資訊技術在知識管理之應用

由於資訊技術與網際網路之發明與蓬勃發展，使人類在儲存、傳播資料、資訊與知 識之方法上更為便利。藉著資訊技術使用成本低且能大量複製、獲取之特性，資訊因而 大量產生造成搜尋及管理不易等困難，故從 1990 年代初期看到知識類型之企業快速成 長，可知知識經濟越趨重視，如何在資訊充斥之環境中獲取及管理所需之知識，係知識 經濟時代之關鍵，而知識管理將是此環境下有效管理知識之方法之一。本研究依據學者 認為資訊技術於知識管理之重要性，茲探討資訊技術在知識管理上之應用如下。

Alavi & Leidner (1999)認為，資訊技術在知識管理上的貢獻有下列四項特點 1.資訊技術可延伸個體在組織之內部網路

2.資訊技術可提供快速學習

3.資訊技術可提供快速儲存，取用，更新資訊

4.資訊技術可使結構化之知識與查詢在組織中垂直和水平散播

Davenport & Prusak (1999)認為，資訊技術可有效地增加知識在組織中創造、儲存、

擴散以及應用之寬度、深度、品質與速度。然單獨資訊技術之存在與應用係無法造就一 個知識創造型之企業。

Alavi & Leidner (1997)認為，資訊技術與知識管理密不可分，利用資訊技術進行知 識管理已成為各組織與企業努力之目標。由於資訊技術進步，尤以網際網路與全球通訊 技術之普遍化，企業更容易地建立有效之知識管理與績效支援機制。

Bill Gates(1999) 認為，知識管理欲具備完善之功能必須有工具加以輔助才行，基本 條件包含資料庫，檔案，以及電子郵件和工作流程之應用軟體，此外，並包含搜尋功能。

Newell et al (1999)認為，有效利用資訊技術支援組織內之知識管理，可將組織內部 複雜之事務，轉化成明確且容易執行。

Pantland B. T. (1995) 曾對資訊技術於知識管理之輔助作探討，如表 8 所示。

表 8 資訊技術於知識管理之輔助

知識創造 知識儲存 知識擴散 知識應用

支援之資訊技術 Data Mining 學習工具 群組軟體

電子佈告欄 知識資料庫

電子佈告欄 專家系統

科技可支援之部份 1.較多之知識來源 2.普及性高之內部 網路

3.即時學習

1.較多之歷史資料 2.組織全面性資料

1.普及性高之內部 網路

2.較多之溝通管道 3.快速更新資訊

1.普及性高之內部 網路

2.更快速地應用新 知識

資料來源：

綜合上述學者之看法，在e 化環境下推動知識管理，必須藉由資訊技術之輔助，始 能讓知識管理活動(知識之創造、擷取、分享及應用)之推動順利進行，故本研究以資訊 技術為研究對象，建置營建產業之知識地圖，期望透過知識地圖之分析與管理，提升整 體產業之競爭力。

第 二 章 原 文 附 註 ：

[註 1]

The basic building blocks are creating an awareness of knowledge management, performing knowledge management benchmarking to see what other similar organizations have done, developing a knowledge taxonomy which serves as a vocabulary and structure in which to construct the knowledge management system, developing a knowledge management strategy, and pinpointing target areas for greatest use of knowledge management activities. Then, the next level involves selecting appropriate knowledge management technologies and tools, developing a knowledge management organizational infrastructure, and building and nurturing online communities of practice (CoP). Afterwards, knowledge management pilots can be conducted and measurements made, along with instituting a change management process within the organization.

Finally, full implementation of the knowledge management systems, processes, and practices can be made, with the constant sustaining and extending a

knowledge sharing culture.

[註 2]

Strengths

․Good support for the identification and acquisition of K both through conventional K elicitation techniques and ML techniques

․Experience of categorisation through the use of ontologies

․K modelling and representation techniques

․Understanding of problem solving methods

․Support for sharing and reuse of K

․Experience of the reuse and application of K (e.g., via KBS and CBR) Weaknesses

․Poor understanding of cultural or organisational issues

․No support for valuing K assets

․Limited contribution for dealing with tacit K

․AI techniques may discourage a holistic view of K

․Limited support for recognising redundant K

․AI systems can be complicated, requiring very specialist skills and can be expensive (AI is viewed as "rocket science").

Opportunities

․AI has a lot of practical experience and techniques to offer KM

․AI could become better accepted within companies

․KM is a good vehicle for research funding Threats

․KM is yet another management buzzword

․KM could/will be overtaken by a "new" hyped movement in 5 years and if AI is too closely associated it will be percieved as "old hat" and suffer from (another) backlash.

․KM may be taken over by document management, groupware and Intranet software companies

․Conversely KBS applications are not KM either

[註 3]

․Developing a knowledge map of an organization is a critical component of knowledge management. This is typically part of the knowledge audit step that attempts to identify stores, sinks, and constraints dealing with knowledge in a targeted business area, and then identifies what knowledge is missing and available, who has the knowledge, and how that knowledge is used. A knowledge map will then be drawn to depict those relationships in that organization.

[註 4]

Typically, concept mapping is performed for several purposes (Lanzing, 1997)：

․To generate ideas (brainstorming, etc.)

․To design a complex structure (long texts, hypermedia, large web sites, etc.)

․To communicate complex ideas

․To aid learning by explicitly integrating new and old knowledge

․To assess understanding or diagnose misunderstanding

[註 5]

․One type of knowledge map, sometimes called organizational map, links people interactions by departments in the organization. Such a knowledge map may resemble the structure below (where X represents a person in the organization and the lines represent frequent interactions).This knowledge/organizational map might suggest that the marketing department is not in frequent contact with product development, which may be problematic as marketing may not know the new products or new versions of current products that are being planned. Marketing should usually be kept abreast of R & D or product development initiatives in order to keep thensales representatives well-informed when meeting with customers/clients.

[註 6]

․Another type of knowledge map may link expertise or knowledge areas to experts or individuals.

[註 7]

․A third type of knowledge map may specifically relate knowledge areas that are available and those that are needed/missing in the organization.

[註 8]

․A last type of knowledge map that is frequently used is a type of semantic network with nodes (knowledge areas) and links (relationships between the nodes).