Operational Knowledge Management

2011 ◽  
pp. 1237-1249 ◽  
Author(s):  
Fons Wijnhoven
Keyword(s):  
Knowledge Management ◽  
Operations Management ◽  
Main Question ◽  
Human Capabilities ◽  
Business Economics ◽  
Management Framework ◽  
Knowledge Processes ◽  
Management Processes ◽  
Organization Analysis ◽  
Knowledge Intensive

The differences between the paradigms of knowledge management (KM) and operations management are huge. Whereas KM is rooted in the disciplines of human relations, sociology, organization analysis, and strategic management, the operations management paradigm finds its roots in industrial engineering, business economics, and information systems. These differences result in poor acceptance of KM ideas in operations management and vice versa. Several approaches to this problem are possible. For instance, one may state that the operations management paradigm is irrelevant for knowledge management. This is incorrect, because besides of the traditional person-oriented knowledge management processes, modern knowledge intensive firms use reengineered knowledge processes intensively (e.g., Hansen, Nohria, & Tierney, 1999). An alternative approach may be to forget about the KM paradigm and only use the operations management paradigm. This is wrong again, because most industrial enterprises compete on the development and exploitation of their expertise and human capabilities (Hamel & Prahalad, 1994; Quinn, 1992). Consequently, if knowledge management is relevant and if operations management is not irrelevant, then the main question is how to translate knowledge management issues into an operations management framework. I provide a conceptual framework for such a knowledge operations management (KOM) perspective.

Toward a Knowledge Management Framework for Auditing Processes

2017 ◽  
Vol 8 (3) ◽  
pp. 45-67 ◽  
Author(s):  
Loan Nguyen ◽  
Youji Kohda
Keyword(s):  
Knowledge Management ◽  
Theoretical Model ◽  
Qualitative Methodology ◽  
Experimental Studies ◽  
Management Framework ◽  
Documentary Analysis ◽  
Management Processes ◽  
Assurance Services ◽  
Knowledge Intensive

We aimed at discovering how auditors working in an auditing firm managed their knowledge-related processes, and then built a theoretical model for the knowledge management of professional knowledge-intensive services like auditing. We conducted a case study in an auditing firm in Vietnam by employing a qualitative methodology in this research by using twenty in-depth interviews, observations, and documentary analysis. A literature review revealed that auditing research has been developed through various approaches ranging from experimental studies to information processing and experience-focused and knowledge-related interests. However, there has not been much empirical research that explains how knowledge is created during an auditing process. We conducted an empirical case study in this research that provided useful insights into constructing a theoretical model of knowledge management processes in auditing. Because the theoretical model consisted of three phases of collecting data, analyzing data (thereby turning them into information), and synthesizing information into knowledge, we called it the collect-analyze-synthesize (CAS) model. The model was used to visualize the auditing process as a spiral with many iterative CAS processes. Wisdom in the CAS model is defined as high levels of accumulated knowledge and the ability to exercise professional judgments attained from long-term experience. Wisdom is retained by members in an auditing firm and drives the auditing process. The significance of this study was inherent in three main areas: providing scholarly extensions of the literature by suggesting a knowledge management framework for auditing processes, helping auditors and auditing firms with their roles, and ensuring better assurance services for society.

Operational Knowledge Management

2011 ◽  
pp. 2829-2842
Author(s):  
Fons Wijnhoven
Keyword(s):  
Knowledge Management ◽  
Operations Management ◽  
Main Question ◽  
Human Capabilities ◽  
Business Economics ◽  
Management Framework ◽  
Knowledge Processes ◽  
Management Processes ◽  
Organization Analysis ◽  
Knowledge Intensive

The differences between the paradigms of knowledge management (KM) and operations management are huge. Whereas KM is rooted in the disciplines of human relations, sociology, organization analysis, and strategic management, the operations management paradigm finds its roots in industrial engineering, business economics, and information systems. These differences result in poor acceptance of KM ideas in operations management and vice versa. Several approaches to this problem are possible. For instance, one may state that the operations management paradigm is irrelevant for knowledge management. This is incorrect, because besides of the traditional person-oriented knowledge management processes, modern knowledge intensive firms use reengineered knowledge processes intensively (e.g., Hansen, Nohria, & Tierney, 1999). An alternative approach may be to forget about the KM paradigm and only use the operations management paradigm. This is wrong again, because most industrial enterprises compete on the development and exploitation of their expertise and human capabilities (Hamel & Prahalad, 1994; Quinn, 1992). Consequently, if knowledge management is relevant and if operations management is not irrelevant, then the main question is how to translate knowledge management issues into an operations management framework. I provide a conceptual framework for such a knowledge operations management (KOM) perspective.

Operational Knowledge Management

2011 ◽  
pp. 703-712
Author(s):  
Fons Wijnhoven
Keyword(s):  
Knowledge Management ◽  
Operations Management ◽  
Main Question ◽  
Human Capabilities ◽  
Business Economics ◽  
Management Framework ◽  
Knowledge Processes ◽  
Management Processes ◽  
Organization Analysis ◽  
Knowledge Intensive

The differences between the paradigms of knowledge management (KM) and operations management are huge. Whereas KM is rooted in the disciplines of human relations, sociology, organization analysis, and strategic management, the operations management paradigm finds its roots in industrial engineering, business economics, and information systems. These differences result in poor acceptance of KM ideas in operations management and vice versa. Several approaches to this problem are possible. For instance, one may state that the operations management paradigm is irrelevant for knowledge management. This is incorrect, because besides of the traditional person-oriented knowledge management processes, modern knowledge intensive firms use reengineered knowledge processes intensively (e.g., Hansen, Nohria, & Tierney, 1999). An alternative approach may be to forget about the KM paradigm and only use the operations management paradigm. This is wrong again, because most industrial enterprises compete on the development and exploitation of their expertise and human capabilities (Hamel & Prahalad, 1994; Quinn, 1992). Consequently, if knowledge management is relevant and if operations management is not irrelevant, then the main question is how to translate knowledge management issues into an operations management framework. I provide a conceptual framework for such a knowledge operations management (KOM) perspective.

Big data investments in knowledge and non-knowledge intensive firms: what the market tells us

2017 ◽  
Vol 21 (3) ◽  
pp. 623-639 ◽  
Author(s):  
Tingting Zhang ◽  
William Yu Chung Wang ◽  
David J. Pauleen
Keyword(s):  
Big Data ◽  
Knowledge Management ◽  
Stock Market ◽  
Value Chain ◽  
Stock Prices ◽  
Economic Value ◽  
Information Value ◽  
Publicly Traded ◽  
Content Type ◽  
Knowledge Intensive

Purpose This paper aims to investigate the value of big data investments by examining the market reaction to company announcements of big data investments and tests the effect for firms that are either knowledge intensive or not. Design/methodology/approach This study is based on an event study using data from two stock markets in China. Findings The stock market sees an overall index increase in stock prices when announcements of big data investments are revealed by grouping all the listed firms included in the sample. Increased stock prices are also the case for non-knowledge intensive firms. However, the stock market does not seem to react to big data investment announcements by testing the knowledge intensive firms along. Research limitations/implications This study contributes to the literature on assessing the economic value of big data investments from the perspective of big data information value chain by taking an unexpected change in stock price as the measure of the financial performance of the investment and by comparing market reactions between knowledge intensive firms and non-knowledge intensive firms. Findings of this study can be used to refine practitioners’ understanding of the economic value of big data investments to different firms and provide guidance to their future investments in knowledge management to maximize the benefits along the big data information value chain. However, findings of study should be interpreted carefully when applying them to companies that are not publicly traded on the stock market or listed on other financial markets. Originality/value Based on the concept of big data information value chain, this study advances research on the economic value of big data investments. Taking the perspective of stock market investors, this study investigates how the stock market reacts to big data investments by comparing the reactions to knowledge-intensive firms and non-knowledge-intensive firms. The results may be particularly interesting to those publicly traded companies that have not previously invested in knowledge management systems. The findings imply that stock investors tend to believe that big data investment could possibly increase the future returns for non-knowledge-intensive firms.

Ontology-Based Interorganizational Knowledge Management in Sustainable Construction Project

2011 ◽  
Vol 243-249 ◽  
pp. 6339-6343
Author(s):  
Guang Bin Wang ◽  
Gui You He ◽  
Li Bian
Keyword(s):  
Knowledge Management ◽  
Construction Industry ◽  
Negative Impact ◽  
Sustainable Construction ◽  
Construction Process ◽  
Application Process ◽  
Process Ontology ◽  
Knowledge Intensive ◽  
Traditional Construction ◽  
Industry Needs

Due to the great negative impact, the construction industry needs to undergo a paradigm shift from traditional construction to sustainable construction. To reach the goal of sustainable development, the construction industry needs to intensify its efforts to move to a knowledge intensive mode. Based on the analysis of e-Cognos and the concept of ontology, this paper proposes that e-Cognos ontology can be applied in the development of sustainable construction process ontology, which is a key part of knowledge management system (KMS). Following this, the application process of ontology-based KMS is analyzed using IDEF0 modeling method. Finally, this paper analyzes interorganizational collaboration model in sustainable project.

scholarly journals Strategies for knowledge management in law firms in Botswana

2009 ◽  
Vol 11 (2) ◽  
Author(s):  
M.C. Fombad ◽  
J.A. Boon ◽  
T.J.D. Bothma
Keyword(s):  
Knowledge Management ◽  
Developed Countries ◽  
Law Firms ◽  
Legal Environment ◽  
Traditional Methods ◽  
Competitive Edge ◽  
Cost Efficient ◽  
Knowledge Intensive

This article formulates a route map on how law firms in Botswana may utilise knowledge management to enhance their competitive edge amidst the changing legal environment. It draws from the multiple definitions and perspectives of knowledge management, several frameworks and models together with the empirical findings to recommend a strategy for knowledge management in law firms in Botswana. It underscores the fact that knowledge management is becoming an imperative for the survival of law firms as knowledge intensive organisations. Law firms in Botswana can no longer afford to rely on the traditional methods of managing knowledge because there is a need for the 'best minds' and the best knowledge in their area of practice. It is recommended that lawyers should be proactive, adaptive, innovative, effective and competitive in the provision of outstanding, cost-efficient and effective services to clients. Most previous studies in this area have been carried out in developed countries with large law firms.

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