Knowledge Engineering: The Process Paradigm

Description

Knowledge management is far-reaching. It can dramatically reduce costs such as costs of office work repetition, human resource retirement, information reuse, etc. Rather than reinventing the wheel and having it be a costly and inefficient activity, systematic reuse of knowledge can show substantial cost benefits immediately. This book shows how to develop process-oriented methodologies, covers both interorganizational and enterprises models, discusses how knowledge management can dramatically reduce costs and increase speed of response, presents a wide range of quantitative methods applied to various knowledge engineering problems, and offers several graphical presentations of models and processes. Academicians and practitioners in the area of knowledge management and engineering, especially managers in industries will fine this book useful. The material might also be useful in knowledge management graduate studies. Cover Half Title Title Page Copyright Page Table of Contents Preface Introduction Chapter 1 Knowledge and Global Learning Main Body Subsidiaries’ Knowledge Stock Knowledge Transfer Mechanisms Data and Methods Dependent Variables Independent Variables Control Variables Methods Assessment of Measures Concluding Remarks References Chapter 2 Knowledge Processes, Intensity and Innovation Introduction Literature Review Main Body Hypotheses Analysis Measurement Concluding Remarks References Chapter 3 Knowledge with Innovation Performance Introduction Main Body Properties of Knowledge Absorptive Capacity The Research Framework of the Study Methods and Measurement Data Collection and the Sample Definitions and Measurements of the Constructs Dependent Variables Independent Variables Moderate Variables Results Model and Analysis Regression Analysis of Innovation Performance on Properties of Knowledge The Moderate Effects of a Firm’s Absorptive Capacity Concluding Remarks References Chapter 4 Knowledge and Innovation in Networked Environments Literature Review From Dynamic Capabilities to Knowledge-Based Dynamic Capabilities The Construct of Knowledge-Based Dynamic Capabilities Network Embeddedness and Innovation Hypotheses Development The Link between Knowledge-Based Dynamic Capabilities and Innovation The Antecedents of Dynamic Capabilities: Network Embeddedness Methods and Materials Dependent Variable: Innovation Performance Knowledge-Based Dynamic Capabilities (KDC) Independent Variables: Network Embeddedness Evaluations Construct Validity and Reliability Hypothesis Testing Robustness of the Results Concluding Remarks References Chapter 5 Knowledge and Organizational Business Loss Research Scope Literature Review Key Success Factors Described in Literature Literature Critique Lessons Learned Proposed Framework Research Method and Results Concluding Remarks References and Further Reading Chapter 6 Knowledge Sharing Using Semantic Web Introduction Main Body Articulation Knowledge-Sharing Platform Concluding Remarks References Chapter 7 Knowledge Sharing and Tax Payment Introduction and Background Proposed Problem and Model Risk Modeling Structure Interval Programming Case Study Computing Mean Values (ti) Computing Loss Function Computing f(xi) for the Factors Computing Risk Function (R(xi)) Concluding Remarks References Chapter 8 Knowledge Sharing for Enterprise Resources Introduction and Background Proposed Framework Network Range Tie Strength Network Efficiency Measuring CNIAM Case Study Concluding Remarks References Chapter 9 Knowledge Sharing and Organizational Culture Introduction Literature Review Research Importance and Necessity Research Hypotheses Research Method Data Analysis Variable Rankings Based on Friedman Test Concluding Remarks References Chapter 10 Knowledge Sharing and Learning Capability Introduction Organizational Learning Capability Organizational Learning Capability Dimensions Risk-Taking Interaction with the External Environment Dialogue Participative Decision Making Managerial Commitment Systems Perspective Openness and Experimentation Knowledge Transfer and Integration Teamwork Demonstration of Mission and Goals Problem Definition and Modeling Computational Results Concluding Remarks References Index