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The purpose of this study paper is to identify and prioritize the factors affecting the knowledge flow in high-tech industries.

This research is applied in terms of purpose and descriptive-survey in terms of data collection method. This research has been done in a qualitative–quantitative method. In the qualitative part, due to the nature of the data in this study, expert interviews have been used. The sample studied in this research includes 35 managers and expert professors with experience in the field of knowledge management working in universities and high-tech industries who have been selected by the method of snowball. In the quantitative part, the questionnaire tool and DANP multivariate decision-making method have been used.

In this study, a multicriteria decision-making technique using a combination of DEMATEL and ANP (DANP) was used to identify and prioritize the factors affecting the knowledge flow in high-tech industries. In this study, the factors affecting the knowledge flow, including 8 main factors and 31 subfactors, were selected. Human resources, organizational structure, organizational culture, knowledge communication, knowledge management tools, knowledge characteristics, laws, policies and regulations and financial resources were effective in improving knowledge flow, respectively.

By studying the research, it was found that the study area is limited, and the previous work has remained at the level of documentation and little practical use has been done. In previous research, the discussion of knowledge flow has not been very open, and doing incomplete work causes limited experiences and increases cost and time wastage, and parallel work may also occur. Therefore, to complete the knowledge management circle and fully achieve the research objectives, as well as to make available and transfer the experiences of people working in this field and also to save time and reduce costs, the contents and factors of previous models have been counted. It is designed for high-tech industries, a model for the flow of knowledge.

The purpose of this paper is to investigate the relationship among knowledge management (KM), intellectual capital and organizational innovation. The present literature in these three areas of study, the effect of KM on organizational innovation through the development of intellectual capital has been rarely studied so far. Therefore, in this research, the authors tried to examine the effect of KM processes on organizational innovation through the development of intellectual capital in Iranian industrial organizations.

The data of this research has been gathered and aggregated through the distribution of a closed questionnaire in a sample of 384 people selected from the statistical population consisting 4,589 managers and senior managers of the Iranian industrial organizations. Data were then analyzed using SPSS software and structural equation modeling method which was used to measure the models integrity.

The results of this research indicate that KM processes affect the development of intellectual capital of an organization. KM processes are also effective in promoting innovation in the organization. KM processes also contribute to improving the level of innovation in the organization through intellectual capital development. The results also show that managers need to focus on the development of their human capital through the use of young native educated specialists to maximize internal capacity and knowledge creation and move toward improving human capital of the organization.

The present literature in these three areas of study, the effect of KM on organizational innovation through the development of intellectual capital has not been studied so far. This study of industrial organizations is also a valuable factor in this paper.

The purpose of this paper is to examine the relationship between knowledge management (KM) processes and supply chain performance, with information technology/information system (IT/IS) support, supply chain integration, and supply chain strategy as moderators.

Drawing on the knowledge-based view, a theoretical framework is developed consisting of six KM processes: knowledge creation, knowledge capture, knowledge organization, knowledge storage, knowledge dissemination, and knowledge application, and the performance of supply chain is evaluated in terms of four Supply Chain Operations Reference (SCOR) process elements: Plan, Source, Make, and Delivery. Structural equation modeling is employed using a sample of 78 Iranian manufacturers in mechanical and engineering industry.

Empirical results show that KM processes have a significant impact on supply chain performance which is positively moderated by IT/IS support and supply chain integration. While the moderating effect of IT/IS support is found to be considerably stronger, the relationship between KM processes and supply chain performance is not significantly different in lean and agile supply chains.

Since the sample for this study is small and drawn only from manufacturing companies in mechanical and engineering industry, it would be important to conduct further empirical studies with larger samples from a wider range of industries to improve and strengthen our analyses and provide more conclusive and generalizable results.

Through empirical study, a better understanding of the impact of KM processes on supply chain performance and the moderating role of IT/IS support and supply chain integration can be gained.

The purposes of this study are to identify, classify and prioritize knowledge management (KM) barriers in an Iranian project-based organization (PBO) and to present a conceptual framework for improving attitudes to KM in the Iranian context.

After studying previous literature on the topic, initial barriers of KM in PBOs were extracted. Then, a list of barriers of KM in the aforementioned organizations was finalized by interviewing experts in KM. After that, the barriers were prioritized using a questionnaire. Finally, a conceptual framework for successfully tackling KM barriers was presented.

In this article, barriers of KM in PBOs have been divided into five categories: individual, organizational, technological, contextual, and inter-project. Then a three-layered conceptual framework has been presented which describes how the barriers of KM in PBOs may be removed progressively.

The prepared and prioritized list of barriers of KM in PBOs is a stepping stone and a guideline for managers in PBOs which will enable them to identify barriers of KM in their own organizations and resolve them and improve KM in their organizations. It also serves as a useful base for researchers to expand further research concerning barriers of KM in PBOs.

This article is probably the first article which has identified barriers of KM via interviews and questionnaires carried out in 50 active PBOs which had a KM section. The article also presents a three-layered framework for lowering barriers of KM, which can be applied step by step after considering the level of importance of each one identified.

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.

In recent decades, many managers have conceived the radical role of knowledge in acquiring a competitive advantage and pursuing organizational strategic goals. Therefore, knowledge management is now a competitive requirement in organizations. However, if proper infrastructures and necessary prerequisites are not provided for executing such a process, the result will be nothing except failure and resource waste. Therefore, it is necessary that organizations identify effective factors for their readiness in executing knowledge management. The purpose of this study is identifying and prioritizing of effective constructs in readiness of knowledge management implementation by using fuzzy analytic hierarchy process (AHP).

In the present study, the relevant literature is initially reviewed and then seven factors and 19 affecting indicators on knowledge management readiness are identified by using a questionnaire for knowledge management elites which also constitute the research conceptual model. Finally, the weight of each factor is determined by fuzzy analytical hierarchy process and the readiness priority and preference of each factor are discussed.

The results of fuzzy analytic hierarchy process show that the management factor is recognized as the most effective factor in knowledge management execution readiness.

The model proposed in this study is applicable to the academic culture. Modification of the proposed model may be needed in applying this model to other environments.

As limited studies have been carried out on identifying and prioritizing of effective constructs in readiness of knowledge management implementation by using fuzzy analytic hierarchy process, the findings of this study will be useful in identifying and assessing the main components in readiness of knowledge management implementation in the research and training centers.

This research paper aims to investigate the internationalization and visibility of Iranian scientific journals covered by the Institute for Scientific Information (ISI) between 2000 and 2006.

A total of 1,298 articles published in seven Iranian ISI journals and a random sample of 1,298 articles written by Iranians and published in non‐Iranian ISI journals between 2000 and 2006 were selected. Impact factor (IF), total citation (TC), citation rates, self‐citation, foreign citation, international citation (IC), international authorship, and subject distribution were analyzes for the collections.

Results indicated that: the visibility rate of Iranian journals is low compared to their international counterparts; the international visibility of Iranian journals differs among disciplines; the increasing citation rate is less than the increase in publication rate; and the majority of authors who published in these journals were Iranian.

Mere inclusion of scientific journals in the ISI does not necessarily lead to an increase in international visibility. The study highlights the need for more studies on the techniques to increase the visibility of scientific journals of the developing countries.

In the present research, a numerical investigation is carried out to study the fluid flow and heat transfer in a double-pipe, counter-flow heat exchanger exploiting metal foam inserts partially in both pipes. The purpose of this study is to achieve the optimal distribution of a fixed volume of metal foam throughout the pipes which provides the maximum heat transfer rate with the minimum pressure drop increase.

The governing equations are solved using the finite volume method. The metal foams are divided into different number of parts and positioned at different locations. The number of metal foam parts, their placements and their volume ratios in each pipe are sought to reach the optimal conditions. The four-piece metal foam with optimized placement and partitioning volume ratios is selected as the best layout. The effects of the permeability of metal foam on the Nusselt number, the performance evaluation criteria (PEC) and the overall heat transfer coefficient are investigated.

It was observed that the heat transfer rate, the overall heat transfer coefficient and the effectiveness of the heat exchanger can be improved as high as 69, 124 and 9 per cent, respectively, while the highest value of PEC is 1.36.

Porous materials are widely used in thermo-fluid systems such as regenerators, heat sinks, solar collectors and heat exchangers.

Having less pressure drop than fully filled heat exchangers, partially filled heat exchangers with partitioned metal foams distributed optimally enhance heat transfer rate more economically.

The purpose of this paper is to improve the lattice Boltzmann method’s ability to simulate a microflow under constant heat flux.

Develop the thermal lattice Boltzmann method based on double population of hydrodynamic and thermal distribution functions.

The buoyancy forces, caused by gravity, can change the hydrodynamic properties of the flow. As a result, the gravity term was included in the Boltzmann equation as an external force, and the equations were rewritten under new conditions.

To the best of the authors’ knowledge, the current study is the first attempt to investigate mixed-convection heat transfer in an inclined microchannel in a slip flow regime.

This paper aims to propose a new nonlinear function estimation fuzzy system as a novel statistical approach to estimate nanofluids’ thermal conductivity.

A fuzzy system having a product inference engine, a singleton fuzzifier, a center average defuzzifier and Gaussian membership functions is proposed for this purpose.

Results indicate that the proposed fuzzy system can predict the thermal conductivity of Al₂O₃/paraffin nanofluid with appropriate precision and generalization and it also outperforms the classic interpolation methods.

A new nonlinear function estimation fuzzy system was introduced as a novel statistical approach to estimate nanofluids’ thermal conductivity for the first time.