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Expert systems have come to the forefront in the modeling of problems. One of the major problems facing the expert system designers is to develop an accurate knowledge base and a meaningful model of uncertainty associated with complex models. Decision-making is based on knowledge, and decision system support needs a knowledge base as well. An adequate knowledge acquisition (KA) process leads to accurate knowledge and improves the decision-making process. To manage the risk of a medical service (twin pregnancy in this case) a knowledge management system was created. The captured knowledge may be associated with an uncertainty. This study aims to introduce a method for evaluating the reliability of a tacit KA model. It assisted engineering managers in assessing and prioritizing risks. The study tried to use this method in risk management and new case in the health domain.

In this study, relevant variables were identified in the knowledge management literature reviews and the domain of expertise management. They are validated by a group of domain experts. Kendall’s W indicator was used to assess the degree of consensus. On the basis of combined cognitive maps, a cognitive network was constructed. Using Bayesian belief networks and fuzzy cognitive maps, an uncertainty assessment method of tacit KA was introduced. To help managers focus on major variables, a sensitivity analysis was conducted. Reliability of model was calculated for optimistic and pessimistic values. The applicability and efficacy of the proposed method were verified and validated with data from a medical university.

Results show that tacit KA uncertainty can be defined by independent variables, including environmental factors, personality and acquisition process factors. The reliability value shows the accuracy of the captured knowledge and the effectiveness of the acquisition process. The proposed uncertainty assessment method provides the reliability value of the acquisition model for knowledge engineers, so it can be used to implement the project and prevent failures in vital factors through necessary actions. If there is not a satisficed level of reliability, the KA project reliability can be improved by risk factors. The sensitivity analysis can help to select proper factors based on the resources. This approach mitigated some of the disadvantages of other risk evaluation methods.

The contribution of this study is to combine the uncertainty assessment with tacit KA based on fuzzy cognitive maps and the Bayesian belief networks approach. This approach used the capabilities of both narrative and computational approaches.

Knowledge is a key driver for the competitive success of organizations, but about 90 percent of organizational knowledge is inside employees’ minds with personal essence; therefore, this paper provides valuable vision for managers by exploring knowledge acquisition (KA) techniques and personality type. The purpose of this paper is to examine KA techniques and explore the impact of personality type on the KA process in the aerospace industry.

This paper examines KA techniques through an empirical study involving 83 participants to take part in KA sessions. For exploring techniques, a questionnaire was used, and also the Myers-Briggs Type Indicator was used to identify participants’ personality type. The impact of personality type on KA processes was determined by correlation analysis.

Analyses confirmed some association between the type of personality and KA process. In addition, the findings of exploring questionnaire items showed that participants gave the laddering technique the highest rating.

The paper may be of high value to researchers in the field of KA, especially in aerospace industries, because there is very little experimental investigation of KA, and it also provides valuable information and guidelines that hopefully will help researchers to select appropriate KA techniques.

The purpose of this paper is to conduct a survey on the knowledge for supplier correlation with their capabilities and willingness as segmentation criteria. There are many contexts for sharing knowledge. What are more beneficial contexts?

After developing the research hypothesis, a structured questionnaire was adopted to gather primary data from suppliers. The draft questionnaire was sent to five academic and industry experts to comment on the content. Received feedback was used to change the layout of the questionnaire. Instead of the traditional partial least squares, the state-of- art consistent partial least square technique was put into practice.

By definition, knowledge for supplier has a large impact on supplier capabilities. The Important-Performance Matrix Analysis (IPMA) prioritizes the indicators and suggests to focus on knowledge sharing about manufacturing processes, development expertise and marketing expertise. Results showed that supplier willingness for sharing confidential knowledge and longtime relationship depends on development programs.

Having a communication mechanism for each of the partnerships’ specific contexts was suggested to maximize the knowledge flow.

For maximizing the knowledge flow and studying the effect on the segmentation criteria such as capability and willingness, the main contribution of the paper is to survey the supplier knowledge in depth. The IPMA was implemented to highlight the indicators.

Although there are some studies about knowledge management at national level, no integrated attempts have been reported in the direction of introducing knowledge management pattern at national level based on real experiences. Numerous researches have been conducted in the domain of knowledge management at micro level. But at macro/national level, some concepts and components have been investigated briefly. The purpose of this paper is to deal with this gap.

This research uses the hybrid method. The technique of qualitative case study of grounded theory method has been selected in this research for gathering and analyzing data. Data have been categorized and analyzed from case studies (at countries level) using the steps of this method. The degree of correlation and causality and the importance of each concept existing in the pattern have been computed by applying decision-making trial and evaluation (dematel) technique. The obtained concepts and pattern could be applied as a guide for accepting and implementing knowledge management at national level.

Total positive findings have been obtained from case studies, and the authors attained 14 concepts and one pattern. These findings provide the steps of designing and are useful in implementing projects and programs of knowledge management at national level. The degree of correlation between the components of the pattern is the other finding of this study.

The obtained concepts and patterns can be used as a guide in countries and governments which decide to implement knowledge management at national level. These can be a basis for countries which are in the process of implementing the projects of knowledge management at national level.

This research is the first study that aims to provide the pattern of knowledge management at national level and can provide useful information for countries and governments and can be used as a reference to guide them for the implementation. So these countries will be able to design and implement their programs of knowledge management purposefully.

Selection of knowledge management strategies (KMS) is one of the most important and effective factors in acquiring the competitive advantage and elevating the knowledge level of the organizations. Those organizations that have taken steps toward knowledge management necessarily need to pay utmost attention to the matter of KMS before taking any further steps in their activities. One of the effective ways in adopting the proper KMS is evaluating the knowledge management maturity level in the organization. The purpose of this paper is to design an expert fuzzy system to adopt the KMS based on Bloodgood model in accordance with the maturity level of the organization.

In this method, with the help of expert fuzzy system, a model has been designed, by using MATLAB software, to adopt the KMS. The KM maturity level, tacit knowledge and explicit knowledge are chosen as inputs, and each one of Bloodgood’s KMS (production, transfer and protecting the knowledge) are chosen as outputs. To perform the system, the maturity level of knowledge management of an industrial organization that has been evaluated by the standard Asian Productivity Organization questionnaire is used as the input, which has been given to expert fuzzy system. Then, considering the output of the system, KMS for the organization have been recommended.

Knowledge management maturity level of the organization is on Level 4; considering the expert fuzzy system that has been designed, “knowledge production” strategy is recommended for the organization under study.

An expert fuzzy system has been designed regarding the maturity of knowledge management and Bloodgood model that can be used as a guide for organizations and academic people as an appropriate practical model for selecting knowledge management strategies.

Knowledge discovery in databases (KDD) is a tedious and repetitive process. A challenge for the effective use of KDD is understanding and confirming its results derived from the harmonized process. To exploit the advantages of agents’ application, this paper aims to propose a conceptual model based on a multi-agent system (MAS) to control each step of the KDD process.

This paper reports the empirical findings of a survey conducted among academic and industrial sectors in Tehran, Iran. In this survey, the participants answered a questionnaire about the main factors of designing a suitable model for the KDD process based on MAS. The factor analysis reveals important insights of previous models developed by various researchers.

This research uses the survey results to find six critical success factors, continuity in refinement and improvement; learning and acting concurrently; loosely or tightly coupled approach for using technologies; cooperative, dynamic and flexible environment; documentation and reporting; and extracting and evaluating knowledge intelligently, for a proper conceptual model of the KDD process based on MAS.

The proposed model reflects all aspects of the KDD process by applying the intelligent agents for each process steps. In addition, this research only considers the Iran society; hence, it cannot be generalized to other nations, and it may need further research in other countries and to be implemented in real-world business domains.

This research helps organizations to adopt a proposed model and implement a KDD process to advantage the valuable knowledge that exists in their data resources.

Due to importance of knowledge management (KM) strategies in successful implementation of KM processes and saving time and expense, selection of suitable KM strategies has been changed to be a major concern by many organizations. Therefore, this is necessary for organizations to move along KM processes in selection and establishment of their strategies at their first step. An influential factor in selection of KM strategies is measurement and identification of an organization’s condition of its knowledge maturity. Accordingly, this paper aims to select and prioritize KM strategies as proportionate with an organization’s level of maturity.

For that, the author-constructed questionnaire was designated based on the opinions made by experts acquainted with KM and KM strategies. According to experts’ opinions, the paradigm for suggestion of strategies was elucidated based on KM’s level of maturity. Afterwards, the standard questionnaire knowledge navigator model was used to evaluate the organization’s level of maturity, and KM strategies for the organization were proposed based on identified level of maturity. Finally, proposed KM strategies were ranked using the fuzzy TOPSIS technique.

In this study, a paradigm for selection of suitable KM strategies was proposed based on Hansen KM strategy as per maturity level of the organization’s KM. Then, knowledge conditions of a research organization were evaluated, and, after maturity level of that organization’s KM was assessed, different criteria of Hansen KM strategy were suggested for each level independently. Research results are indicative of the fact that the intended organization is placed at the second level of KM maturity. Therefore, personalization strategies are proposed for this organization based on the elucidated paradigm. Moreover, development of work communities and development of face-to-face interactions among staff through continuous meetings were chosen as the most significant KM strategies in this organization.

This paper is one of the leading studies carried out in the purview of codification of KM strategies according to different organizations’ level of maturity. Results of this study might be used as guidelines by different organizations, academic people and experts intending to codify KM strategies.

Sharing knowledge with business partners is a challenging issue as firms need to share their valuable know-how assets with individuals or other companies out of their organizational boundaries. As supply chain management (SCM) deals with various stakeholders, firms face difficulties with privacy and ownership when they share their know-how with suppliers or business partners. This study introduces blockchain technology as a mediator in improving knowledge sharing (KS) practices in supply chains.

The data have been collected from surveys with 116 experts working in blockchain start-ups and organizations, and the authors used structural equation modeling for its analysis.

The results show that two features of blockchain technology, namely transparency and security, have the highest impacts on mediating knowledge sharing impacts on supply chain performance. The authors’ findings also highlight that among the performance metrics of SCM, speed is highly improved when blockchain technology is used for knowledge sharing. Their study provides guidance for managers on how to improve SCM performance through KS, which is empowered by a blockchain system.

The authors’ findings help organizations to improve supply chain actions, improve innovation, enhance competitive advantage and increase the speed of relationships in the supply chain. The research also contributes literature by analyzing the key factors showing how knowledge sharing structure may be improved by blockchain technology which would be helpful for both academics and practitioners.

It is commonly known that intellectual capital (IC) plays a remarkable role in organizations, especially in colleges and academic centers. The purpose of this study is to investigate the effects of knowledge sharing (KS) on IC.

Based on the extensive literature review, a questionnaire was designed. The questions were composed of two parts; KS questions and IC questions. In total, 352 students completed questionnaires in the Shahinshahr branch of Payam-e-Noor University. Structural equation modeling was used to develop the measurement model.

The findings showed that KS has a significant positive correlation with IC and its dimensions. The structural equation modeling confirmed the research model and showed a good match with it.

Given that this study aimed to examine KS and IC, it implies that with optimized knowledge management in universities, providing the infrastructures of KS and strengthening students’ motivational factors, KS capacities can be enhanced and IC of universities would be strengthened.

This paper intends to propose an approach for formation of the R&D project teams, so that in addition to the selection of the most expert individuals, facilitates the knowledge sharing among people.

Mathematical modeling was used to formulate the problem of selecting appropriate members for the project team. As the problem was formulated as a bi-objective mixed integer nonlinear programming problem, it was initially transformed from nonlinear to linear problem, and then, the global criterion method was applied to convert the problem into a single-objective problem. To collect the data for exogenous variables, the measurement scales (their validity had been verified in previous research) were adopted.

The results of various tests for evaluating the proposed approach in the case study confirmed its effectiveness in selecting the appropriate members of the project team.

Using the proposed approach, R&D project managers will be able to select the most appropriate members for the project team and, while ensuring the achievement of project objectives, prevent the loss of knowledge gained in the project lifecycle.

This paper is the first attempt to provide an approach for sharing the knowledge gained by the project team members in the R&D projects.