Search results

The purpose of this paper is to explore the applicability of using concept maps in organizations where knowledge management is the goal.

Based on the principles stated by Nonaka and Takeuchi about knowledge creation and conversion and on the work by Novak and Gowin on concept maps, the core idea is to present the use of concept maps as a technique that facilitates, in some cases, and supports, in others, the realization of the following knowledge conversion operations: socialization, exteriorization, combination and internalization. These are the operations that, according to Nonaka and Takeuchi (1999), allow for the transformation of individual knowledge into collective knowledge and vice versa. Furthermore, it aims to answer the question of how to support the process of knowledge management in an organization through the use of a software application like CmapTools.

This paper shows that knowledge evolves through various stages, with particular characteristics that need to be acknowledged in order to be managed properly.

The technique of employing concept maps is appropriate to sponsor and facilitate the transitions among these stages of knowledge. It even allows for the preservation of the valuable knowledge of a person through the management of individual knowledge or the knowledge of a group of persons in an organization. This, in turn, promotes knowledge management in the enterprise itself.

The purpose of the research reported here is to improve comprehension of the socially‐negotiated identity of concepts in the domain of knowledge organization. Because knowledge organization as a domain has as its focus the order of concepts, both from a theoretical perspective and from an applied perspective, it is important to understand how the domain itself understands the meaning of a concept.

The paper provides an empirical demonstration of how the domain itself understands the meaning of a concept. The paper employs content analysis to demonstrate the ways in which concepts are portrayed in KO concept maps as signs, and they are subjected to evaluative semiotic analysis as a way to understand their meaning. The frame was the entire population of formal proceedings in knowledge organization – all proceedings of the International Society for Knowledge Organization's international conferences (1990‐2010) and those of the annual classification workshops of the Special Interest Group for Classification Research of the American Society for Information Science and Technology (SIG/CR).

A total of 344 concept maps were analyzed. There was no discernible chronological pattern. Most concept maps were created by authors who were professors from the USA, Germany, France, or Canada. Roughly half were judged to contain semiotic content. Peirceian semiotics predominated, and tended to convey greater granularity and complexity in conceptual terminology. Nodes could be identified as anchors of conceptual clusters in the domain; the arcs were identifiable as verbal relationship indicators. Saussurian concept maps were more applied than theoretical; Peirceian concept maps had more theoretical content.

The paper demonstrates important empirical evidence about the coherence of the domain of knowledge organization. Core values are conveyed across time through the concept maps in this population of conference papers.

Many of today's organizations already have a strong integration of groupware systems within their IT‐infrastructure. The shared databases of these groupware systems form organizational memories, which comprise the complete knowledge of an organization collected over the time of its existence. One key problem is how to find relevant knowledge or information in continuously growing and distributed organizational memories. In many cases, the basic functionalities and mechanisms of groupware systems are not sufficient to support users in finding required knowledge or information. Topic maps provide strong paradigms and concepts for the semantic structuring of link networks and therefore, they are a considerable solution for organizing and navigating large and, continuously growing organizational memories. The K‐Discovery project suggests applying topic maps to groupware systems to address the mentioned challenges. Thus, the K‐Discovery project introduces a conceptual framework, an architecture, and an implementation approach to create knowledge structures by generating topic maps from organizational memories and offers navigation tools to exploit the created structures.

The purpose of this paper was to map the safety management research of construction industry by scientometric analysis, which can predict important highlights and future research directions of safety management research in the construction industry. As an important issue in the construction industry, safety management issues have been researched from different perspectives. Although previous studies make knowledge contributions to the safety management research of construction industry, there are still huge obstacles to distinguish the comprehensive knowledge map of safety management research in the construction industry.

This study applies three scientometric analysis methods, collaboration network analysis, co-occurrence network analysis and cocitation network analysis, to the safety management research of construction industry. 5,406 articles were retrieved from the core collection database of the Web of Science. CiteSpace was used for constructing a comprehensive analysis framework to analyze and visualize the safety management research of construction industry. According to integrating the analysis results, a knowledge map for the safety management research of construction industry can be constructed.

The analysis results revealed the academic communities, key research topics and knowledge body of safety management research in the construction industry. The evolution paths of safety management research in the construction industry were divided into three development stages: “construction safety management”, “multi-objective safety management” and “comprehensive safety management”. Five research directions were predicted on the future safety management research of construction industry, including (1) comprehensive assessment indicators system; (2) intelligent safety management; (3) cross-organization collaboration of safety management; (4) multilevel safety behavior perception and (5) comparative analysis of safety climate.

The findings can reveal the overall status of safety management research in the construction industry and represent a high-quality knowledge body of safety management research in the construction industry that accurately reflects the comprehensive knowledge map on the safety management research of construction industry. The findings also predict important highlights and future research directions of safety management research in the construction industry, which will help researchers in the safety management research of construction industry for future collaboration and work.

This paper aims to present a specific model and method for analyzing the knowledge domains and organization knowledge map. One of the functions of the organizational knowledge map is the possibility of extracting the risk of the organization's knowledge domains and thus the ability to define knowledge-based strategies in the organization. So far, various software tools have been designed to support the process of creating, analyzing knowledge domains and structure knowledge map. However, software companies have less detail and methodology of their software analysis and less research has been addressed.

This model calculates the risk of knowledge domains using the recursive algorithm approach, assuming there is one-way communication between the knowledge domains and using specific factors.

The prominence of this model is to calculate knowledge domains risk, dynamic updating of knowledge domains risk after any changes in knowledge domain risk in the organization's knowledge map. The model can also be used as a simulation model and prioritize corrective actions.

This is a recursive model that by assuming one-way relations among knowledge domain computes the risk of each domain knowledge by considering the risk of its related domains, relations among different domains and pre-requisites and post-requisites. This model has no limitation in determining the number of knots and communications. Despite of simplicity, it is too efficient and any organization can localize it based on its own needs.

The purpose of this research is to propose an approach for discovering operational intelligence and knowledge mapping in a supply network with uncertainty.

Knowledge mapping and handbook techniques are used. TAPS software is used to model a supply network with uncertainty and to discover operational intelligence in a supply network.

Knowledge management is inadequate for managing a supply network with uncertainty. Knowledge mapping is proposed, but it needs to be assisted by operational intelligence.

iTAPS provides managers with an ability to visualise the operational intelligence for a given objective, and to identify the likely effects on implementing a particular tool or technique in a supply network.

A new approach – called the “intelligence handbook” is proposed to discover operational intelligence in order to map knowledge in a supply network with uncertainty.

The US$1.2 million company faces critical issues of management succession, business strategy, market expansion and innovative product improvements. These would prevent a steady flow of future potential earnings. The core knowledge resides in the management team who has worked in the factory from young. They have not patented the equipment designs or the proprietary processes. The first step in managing its intellectual capital uses the framework of the ISO 9000 standard to provide a mapping structure for capturing its core knowledge in products, process, management and customers. The focus on quality sets the context for shaping and organising the work of capturing its core knowledge. The ISO 9000 standard provides convenient categories for knowledge mapping, and presents a common language for consultant‐client interaction during the mapping process. A limitation in using the ISO 9000 standard for knowledge mapping is its inability to map knowledge concerning the customer base and product opportunities.

This paper aims to identify knowledge risk components. The present research also tends to determine the relationship between knowledge risk components, the importance of each component and the final ranking of components.

This is applied research regarding type, as well as being a descriptive, analytical study regarding performance; it is done according to the opinion of experts. Library studies are applied to extract knowledge risk components. After extracting components, components were screened using the interview technique. In addition, network analytical process method has been used for considering the interrelationship of components and determining their values.

After making the required analysis and studies, a total of 17 knowledge risk components were identified in four clusters. The four clusters include knowledge cluster, knowledge map cluster, organization cluster and expert cluster. It is to be noted that the extracted components are prioritized in each cluster. In the regarded case study, different parts of the organization have been evaluated in terms of exposure to knowledge risk.

Identifying the knowledge risk components enables the organization for moving toward the implementation of the knowledge management system and informing the organization in connection with risk aversion. In fact, such components provide the chance for the organization to identify risks inherent in each department of any organization and develop the necessary measures to reduce the risk in risky areas.

Previous commonly used author co-citation analysis (ACA) methods have limited the ability to deal with accidental co-citation in constructing a raw co-citation matrix. Therefore, the purpose of this paper is to propose a new method, called author tri-citation analysis (ATA), to better map knowledge domains and depict scientific intellectual structures.

Different from the previous method of using ACA that captures author co-citation relationships, the ATA method seeks tri-citation relationships among authors. Compared with ACA, ATA can ignore some accidental co-citation relationships between authors and can improve the accuracy of mapping knowledge domains.

Although ATA does not mine more sub-fields than ACA does, the results of the empirical studies show that ATA, the newly proposed method, performs better in knowledge domain maps based on publications in the field of computer science.

The definition of ATA in this article is simple and still insufficiently informative. Many other pieces of information can be involved; for example, all authors’ information, authors’ sequence in the author list, reference published time and similar. These can be enhanced in future studies.

This research will enrich the methods of mapping knowledge domains due to its new perspective.

Knowledge domain mapping is important to understand a discipline, and this research provides more potential methods for this, which benefits the performance of the maps.

ATA can provide a methodological awareness for mapping knowledge domains. This value lies in not only a tri-citation perspective, but also author bibliographic tripling and author tri-operation perspectives (“tri-” perspectives).

This paper aims to describe a method of teaching that is based on Novak's concept‐mapping technique.

The paper shows how concept mapping can be used to measure prior knowledge and how simple mapping exercises can promote the integration of teachers' and students' understandings in ways that are meaningful.

The concept‐mapping method facilitates quick and easy measures of student knowledge‐change so that teachers can identify the parts of the curriculum that are being understood and those that are not. This is possible even among very large student groups in the 50‐minute slots that are allocated to so much teaching in higher education.

Concept mapping is discussed in the wider context of student learning style. The styles literature has been criticised because it tends to encourage undue labelling of people or behaviours. The approach described here also uses “labels” to typify learning (using the terms non‐learning and rote or meaningful learning to identify different qualities of change).

The difference in this approach is that terms are attached to empirical measures of learning outcome, not to personal or psychological styles. Concept mapping makes learning visible so that the actual quality of the learning that has occurred can be seen and explored. Using concept mapping in the course of teaching means that learning is no longer a complex and intractable process, measurable only by proxy, but an observable phenomenon.