程。在知識管理流程方面，主要區分為知識擷取、整合、儲存/歸類、散播和應用知識等程序。另外，資訊技術可用來協助知識管理，並能使知識管理更有效率。知識管理的主要議題之ㄧ是知識的擷取，由於目前知識來源的提供，主要是透過知識工作者，可是它對於知識工作者而言，是一種額外的負擔。因此，設計一個有效的方法來自動產生組織知識，以減輕他們的額外負擔，將是一個很重要的課題。第二個相當重要的議題是知識整合，由於不同來源的知識，可能造成組織知識的衝突，因此設計一個知識整合方法，把不同來源的知識整合成一個完整的知識，組織將會逐漸增加這方面的需求。 分類在很多應用中是常遭遇的問題，例如財務預測、疾病診斷等。在過去，分類規則常藉由決策樹的方法所產生，並用於解決分類的問題。在本論文中，提出兩個以遺傳規劃為基礎的知識擷取方法和兩個以遺傳規劃為基礎的知識整合方法，分別支援知識管理流程中的知識擷取和知識整合。 在兩個所提的知識擷取方法中，第一個方法是著重在快速和容易地找到想要的分類樹，但是，此方法可能會產生結構較複雜的分類樹。第二個方法是修正第一個方法，產生一個較精簡和應用性高的分類樹。這些所獲得的分類樹，能被轉換成規則集合，並匯入知識庫中，幫助企業決策的制定和日常的運作。 此外，在兩個所提的知識整合方法中，第一個方法，能自動結合多重的知識來源成為一個整合的知識，並可匯入知識庫中，但是此方法只考慮到單一時間點的整合。第二個方法則是可以解決不同時間點的知識整合問題。另外，本論文提出三個新的遺傳運算子，在演化過程中，可用來解決規則集合中有重複、包含和衝突等常見的問題，因而可以產生較精簡及一致性高的分類規則。最後，本論文採用信用卡資料及乳癌資料來驗證所提方法的可行性，實驗結果皆獲得良好的成效。 / In today’s business environment, many enterprises make efforts in managing and applying organizational knowledge to sustain their core competence and create competitive advantage. The effective management of organizational knowledge can reduce the time and cost of solving problems, improve organizational performance, and increase organizational learning as well as innovative competence. Moreover, due to the need to accumulate knowledge resources, many enterprises have devoted to developing their knowledge repositories. These repositories store organizational and individual knowledge that are used to increase overall organization efficiency, support daily operations, and implement business strategies. Knowledge management (KM) is the modern paradigm for effective management of organizational knowledge to improve organizational performance. The intent of KM is to emphasize knowledge flows and the main process of acquisition, integration, storage/categorization, dissemination, and application. Furthermore, extant information technologies can provide a way of enabling more effective knowledge management. One of the important issues in knowledge management is knowledge acquisition. It is an extra burden for knowledge workers to contribute their knowledge into repositories, such that designing an effective method for abating an extra burden to automatically generate organizational knowledge will play a critical role in knowledge management. A second rather important issue in knowledge management is knowledge integration from different knowledge sources. Designing a knowledge-integration method to combine multiple knowledge sources will gradually become a necessity for enterprises. Classification problems, such as financial prediction and disease diagnosis, are often encountered in many applications. In the past, classification trees were often generated by decision-tree methods and commonly used to solve classification problems. In this dissertation, we propose two GP-based knowledge-acquisition methods and two GP-based knowledge-integration methods to support knowledge acquisition and knowledge integration respectively in the knowledge management processes for classification tasks. In the two proposed knowledge-acquisition methods, the first one is fast and easy to find the desired classification tree. It may, however, generate a complicated classification tree. The second method then further modifies the first method and produces a more concise and applicatory classification tree than the first one. The classification tree obtained can be transferred into a rule set, which can then be fed into a knowledge base to support decision making and facilitate daily operations. Furthermore, in the two proposed knowledge-integration methods, the former method can automatically combine multiple knowledge sources into one integrated knowledge base; nevertheless, it focuses on a single time point to deal with such knowledge-integration problems. The latter method then extends the former one to handle integrating situations properly with different time points. Additionally, three new genetic operators are designed in the evolving process to remove redundancy, subsumption and contradiction, thus producing more concise and consistent classification rules than those without using them. Finally, the proposed methods are applied to credit card data and breast cancer data for evaluating their effectiveness. They are also compared with several well-known classification methods. The experimental results show the good performance and feasibility of the proposed approaches.

近年來，許多公司面臨需要透過資訊科技來獲取競爭優勢。各產業對於資訊系統的要求越來愈多，促使資訊系統的開發工作越加複雜，而使得成功完成資訊系統的開發變的日益困難。 軟體工程協會指出軟體能力成熟度整合模式(Capability Maturity Model Integration, CMMI)強調軟體開發需要追求開發程序的改善與程序的最佳化。透過程序的改善以降低軟體開發專案失敗的機率。根據創意的定義，資訊系統開發程序的改善是團隊創意的表現。 目前少有研究從創意的觀點探討資訊系統開發程序的改善。根據社會認知理論指出效能信念是解釋行為/產出的關鍵元素。學者們也證明創意自我效能對於創意的重要性。到目前為止，效能與創意的連結僅限於個人層次的研究。因此，本研究將以資訊系統開發程序改善為研究情境，進行集體效能與創意文獻的連結，提出資訊系統開發團隊集體創意效能之概念，並探討集體創意效能的前置因素與了解干擾集體創意效能形成的因素。 本研究採用部分最小平方法 (Partial Least Squares)，分析98組開發資訊系統的學生團隊與61組開發資訊系統的業界團隊資料，以驗證研究模型。結果指出在學生團隊方面，團隊知識程度、成就動機、團隊知識整合能力會正向影響集體創意效能的形成；團隊互動程度會干擾團隊知識程度與集體創意效能的關係、專案複雜度會干擾團隊知識程度與集體創意效能的關係以及干擾團隊知識整合能力與集體創意效能的關係。在業界團隊方面，團隊知識程度、成就動機、團隊知識整合能力會正向影響集體創意效能的形成；團隊互動程度會干擾團隊知識程度與集體創意效能的關係、專案複雜度會干擾團隊知識程度與集體創意效能的關係、成就動機與集體創意效能的關係以及團隊知識整合能力與集體創意效能的關係。此外，本研究亦探討在不同專案複雜度的情境中，影響集體創意效能之前置因素。 / Numerous companies have recently employed information systems to obtain a competitive edge. The demand for many new and different information system (IS) applications has increased the scope and complexity of IS developing. Developing successful IS projects became difficult. Software Engineering Institute proposed Capability Maturity Model Integration (CMMI) that emphasized process optimization of software development. The improvement in software process can reduce the probability failure in development software. According to the definition of creativity, the improvement in software process is team creativity. However, there are few studies which discuss the issues about systems development process improvement from creative perspective. According to the social cognitive theory, efficacy is a key factor for interpreting behavior/products. Scholars demonstrated that creative self-efficacy is important to creativity. Previous researchers which studied the potential link between efficacy and creativity are focus on individual level. Thus, this study combined the literatures of collective efficacy and team creativity to propose a new construct (Collective creative efficacy, CCE) for information systems development teams, and explore the influences and moderators for CCE. 98 student project teams and 61 industry project teams are surveyed. Partial least squares (PLS) results demonstrate that team knowledge, achievement motivation and knowledge integration ability positively influenced CCE, team interaction positively moderated the relationships between team knowledge and CCE, and project complexity negatively moderated the relationships between team knowledge and CCE, and the relationships between knowledge integration capability and CCE in both samples. Project complexity positively moderated the relationships between achievement motivation and CCE in the model of industry project teams. An attempt is also made to understand the antecedents of CCE in different project complexity.

管理大師彼得。杜拉克(Peter F. Drucker)在1960年代即提出『知識工作』與『知識工作者』等觀點。之後，更在1993 年其著作-『後資本主義社會』（Post-Capitalist Society）當中表示，『我們正進入一個知識社會，在這個社會當中，基本的經濟資源將不再是資本(Capital)、自然資源(Natural Resources)或是勞力(Labor)，而將是知識，而知識員工將成為其中的主角』。 在知識經濟的年代，創造力比生產力重要，再加上，知識工作者所想要的是挑戰性較高的工作，所以喜歡在成功的團體中工作(Dick Dove,1998)。今日，許多由知識型工作者組成的知識型團隊紛紛出現，也是因為一個案子的成功已不太可能是只靠一人之人所達成，而是集眾人之力，因此，本研究以知識型團隊為主角，欲了解知識型團隊的運作的過程。 本研究嘗試想用左腦工作者與右腦工作者為出發點，想找出不同的知識工作者所組成的知識型團隊的團隊特性是否有差異？此外，這些差異是否會造成知識型團隊在選擇知識管理策略時選擇方向的不同？於是，想以成功團隊為例，試圖找出各個知識型團隊在團隊本質、創意特性、團隊特性與知識整合上的一般性，期望以知識管理為一架構，做一個重新的詮釋。 最後，經由「個案分析法」，本研究歸納出以下幾點結論： (1)、知識型團隊的特性可分為「團隊構成(知識異質性)」、「團隊的任務(任務模糊性)」與「相互關係」。「團隊的任務」與「相互關係」具有正相關，當團隊的任務模糊性高時，團隊成員與成員間相互關係自然緊密；若任務模糊性低，成員與成員間的互動會減少、互動方式只有垂直式互動為必須，互相依賴的程度也會變少，造成成員間的相互關係為鬆散。而不同知識型團隊因具有不同的團隊特性導致團隊「知識管理策略」產生不同的情形。 (2)、知識型團隊特性會影響團隊的知識管理策略。「知識依附的方式」、「知識儲存與協調的方式」、「知識整合模式」、「知識整合機制」與「整合者角色」與「團隊的任務(任務模糊性)」及「相互關係」的關聯性最強，與「團隊構成(知識異質性)」的關聯性最弱。 (3)、知識型團隊特性會影響團隊的知識管理策略。「知識整合機制」與「開展性與整合性思考時間比例」與「團隊的任務(任務模糊性)」及「相互關係」的關聯性最弱，與「團隊構成(知識異質性)」的關聯性最強。 (4)、「學習機制」、「整合者類型」與知識型團隊特性無關。 期望這幾點研究發現能對未來後續研究有任何啟發，並能對「知識管理」領域有些許貢獻。 / In 1960s, Peter F. Drucker was the first person who mentioned that “knowledge worker”. Afterward, he proposed that “now the society is a knowledge society. In knowledge society, the most important resource is not capital, natural resources and labor, but knowledge. Knowledge workers will become the main actors.” in “Post-Capitalist Society” in 1993. In knowledge economy era, creativity is more critical than productivity. Besides, knowledge workers want to work in more challenge environment, therefore, they want to work for successful teams. (Dick Dove, 1998) Nowadays, many knowledge teams emerge, because one project could not succeed by only one man’s effort. Therefore, knowledge team was selected as main actor in this investigation. In addition, it uses different types of knowledge workers as starting point in this work. It hopes to find some connections between “knowledge team’s characteristics” and “knowledge management strategies”. Also, it uses “case study method” to develop and summarize primary and secondary materials in this investigation. The aim of this study is as the follow: (1) To summarize “knowledge team’s characteristics” from practice of four cases. (2) To find the connections between “knowledge team’s characteristics” and “learning mechanism”. Also, it will analyze which “knowledge team’s characteristics” effects the knowledge team’s “learning mechanism” selections. (3) To find the connections between “knowledge team’s characteristics” and “the knowledge depending way”. Also, it will analyze which “knowledge team’s characteristics” effects the knowledge team’s “the knowledge depending way” selections. (4) To find the connections between “knowledge team’s characteristics” and “the knowledge storage and coordination way”. Also, it will analyze which “knowledge team’s characteristics” effects the knowledge team’s “the knowledge storage and coordination way” selections. (5) To find the connections between “knowledge team’s characteristics” and “the knowledge integration model”. Also, it will analyze which “knowledge team’s characteristics” effects the knowledge team’s “the knowledge integration model” selections. (6) To find the connections between “knowledge team’s characteristics” and “the knowledge integration mechanism”. Also, it will analyze which “knowledge team’s characteristics” effects the knowledge team’s “the knowledge integration mechanism” selections. (7) To find the connections between “knowledge team’s characteristics” and “the types of knowledge integrator”. Also, it will analyze which “knowledge team’s characteristics” effects the knowledge team’s “the types of knowledge integrator” selections. (8) To find the connections between “knowledge team’s characteristics” and “the role of knowledge integrator”. Also, it will analyze which “knowledge team’s characteristics” effects the knowledge team’s “the role of knowledge integrator” selections. (9) To find the connections between “knowledge team’s characteristics” and “the time ratio of opening and integration thinking”. Also, it will analyze which “knowledge team’s characteristics” effects the knowledge team’s “the time percentage of opening and integration thinking” selections. After doing interview and analysis, it gets several conclusions in this investigation: 1、“Knowledge team’s characteristics” can be divide into three parts: 　 A “The composition of team” B “The task of team” 　 C “The interrelation of team” There is an interesting thing among those three parts. “The task of team” is proportional to “The interrelation of team”. In other words, if “The task of team” is very hard, all teammates will interact frequently and job overlap is often. Then, “The interrelation of team” will be very closed. 　2、“Knowledge team’s characteristics” influence knowledge team’s “Knowledge Management Strategy”. In this investigation, “The task of team” effects knowledge team’s decision about “Knowledge Management Strategy” in several aspects, “The knowledge depending way”, “The knowledge storage and coordination way”, “The knowledge integration model”, ”The knowledge integration mechanism” and “The role of knowledge integrator”. 3、“Knowledge team’s characteristics” influence knowledge team’s “Knowledge Management Strategy”. In this investigation, “The composition of team” effects knowledge team’s decision about “Knowledge Management Strategy” in several aspects, ”The knowledge integration mechanism” and “The time ratio of opening and integration thinking”. 4、There is not any correlation between “Learning mechanism”, “The types of knowledge integrator” and “Knowledge team’s characteristics”.

由於國內市場競爭激烈與本業成熟化，我國集團企業的多角化程度高，且跨業的意願也高，但是這些跨業多角化的績效卻不如預期的理想。本研究認為集團跨業多角化時應該發揮 「知識」的範疇經濟，也就是善用集團現有的核心知識，將這些知識帶入新產業內，並使用適當的知識管理模式管理集團內與集團外的知識，進而創造出新的核心知識與競爭優勢，以提升集團跨業多角化的成功績效。 本研究以 「知識理論」為基礎，探討集團跨業多角化中，知識流通、知識蓄積、知識整合與知識創造及產業創新間的關連，並以個案研究的方式推導出相關的命題與結論。主要的研究發現與結論如下： (一)知識的特性會影響集團企業跨業多角化的知識流通方式。 本研究將知識分為兩個特性，即專屬性與內隱性，跨業多角化所流通的核心知識中，專屬性高的知識流通來源主要來自集團內，而內隱性高的知識流通媒介主要以人員移轉或引進的方式。 (二)多角化的知識管理模式會影響新核心知識的創造。 本研究認為知識管理模式包括知識流通、知識蓄積與知識整合，得出以下的結論： 1.跨業多角化的知識創造都需要有集團外的知識流通。 2.跨業多角化的知識創造會將專屬性低、內隱性高的知識轉化為專屬性高、內隱性低的知識，也就是將蓄積在個人的知識，外顯化成為蓄積在實體系統的知識。 3.跨業多角化過程中，知識的整合會建構新的核心知識。 4．集團外與集團內知識的整合成功是集團跨業多角化知識創造的主因。 (三)集團多角化企業的知識創造將會影響產業創新。 本研究發現，集團跨業多角化的創新來自於新核心知識的創造，而該企業應用新核心知識的創新將促成該產業的創新。