Knowledge Creation

2011 ◽  
pp. 527-538 ◽  
Author(s):  
Nilmini Wickramasinghe
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Organizational Performance ◽  
Knowledge Creation ◽  
Business Processes ◽  
Business Environment ◽  
Sustainable Competitive Advantage ◽  
Continuous Innovation ◽  
Knowledge Spiral ◽  
Business Challenges

Knowledge management (KM) is a newly emerging approach aimed at addressing today’s business challenges to increase efficiency and efficacy of core business processes, while simultaneously incorporating continuous innovation. The need for knowledge management is based on a paradigm shift in the business environment where knowledge is now considered to be central to organizational performance and integral to the attainment of a sustainable competitive advantage (Davenport & Grover, 2001; Drucker, 1993). Knowledge creation is not only a key first step in most knowledge management initiatives, but also has far reaching implications on consequent steps in the KM process, thus making knowledge creation an important focus area within knowledge management. Currently, different theories exist for explaining knowledge creation. These tend to approach the area of knowledge creation from either a people perspective—including Nonaka’s Knowledge Spiral, as well as Spender’s and Blackler’s respective frameworks—or from a technology perspective—namely, the KDD process and data mining.

scholarly journals Knowledge Creation

2011 ◽  
pp. 326-335 ◽  
Author(s):  
Nilmini Wickramasinghe
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Organizational Performance ◽  
Knowledge Creation ◽  
Business Processes ◽  
Business Environment ◽  
Sustainable Competitive Advantage ◽  
Continuous Innovation ◽  
Knowledge Spiral ◽  
Business Challenges

Knowledge management (KM) is a newly emerging approach aimed at addressing today’s business challenges to increase efficiency and efficacy of core business processes, while simultaneously incorporating continuous innovation. The need for knowledge management is based on a paradigm shift in the business environment where knowledge is now considered to be central to organizational performance and integral to the attainment of a sustainable competitive advantage (Davenport & Grover, 2001; Drucker, 1993). Knowledge creation is not only a key first step in most knowledge management initiatives, but also has far reaching implications on consequent steps in the KM process, thus making knowledge creation an important focus area within knowledge management. Currently, different theories exist for explaining knowledge creation. These tend to approach the area of knowledge creation from either a people perspective—including Nonaka’s Knowledge Spiral, as well as Spender’s and Blackler’s respective frameworks—or from a technology perspective—namely, the KDD process and data mining.

Knowledge Creation

2011 ◽  
pp. 2952-2964
Author(s):  
Nilmini Wickramasinghe
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Organizational Performance ◽  
Knowledge Creation ◽  
Business Processes ◽  
Business Environment ◽  
Sustainable Competitive Advantage ◽  
Continuous Innovation ◽  
Knowledge Spiral ◽  
Business Challenges

Knowledge management (KM) is a newly emerging approach aimed at addressing today’s business challenges to increase efficiency and efficacy of core business processes, while simultaneously incorporating continuous innovation. The need for knowledge management is based on a paradigm shift in the business environment where knowledge is now considered to be central to organizational performance and integral to the attainment of a sustainable competitive advantage (Davenport & Grover, 2001; Drucker, 1993). Knowledge creation is not only a key first step in most knowledge management initiatives, but also has far reaching implications on consequent steps in the KM process, thus making knowledge creation an important focus area within knowledge management. Currently, different theories exist for explaining knowledge creation. These tend to approach the area of knowledge creation from either a people perspective—including Nonaka’s Knowledge Spiral, as well as Spender’s and Blackler’s respective frameworks—or from a technology perspective—namely, the KDD process and data mining.

The Role of Data Mining for Business Intelligence in Knowledge Management

2015 ◽  
pp. 12-33 ◽  
Author(s):  
Kijpokin Kasemsap
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Human Resources ◽  
Organizational Performance ◽  
Business Intelligence ◽  
Statistical Significance ◽  
Practical Applications ◽  
Business Goals ◽  
Emerging Trends

This chapter introduces the role of Data Mining (DM) for Business Intelligence (BI) in Knowledge Management (KM), thus explaining the concept of KM, BI, and DM; the relationships among KM, BI, and DM; the practical applications of KM, BI, and DM; and the emerging trends toward practical results in KM, BI, and DM. In order to solve existing BI problems, this chapter also describes practical applications of KM, BI, and DM (in the fields of marketing, business, manufacturing, and human resources) and the emerging trends in KM, BI, and DM (in terms of larger databases, high dimensionality, over-fitting, evaluation of statistical significance, change of data and knowledge, missing data, relationships among DM fields, understandability of patterns, integration of other DM systems, and users' knowledge and interaction). Applying DM for BI in the KM environments will enhance organizational performance and achieve business goals in the digital age.

Developing a Framework of Human Resource Management, Organizational Learning, Knowledge Management Capability, and Organizational Performance

2015 ◽  
pp. 164-193 ◽  
Author(s):  
Kijpokin Kasemsap
Keyword(s):  
Knowledge Management ◽  
Resource Management ◽  
Organizational Learning ◽  
Human Resource Management ◽  
Organizational Performance ◽  
Human Resource ◽  
Sustainable Competitive Advantage ◽  
Management Capability ◽  
Knowledge Management Capability

This chapter introduces the framework and the practical concepts of Human Resource Management (HRM), organizational learning, Knowledge Management Capability (KMC), and organizational performance. This chapter also explains the role of HRM, organizational learning, and KMC on organizational performance. The developed framework presents the relationship among the constructs (i.e., HRM, organizational learning, KMC, and organizational performance) and contributes toward a better understanding of the specific mechanisms through which HRM, organizational learning, and KMC positively influence organizational performance. HRM effectively acts as a trigger toward effective organizational learning and KMC processes, thus creating a valuable organizational performance. Organizational performance that can usually help to perform a task in an integrated manner is a source of sustainable competitive advantage. Understanding the role of HRM, organizational learning, KMC, and organizational performance through the framework will significantly enhance the organizational performance and achieve business goals in the modern business world.

Knowledge Management

2018 ◽  
pp. 232-261 ◽  
Author(s):  
Kijpokin Kasemsap
Keyword(s):  
Social Capital ◽  
Human Capital ◽  
Knowledge Management ◽  
Knowledge Transfer ◽  
Knowledge Sharing ◽  
Organizational Performance ◽  
Organizational Factors ◽  
Knowledge Mapping ◽  
Sustainable Competitive Advantage ◽  
Process Technology

This chapter indicates the overview of Knowledge Management (KM); KM and innovation; KM and human capital; KM and social capital; KM and Human Resource Management (HRM); the significant perspectives on KM; and the advanced issues of knowledge transfer, knowledge sharing, and knowledge mapping. KM is the advanced method toward better organizational performance through knowledge transfer and knowledge sharing, and involves various organizational factors, such as people, process, technology, and culture. Utilizing KM can enhance the execution of innovation, human capital, social capital, decision making, and HRM in modern organizations. Regarding KM perspectives, creating and distributing new knowledge through effective knowledge transfer and knowledge sharing have the potential to increase organizational performance and gain sustainable competitive advantage in the knowledge era.

The Effect of Knowledge Management Strategies and Enablers on Knowledge Creation Process and Organizational Performance by Using Partial Least Squares Regression Method

2012 ◽  
Vol 3 (4) ◽  
pp. 38-52 ◽  
Author(s):  
Cheng-Ping Shih ◽  
Hsin-Fu Chou
Keyword(s):  
Knowledge Management ◽  
Organizational Performance ◽  
Least Squares ◽  
Partial Least Squares ◽  
Knowledge Creation ◽  
Least Squares Method ◽  
Management Strategies ◽  
Integrative Model ◽  
Least Squares Regression ◽  
Creation Process

Under Knowledge-based economy, knowledge has been recognized as a form of capital for organizations and provides sustainable competitive advantages. knowledge is not only one of the few recyclable assets that continuously lends itself to new intellectual capital but also be integrated in many different ways in order to maximize its value. This paper has three research objectives. Firstly, measure the effect of Knowledge Management (KM) Strategies on KM Enablers; secondly, measure the effect of KM Enablers on the Knowledge Creation Process (KCP); thirdly, to measure the effect of KCP on the three aspects of Organizational Performance. A knowledge integrative model was built by using Partial Least Squares method, and the findings indicate that KM Strategies do have a significant effect on KM enablers, which in turn does have a significant effect on the KCP. KCP also has a significant effect on innovation, customer’s satisfaction and financial performance for Taiwan multinational company in Thailand.

A Conceptual Framework for Data Mining and Knowledge Management

2011 ◽  
pp. 1-15 ◽  
Author(s):  
Shamsul I. Chowdhury
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Knowledge Base ◽  
Business Processes ◽  
Data Warehousing ◽  
Case Based Reasoning ◽  
Integrated Framework ◽  
Large Databases ◽  
Main Components ◽  
Mining Tools

Over the last decade data warehousing and data mining tools have evolved from research into a unique and popular applications, ranging from data warehousing and data mining for decision support to business intelligence and other kind of applications. The chapter presents and discusses data warehousing methodologies along with the main components of data mining tools and technologies and how they all could be integrated together for knowledge management in a broader sense. Knowledge management refers to the set of processes developed in an organization to create, extract, transfer, store and apply knowledge. The chapter also focuses on how data mining tools and technologies could be used in extracting knowledge from large databases or data warehouses. Knowledge management increases the ability of an organization to learn from its environment and to incorporate knowledge into the business processes by adapting to new tools and technologies. Knowledge management is also about the reusability of the knowledge that is being extracted and stored in the knowledge base. One way to improve the reusability is to use this knowledge base as front-ends to case-based reasoning (CBR) applications. The chapter further focuses on the reusability issues of knowledge management and presents an integrated framework for knowledge management by combining data mining (DM) tools and technologies with CBR methodologies. The purpose of the integrated framework is to discover, validate, retain, reuse and share knowledge in an organization with its internal users as well as its external users. The framework is independent of application domain and would be suitable for uses in areas, such as data mining and knowledge management in e-government.

scholarly journals Mediating Role of Knowledge Management in the Relationship between Organizational Learning and Sustainable Organizational Performance

2020 ◽  
Vol 12 (23) ◽  
pp. 10061
Author(s):  
Mirna Kordab ◽  
Jurgita Raudeliūnienė ◽  
Ieva Meidutė-Kavaliauskienė
Keyword(s):  
Knowledge Management ◽  
Organizational Learning ◽  
Organizational Performance ◽  
Business Environment ◽  
Mediating Role ◽  
Knowledge Based ◽  
East Region ◽  
The Relationship ◽  
Consulting Companies

Organizations operating in the intensive knowledge-based sector seek efficient management approaches and sustainable development practices to perform efficiently in the dynamic business environment. Knowledge management practice and organizational learning are significant factors in order to achieve sustainable organizational performance in a rapidly changing business environment. Based on the scientific literature analysis, there is still a lack of evidence related to the mediating role of the whole knowledge management cycle, including the five knowledge management processes (knowledge acquisition, creation, storage, sharing, and application) in the relationship between organizational learning and sustainable organizational performance for organizations operating in intensive knowledge-based sectors. This study aimed to examine the impact of the whole knowledge management cycle on the relationship between organizational learning and sustainable organizational performance in intensive knowledge-based sectors, specifically the audit and consulting companies in the Middle East region. Systematic scientific literature analysis, expert evaluation (structured questionnaire), and structural equation modeling (SEM) technique were used to develop and verify the research model. Data was collected through a structured questionnaire distributed among auditing experts working in a knowledge-based sector—audit and consulting companies in the Middle East region. The research results supported the hypotheses stating that organizational learning positively affects knowledge acquisition, storage, sharing, application processes, and sustainable organizational performance. However, the results verified that organizational learning has an insignificant impact on the Middle Eastern audit and consulting companies’ knowledge creation process.

Executive Insights: Knowledge—The Source of Sustainable Competitive Advantage

1998 ◽  
Vol 6 (3) ◽  
pp. 94-107 ◽  
Author(s):  
John R. Riesenberger
Keyword(s):  
Product Development ◽  
Intellectual Capital ◽  
Business Environment ◽  
Life Cycles ◽  
Sustainable Competitive Advantage ◽  
Global Learning ◽  
Complex Product ◽  
Continuous Innovation ◽  
Competitive Prices ◽  
Development Processes

Today's fast-paced business environment is characterized by chaotic markets with constantly evolving global customers, competitors, and suppliers. Product life cycles are becoming ever shorter, demanding more rapid and complex product development processes that are uniquely tuned into ever-changing customer demands. Global customers demand consistency in service and quality at globally competitive prices. Tomorrow's winners will be determined by those few firms that create the ability to develop constant and continuous innovation and transformation. This ability will be successfully manifested by those enterprises that understand, properly harness, and exploit global learning and the use of the organization's intellectual capital.

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