虛擬知識流程觀模式與知識流歸納抽象化方法之研究

Abstract

在知識密集的工作環境中，有效地保存、管理、分享與利用知識，來提供工作者所需 之參考知識文件，以協助其工作執行，為企業組織知識管理與提昇商業智慧的重要議題。 從知識需求的角度來分析，知識流代表個別與群體知識工作者在執行工作的過程中，其知 識需求與知識參考行為的脈絡，透過知識流可以提供組織工作執行之知識分享與知識支 援。然而，以群體合作之組織工作環境而言，不同工作者依其職務角色、任務特性及工作 處理流程之不同，常有不同的知識需求。目前知識流模式之研究並未考慮如何依工作者之 不同知識需求，提供不同的知識流觀點，相關文獻中，雖已有知識流的研究探討，但並未 有知識流程觀的研究想法。 本計畫提出(虛擬)知識流程觀的創新概念與理論模式，以有效改善知識流研究不足之 處。知識流程觀主要是將知識流中的部分知識節點，依照不同工作者的知識需求，進行知 識概念的歸納抽象化，以產生虛擬知識節點，並進而產生符合工作者知識需求的虛擬知識 流，以有效提供工作者在團隊合作中之知識支援。本計畫將分三年完成，第一年我們將建 構知識流程觀模式及進行理論探討，並發展知識流歸納抽象化方法，來發掘虛擬知識節點 與虛擬知識流。此外，在執行團隊工作時，不同職務角色所需的知識層級並不相同。因此 在第二年，我們將提出以職務角色之知識需求層級為基礎的知識流程觀，包括分析工作者 所需知識主題的知識概念層級，以及相對應之知識流歸納抽象化方法，建構以職務角色為 基礎之虛擬知識流。最後，在第三年，我們將分析工作流程觀與知識流程觀的對應關係， 建立整合理論模式，並發展以知識流程觀為基礎之知識文件過濾提供機制，以提供工作者 執行工作流程所需的知識。 虛擬知識流程觀是一個創新的理論模式，預期本計畫之研究成果將擴展知識流研究領 域的理論，對企業組織在落實知識管理策略，特別是在擴大知識流運用及知識分享與利用 等亦有創新性與實務性之貢獻。

In knowledge-intensive working environments, workers need task-relevant knowledge and documents to support their task performance. Thus, how to effectively fulfill workers’ task-needs on codified knowledge (knowledge-needs) by preserving, sharing and reusing task-relevant knowledge is an important issue in realizing knowledge management and promoting business intelligence in organizations. From a knowledge-needs perspective, a Knowledge Flow (KF) represents the flow of individual’s or group members’ knowledge-needs and referencing behaviors of codified knowledge in conducting organizational tasks. Through the knowledge flow, organizations can provide task-relevant knowledge to workers to fulfill their knowledge-needs. Nevertheless, in teamwork environments, knowledge workers with different roles and task functions usually have different knowledge-needs. Conventional KF models do not provide different views of knowledge flow according to the different knowledge-needs of individuals or team workers. Several researchers have investigated the KF models, but they do not address the concept of knowledge flow view. The research objective of this project is to study the novel concept and theoretical model of Knowledge Flow View (KFV). According to different workers’ knowledge-needs, the KFV model abstracts the knowledge nodes of partial knowledge flow to generate virtual knowledge nodes through knowledge concept induction and generalization. Different virtual knowledge flows can then be derived to fulfill workers’ different knowledge-needs and provide effective knowledge support in teamwork. During the first year of this three-year project, the theoretical model of KFV will be investigated and developed. We will also develop knowledge-flow induction and abstraction methods for discovering virtual knowledge nodes and virtual knowledge flows. Besides, the knowledge-needs of workers in teamwork with different roles may vary when performing tasks. In the second year, we will develop a role-based KFV model from knowledge-needs perspective. The research directions include analyzing the concept level of knowledge topics associated with roles and developing role-based knowledge-flow induction and abstraction methods. In the third year, we will investigate the KFV model in the context of workflow environments. We will explore the inter-operations between workflow (process) view and KFV to design the integrated model formally, and then develop a KFV-based filtering mechanism to provide task-relevant knowledge to fulfill workers’ knowledge-needs. This project contributes to developing a novel KFV model which produces both theoretical and business impacts. The model will enhance the theoretical scope of knowledge flow research. In addition, it will also extend the efficiency in the use of KF, as well as the effectiveness of knowledge sharing and knowledge support in organizations.