Knowledge Management Research: A Personal Experience

T.P. LiangNational Sun Yat-sen University

November 7, 2006

T.P. Liang 2006-11-07

Importance of KM Research The importance of knowledge in

business Managing knowledge is a difficult

and continuing process A challenging question: How can

knowledge be managed properly to improve firm performance?

T.P. Liang 2006-11-07

19801980 19901990 20002000

Knowledge Management is Emerging as a Major Business Priority

Business Process Re-Engineering

Global CompetitionEfficiency, Costs OutIT Replaces WorkersRestructuring

Sources: Xerox, Giga

D. HoltshouseKnowledge Initiative, Corp. Business Strategy©1998 XEROX CORP. All Rights Reserved

Total Quality Management

Japanese CompetitionQuality, Error FreeBenchmarkingRetooling

Knowledge Management

Knowledge AssetsInnovation, GrowthIT in Support of K-WorkersRevitalization

4

知識管理是 21世紀的管理趨勢

T.P. Liang 2006-11-07

資料、資訊、知識、智慧關係:價值 文字

化、分類、計算、更正、濃縮

資料

對事件審慎、客觀的紀錄

價值：比較、結果、關連性、互動

資訊

能啟發接收者，能作為重要證據

價值：行動導向、重大效益、智者直覺

知識

經驗、價值，以及經過文字化的法則

智慧

蒐集與應用知識來採取行動

T.P. Liang 2006-11-07

內隱知識與外顯知識的比較項 目

內隱知識 外顯知識

特 點 1.難以書面化表達2.難以系統化3.持續性強，不易被人改變4.例如：經驗、秘訣、信念、感覺、習慣

1.可量化或書面化2.較系統化3.固定的資訊，其運用視人而異4.例如：業務手冊、企劃案、作業指導規範、物理定律

儲存方式 人的心智 資料庫、電腦、文件

分享方式 由於難以表達，故分享困難度視個人表達能力而定，通常只能意會，並透過師徒制來學習

可透過視覺、聲音或動作來呈現、或透過書籍、影片等來傳遞

T.P. Liang 2006-11-07

不同的知識特性

個人 組織

內隱 藝術 IC 設計

外顯(SOP)

大學 生產製造

T.P. Liang 2006-11-07

知識、智慧資本與企業價值企業價值

員工的觀念型知識

員工的經驗型知識

內含於組織文化的知識

內含於組織文化的知識

可編碼的知識

人力資本

顧客資本

組織資本

有形資產

無形資產

財務性資產

知識分類 企業潛力內隱知識

外顯知識

＝

T.P. Liang 2006-11-07

個人知識與組織知識的轉換

個人知識透過分享後，轉變為組織的知識

組織的知識或經驗供個人學習、吸收後，強化個人知識

個人知識創意經驗人脈

組織知識作業程序

Know-How 工作手冊 合作方式

T.P. Liang 2006-11-07

Nonaka的知識成長模式

內隱知識 外顯知識

內隱知識 社會化 外部化

外顯知識 內部化 組 合

T.P. Liang 2006-11-07

知識管理的基本工具 創造 分類 / 儲存 索引 / 檢索 過濾 / 篩選 導覽 使用分析 知識推薦

T.P. Liang 2006-11-07

Research in Knowledge Management Conceptual

Knowledge management cycles Framework of knowledge management

Technical KMS development Knowledge recommendation

Managerial Knowledge management implementation KM and performance

T.P. Liang 2006-11-07

Major constructs of KM Nature of knowledge Organizational environment Nature of organization Knowledge management activities and

processes (cycles) KM platform: infrastructure and KMS Nature of users and intermediaries Effect of KM on organizations

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Sample Studies Effect of Knowledge Diversity on

Firm Performance Capability and Task Technology Fit

on Individual Performance Personalization and Customer-

Centric Systems

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Effect of Knowledge Diversity on Firm Performance

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Research Problem Should an industry focus on a few

key categories of knowledge or a broad coverage of all knowledge in order to be competitive?

Does the adoption of IT have any relationship with the value of knowledge and firm performance?

T.P. Liang 2006-11-07

Ecological model in Organization Hannon and Freeman (1989) proposed

the ecological view of organization that seeks to understand how social conditions affect the rates in which new organizations and new organizational forms arises, the rates at which organizations change forms, and the rates at which organizations die out.

T.P. Liang 2006-11-07

何謂生態學？ 生態學（ Ecology ）是研究生物與其周圍環境相互

關係的科學。亦即，生態學是研究在某一特定範圍內，生物與生物之間、生物與環境之間相互影響關係的科學。

生態學亦可以被視為是一種巨觀的生物學 生態學以不同層次的角度觀察生物，包含：

個體（ Organism ） 物種（ Species ） 族群（ Population ） 群落（ Community ） 生態系統（ Ecosystem ）

T.P. Liang 2006-11-07

生態學的 DICE 模式 基於生態學理論的歸納，生物族群在生態系統內的關係，主要可

以分成分佈、互動、競爭、演化四個階段，並形成一個循環，命名為 DICE 模式。

競爭 (Competition)

分佈 (Distribution)

互動 (Interaction)

演化 (Evolution)

生態系統

T.P. Liang 2006-11-07

分佈（ Distribution ） 在研究的本質上，生態學探討、描述生物體之間及生物體與環境

之間的相互關係。 如何去描繪目前生態系統的狀況便是生態研究

的基礎。 生物分佈狀況或空間塑模（ Spatial Modeling ）：

以數學方法對生態系統進行描述，包含對於各個生物族群數量的計數、地理區域的分佈狀況。

生態研究的第一步工作。

T.P. Liang 2006-11-07

分佈構面的子構面 族群的強度

族群強度在衡量不同族群之間的相對強度，藉以分析族群間的強弱關係並可定義它們之間的行為關係。一般而言，族群的強度可以利用族群的種類、族群內生物體的個數、分佈區域、及在食物鏈上的關係等構面來衡量，可用來描繪群落內族群的分佈輪廓。

物種的多樣性 衡量群落內物種的豐富程度，生態系統的一個重要觀察

指標。 多樣性與穩定性關係法則（ Diversity-stability principle ）

T.P. Liang 2006-11-07

A Knowledge Ecology Basic species in a knowledge ecology

is different types of knowledge that belong to the organization.

The goal of KM is to build a mechanism by which a healthy balance of knowledge can be maintained for achieving superior performance.

T.P. Liang 2006-11-07

Diversity vs. Stability In ecological rules, the diversity-stability

relationship is a major principal, which says an ecology is more stable if it maintains a certain level of diversity.

Similarly, we would like to examine whether the same rule holds in a knowledge ecology, ie, organizations with more diversified knowledge are more stable in performance.

T.P. Liang 2006-11-07

Research Framework

Knowledge Intensity

H11

H12

H21

H32

H22

H31

Knowledge Diversity

IT Capability

Average Performance

Performance Variation

T.P. Liang 2006-11-07

Hypotheses (1) H1: Relationship Between IT and

Knowledge Ecology H11: Higher IT capabilities support

higher knowledge ecology H12: Higher IT capabilities support

higher knowledge diversity

T.P. Liang 2006-11-07

Hypotheses (2) Relationship between Knowledge

diversity and firm performance H21: Higher knowledge intensity

results in higher average performance

H22: Higher knowledge intensity results in lower performance variations

T.P. Liang 2006-11-07

Hypotheses (3) Relationship between knowledge

diversity and firm performance Higher knowledge diversity results in

lower average performance Higher knowledge diversity results in

lower performance variations

T.P. Liang 2006-11-07

Criteria for Choosing Industries Four industries were chosen based on their

knowledge intensity and environmental uncertainty.

Knowledge intensity is measured as the ratio of product price by the tangible costs (including material costs and depreciation of fixed assets).

Environmental uncertainty is measured by the changes in technology (measured by the number and importance of patents) and product lifecycle.

T.P. Liang 2006-11-07

The Chosen Industries

Env. Uncertainty

Knowledge Intensity

Low High

High Banking

IC Design

Low Steel Semi-conductor Foundry

T.P. Liang 2006-11-07

Twelve Knowledge Types Twenty companies were chosen (five in

each category) for study. Value chain activities are used to

differentiate 12 categories of knowledge, such as raw material acquisition, product manufacturing, distribution, marketing, customer services, strategic planning, general management, financial management, quality management, human resource management, R&D, and IS management.

T.P. Liang 2006-11-07

Data Collection A group of experts was invited to fill out

the questionnaire for assessing the relative importance of a particular knowledge in an industry and the relative strength of the twelve types of knowledge among the companies

A total of 58 responses were collected, among which 17 for semiconductor, 16 for IC Design, 15 for banks, and 10 for steel.

T.P. Liang 2006-11-07

Data measurement IT capabilities: mean score on the IT

capability question from experts Knowledge intensity: mean score of the

other 11 types of knowledge Knowledge diversity: using the entropy

to measure it Firm performance: Earnings per share in

the past five years (means and variance)

T.P. Liang 2006-11-07

Relative Importances K. Type IC Design Semiconducto

rBank Steel

Mean Rank Mean Rank Mean Rank Mean Rank

R&D 6.69 1 6.71 1 6.27 1 6.40 1

Acquisition 6.56 2 5.41 10 5.73 5 5.90 9

Strategy 6.50 3 6.06 4 5.60 7 5.80 11

Production 6.44 4 6.35 2 6.13 2 6.20 3

Marketing 6.19 5 5.47 8 5.80 3 5.80 12

Quality mgt

6.19 6 5.88 5 5.20 9 6.30 2

Distribution

5.94 7 4.71 12 4.87 11 6.20 4

IT appl. 5.69 8 5.82 6 5.53 8 5.80 10

Service 5.69 8 6.18 3 5.80 4 6.00 7

General mgt

5.63 10 5.65 7 5.67 6 6.10 6

HRM 5.63 10 4.82 11 4.53 12 6.00 8

Finance 5.44 12 5.41 9 5.20 10 6.20 5

T.P. Liang 2006-11-07

Data Reliability  IC design

Semiconductor foundry Banking Steel

Raw material acquisition 0.8977 0.8608 0.7274 0.7401

Production 0.7180 0.7686 0.7921 0.8023

Distribution 0.7901 0.9489 0.7407 0.9265

Marketing 0.6600 0.8357 0.7096 0.8247

Customer services 0.8008 0.7446 0.1027 0.7342

Strategic planning 0.6704 0.6390 0.8388 0.8106

General mgmt 0.7866 0.8625 0.8415 0.7020

Finance mgmt 0.5080 0.7869 0.8711 0.7803

Quality mgmt 0.7961 0.5822 0.9249 0.8780

Human resources mgmt 0.7750 0.7334 0.9120 0.8691

R&D 0.7709 0.8471 0.8013 0.6753

IT applications 0.9392 0.7617 0.9130 0.8231

All constructs 0.9576 0.9459 0.9508 0.9627

T.P. Liang 2006-11-07

Results from Path Analysis

Knowledge Intensity

0.740***

0.414***

0.619***

-0.127**

0.502***

-0.204***

Knowledge Diversity

IT Capability

Average Performance

Performance Variation

T.P. Liang 2006-11-07

Industrial Differences

HypothesesIndustry

H11 H12 H21 H22 H31 H32

IC Design 0.675*** 0.326** 0.630*** 0.565*** ns -0.25*

Semiconductor 0.718*** 0.375*** 0.732*** ns -0.375*** -0.195

Banking 0.621*** 0.436** ns ns -0.283* -0.272

Steel 0.724*** 0.364*** 0.502*** -0.351* -0.429** ns

T.P. Liang 2006-11-07

Effect of Knowledge Breadth We choose different number of

knowledge types and see how knowledge breadth would affect the hypotheses

Stepwise analysis that removed one knowledge category ranked the least important by experts at a time, and repeated the path analysis for 9 times.

T.P. Liang 2006-11-07

Models with Different Knowledge Spread

HypothesesKnowledge

H11 H12 H21 H22 H31 H32

Top 10 0.740*** 0.414*** 0.619*** 0.502*** -0.204*** -0.127**

Top 9 0.719*** 0.387*** 0.617*** 0.505*** -0.195*** -0.137**

Top 8 0.743*** 0.422*** 0.603*** 0.499*** -0.192*** -0.155*

Top 7 0.700*** 0.365*** 0.602*** 0.514*** -0.183** -0.170**

Top 6 0.711*** 0.368*** 0.635*** 0.511*** -0.196*** -0.157*

Top 5 0.699*** 0.338*** 0.636*** 0.510*** -0.163** -0.145**

Top 4 0.697*** 0.339*** 0.608*** 0.477*** -0.162** -0.142*

Top 3 0.705*** 0.322*** 0.535*** 0.433*** ns ns

Top 2 0.669*** 0.184** 0.491*** 0.392*** ns -0.154**

T.P. Liang 2006-11-07

Effects of Knowledge Breadth by Industry

Hypotheses Knowledgecategory

IC design Semiconductor Banking Steel

Top 11 - - - 0.502***

Top 10 0.594*** 0.535*** ns 0.496**

Top 9 0.599*** 0.543*** ns 0.510***

Top 8 0.587***0.573***

ns 0.503***

Top 7 0.612*** 0.571*** ns 0.505**

Top 6 0.612*** 0.600*** ns 0.539***

Top 5 0.620*** 0.601*** ns 0.565***

Top 4 0.550*** 0.604*** ns 0.587***

Top 3 0.541*** 0.659*** ns 0.540***

Top 2 0.412*** 0.627*** ns ns

H21: knowledge intensity on performance

T.P. Liang 2006-11-07

Major Observations IT affects the intensity and diversity

of organizational knowledge Higher knowledge intensity

improves the average firm performance but reduces the stability (increases variance)

Higher knowledge diversity reduces firm performance, but increases performance stability

T.P. Liang 2006-11-07