Knowledge Management / Awad, Elias.

Format:

Book

Author/Creator:

Awad, Elias, author.

Language:

English

Subjects (All):

Knowledge management.

Organizational learning.

Physical Description:

1 online resource (480 pages)

Edition:

1st edition

Place of Publication:

Pearson India, 2003.

System Details:

text file

Summary:

The KM subject matter is a subset of content taught in the Decision Support Systems course. This text is about knowledge-how to capture it, how to transfer it, how to share it and how to manage it. Awad takes students through a process-oriented examination of the topic, striking a balance between the behavioral and technical aspects of knowledge management and use it.

Contents:

Cover

Contents

Preface

About the Authors

Part I: The Basics

Chapter 1: Working Smarter, Not Harder

In a Nutshell

What Is Knowledge Management?

The Knowledge Organization

Why Knowledge Management?

How It Came About

KM Myths

KM Life Cycle

Implications for Knowledge Management

Summary

Terms to Know

Test Your Understanding

Knowledge Exercises

References

Chapter 2: Understanding Knowledge

Definitions

Knowledge

Intelligence

Experience

Common Sense

Cognition and Knowledge Management

Data, Information, and Knowledge

Data

Information

Types of Knowledge

Shallow and Deep Knowledge

Knowledge as Know-How

Reasoning and Heuristics

Common Sense as Knowledge

From Procedural to Episodic Knowledge

Explicit and Tacit Knowledge

Expert Knowledge

Chunking Knowledge

Knowledge as an Attribute of Expertise

Human Thinking and Learning

Human Learning

Learning by Experience

Learning by Example

Learning by Discovery

Chapter 3: Knowledge Management Systems Life Cycle

Challenges in Building KM Systems

Conventional Versus KM System Life Cycle

Knowledge Management System Life Cycle (KMSLC)

System Justification

Role of Rapid Prototyping

Selecting an Expert

Role of the Knowledge Developer

User Training

Part II: Knowledge Creation and Capture

Chapter 4: Knowledge Creation and Knowledge Architecture

Knowledge Creation

Nonaka's Model of Knowledge Creation and Transformation.

Knowledge Architecture

The People Core

Identifying Knowledge Centers

The Technical Core

Build In-Home, Buy, or Outsource

Chapter 5: Capturing Tacit Knowledge

What Is Knowledge Capture?

Evaluating the Expert

Levels of Expertise

Capturing Single Versus Multiple Experts' Tacit Knowledge

Advantages and Drawbacks of Using a Single Expert

Pros and Cons of Using Multiple Experts

Developing a Relationship with Experts

Creating the Right Impression

Understanding the Expert's Style

Preparing for the Session

Approaching Multiple Experts

Deciding Where to Hold the Sessions

Fuzzy Reasoning and the Quality of Knowledge Capture

Analogies and Uncertainties in Information

Understanding Experience

The Language Problem

The Interview As a Tool

Types of Interviews

Guide to a Successful Interview

Setting the Stage and Establishing Rapport

Phrasing the Questions

Question Construction

Thing to Avoid

Reliability of Information from Experts

Errors Made by the Knowledge Developer

Problems Encountered During the Interview

Ending the Interview

Issues to Assess

Rapid Prototyping in Interviews

Benefits and Drawbacks

Chapter 6: Other Knowledge Capture Techniques

Overview

On-Site Observation

Brainstorming

Electronic Brainstorming

Protocol Analysis

What Is a Scenario?

Protocol Procedure of the Diabetic Foot KM System

Consensus Decision Making

The Repertory Grid

Nominal Group Technique (NGT)

The Delphi Method

Concept Mapping

Procedure.

Concept Mapping and Semantic Nets

Blackboarding

Part III: Knowledge Codification and System Implementation

Chapter 7: Knowledge Codification

What Is Knowledge Codification?

Why Codify?

Diagnosis

Instruction/Training

Interpretation

Planning/Scheduling

Prediction

Things to Remember

Modes of Knowledge Conversion

How to Codify Knowledge

Codifying Tacit Knowledge

Codification Tools and Procedures

Knowledge Maps

Decision Tables

Decision Trees

Frames

Production Rules

Case-Based Reasoning

Knowledge-Based Agents

The Knowledge Developer's Skill Set

Knowledge Requirements

Skills Requirements

Chapter 8: System Testing and Deployment

Quality and Quality Assurance

Knowledge Testing

Key Definitions

Issues to Consider

Approaches to Logical Testing

Circular Errors

Redundancy Errors

Unusable Knowledge

Subsumption Errors

Inconsistent Knowledge

Approaches to User Acceptance Testing

Test Team and Plan

User Acceptance Test Criteria

User Acceptance Test Techniques

Managing the Testing Phase

KM System Deployment

Issues Related to Deployment

Selection of the Knowledge Base Problem

Ease of Understanding the KM System

Knowledge Transfer

Integration Alternatives

The Issue of Maintenance

Organizational Factors

Other Factors

Role of the Champion

User Training and Deployment

Preparing for KM System Training

Combating Resistance to Change

Postimplementation Review

Security Considerations.

Implications for Knowledge Management

Chapter 9: Knowledge Transfer and Knowledge Sharing

Knowledge Transfer As a Step in a Process

The Knowing-Doing Gap

Prerequisites for Transfer

Transfer Methods

Nature of the Problem

Transfer Strategies

Inhibitors of Knowledge Transfer

How Knowledge Is Transferred

Role of the Internet in Knowledge Transfer

Internet Service Providers

Stability and Reliability of the Web

Unique Benefits of the Internet

Limitations

Chapter 10: Knowledge Transfer in the E-World

The E-World

Intranets

Extranets and Knowledge Exchange

Groupware

Groupware Applications

E-Business

The Value Chain

Supply Chain Management (SCM) and Knowledge Exchange

Part IV: KM System Tools and Portals

Chapter 11: Learning from Data

The "Learning" Concept

Data Visualization

Neural Networks As a Learning Model

The Basics

Supervised and Unsupervised Learning

Business Applications

Relative Fit with Knowledge Management

Association Rules

Market Basket Analysis: PETCO

Classification Trees

Definition

Decision for Granting a Loan

Tree Construction

Web Sites

Chapter 12: Data Mining-Knowing the Unknown

What Is Data Mining?

Data Mining and Business Intelligence

Business Drivers.

Technical Drivers

Role of Statistics

Machine Learning

Data Warehouses

OLAP

Evolution of the Decision-Making Architecture

DM Virtuous Cycle

Business Understanding

Develop the DM Application

Data Management

Data Sources

Taxonomy of Data

Data Preparation

Model Building

Parameter Settings and Tuning

Model Testing and Analysis of Results

Taking Action and Deployment

Postdeployment Phase

DM in Practice

Role of DM in Customer Relationship Management

Customer Acquisition

Campaign Optimization

Customer Scoring

Direct Marketing

Integrating DM , CRM , and E-Business

Selected Web Sites

Chapter 13: Knowledge Management Tools and Knowledge Portals

Portals: The Basics

What Is a Portal?

Evolution of Portals

Key Characteristics

Illustration

The Business Challenge

Portals and the Business Transformation

Market Potential

Knowledge Portal Technologies

Key Functionality

Collaboration

Content Management

Collaboration versus Categorization: The Case of the World Bank

Intelligent Agents

Who Is Building Enterprise Portals?

Who Sponsors Enterprise Portals?

Implementation Issues

Bandwidth

Portal Product Selection

Part V: Ethical, Legal, and Managerial Issues

Chapter 14: Who Owns Knowledge?Ethical and Legal Issues

Knowledge Owners

Knowledge for Sale

Releasing Knowledge Gained on the Job

Becoming an Expert via a Corporate Knowledge-Based System

Legal Issues

The Liability Question

The Basis of Liability.

Copyrights, Trademarks, and Trade Names.

Notes:

Online resource; Title from title page (viewed April 1, 2003)

Part of the metadata in this record was created by AI, based on the text of the resource.

ISBN:

9789332506190

9332506191

OCLC:

842893255