How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.

The knowledge-creating company : how Japanese companies create the dynamics of innovation

Knowledge is attributed to human whose problem-solving behavior is subjective and complex. In today's knowledge economy, the need to manage knowledge produced by a community of actors cannot be overemphasized. This is due to the fact that actors possess some level of tacit knowledge which is generally difficult to articulate. Problem-solving requires searching and sharing of knowledge among a group of actors in a particular context. Knowledge expressed within the context of a problem resolution must be capitalized for future reuse. In this paper, an approach that permits dynamic capitalization of relevant and reliable actors' knowledge in solving decision problem following Economic Intelligence process is proposed. Knowledge annotation method and temporal attributes are used for handling the complexity in the communication among actors and in contextualizing expressed knowledge. A prototype is built to demonstrate the functionalities of a collaborative Knowledge Management system based on this approach. It is tested with sample cases and the result showed that dynamic capitalization leads to knowledge validation hence increasing reliability of captured knowledge for reuse. The system can be adapted to various domains

Dynamic Capitalization and Visualization Strategy in Collaborative Knowledge Management System for EI Process

In this study, we first examined the research and studies in the field of analysis and modeling of business processes dealt, Then a methodology for analyzing a business process based on the organizational ontology and process simulation have provided and For this purpose, a variety of organizational ontology of process analysis have studied, Then by identify existing gaps in the ontology, a Ontology-based enterprise knowledge management in organizations have developed and based on this Ontology, we provide a list for four dimensions of manpower, organization, skills and knowledge to identify the shortcomings of our procurement process. In fact, the proposed methodology aims to be a business process from both the quantitative and qualitative simulation tool by using of Ontology and organizational framework for the simultaneous quantitative and qualitative analysis provide a process. In this case study, we have used the sale of a steel plant, The results of simulation according to the standards of time and cost to process represents a failure on the various aspects of the process which creates a relatively wide range in practice, to identify the Failure of process, ontology-based lists prepared with the help of experts and the process is driven. The results indicate that there are shortcomings in some aspects such as knowledge and feedback activities.

Developing a Hybrid Business Process Model Based on Simulation-Knowledge Management

The research is in the design phase of the capitalization method. At the moment the steps, activities and guidelines for the capitalization of knowledge in Software Engineering were defined. It is named KnowCap method. The Figure 1 shows a conceptual model of the Know-Cap method. The faces of the prism represent the source for obtain knowledge (people) and the steps of the method (Identify, Add Value, Maintain and Monitor). As it can be seen in Figure 1, the people is the base of the capitalization method. The representation emphasizes that people is the base of the capitalization process, since they hold, use and generate knowledge throughout the software development. In addition, they participate in identifying the knowledge demands. The step Monitor acts as an integrator by allowing the monitoring of the evolution of knowledge, by identifying its obsolescence and/or valuation.

Know-Cap: A Method for Knowledge Capitalization in Software Engineering

In recent years, the banking industry across the nation have been undergoing swift economic revolution due to the surge created by the Central Bank of Nigeria’s (CBN) restructuring and policies on Commercial Banks Capitalization. As a result of more competitive environments and struggling economies, these banks are trying to survive the economic recession and depression in the marketplace through mergers and acquisitions to improve capital bases. This mergers/acquisitions come with the challenge of streamlining technical information between/among staff members who have come together from different bank cultures and backgrounds. Thus, this paper aimed at the development of a Knowledge Sharing System for Customer Service Officers (CSOs) which exploits knowledge resident in them for competitive advantage after such mergers and acquisitions to ensure a seamless and quick integration process. Online SMS, chat rooms are collaboration techniques used in the system. Resolutions are stored for reuse in the Knowledge Repository.

Development of Collaborative Customer Service Officer Knowledge Sharing System (CCSOKSS)

Knowledge representation is an essential criterion to capitalization of knowledge in organizations. There is need for organizations to employ strategic methods to ensure optimal innovation and effective decision making. Thus, Economic Intelligence proffers strategy to facilitate effective decision making through collection, treatment and use of relevant information for economic actors in decision making process. There are knowledge and information on actors and from required activities respectively that need be capitalized in order to aid resolution of related future decision problems. It is imperative to establish a system of organization, representation, storage and transmission of these knowledge resources. The goal of this study is to provide adaptable framework and user-centered knowledge model for the representation and exploitation of knowledge in the decision making projects of the Economic Intelligence process by acquiring, organizing, integrating and capitalizing such knowledge in order to exploit it for re-use and sharing.

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David Amos

Papers

Representation of knowledge resource in the context of economic intelligence systems