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The purpose of this study is to investigate and analyze the knowledge management (KM) model of Nonaka and Takeuchi, focusing on institutional and infrastructure factors in a specific field of design offices in a product-oriented organization. In other words, this research does not intend to recreate the model of Nonaka and Takeuchi, but seeks to expand and modify this model according to the specific context and institutional and infrastructure factors that may specifically affect the effectiveness of the model.

This study used two distinct questionnaires, administered to the same set of respondents, to comprehensively address different dimensions of KM. The first questionnaire, focused on KM components, assessed aspects such as knowledge creation, sharing and utilization. The second questionnaire evaluated institutional and infrastructural factors critical to KM, covering dimensions like organizational culture, values, leadership, context, hardware, software and network systems. This dual-questionnaire approach is justified, as it allows for a detailed and differentiated analysis: one tool captures the operational aspects of KM, while the other explores the supporting infrastructure. This methodology ensures that the study accurately measures both the effectiveness of KM practices and the adequacy of the supporting environment, thus providing a robust assessment of the KM system.

This study identifies seven key factors influencing KM processes: organizational culture, values, leadership, context, hardware, software and network systems. These factors shape how knowledge is created, shared and used, and support proposed modifications to the Nonaka and Takeuchi KM model. Using the TOPSIS method, this study found that organizational context, culture and values rank above average, while KM policies are moderate, and information technology is below average in the design offices of a product-oriented organization in Tehran. Further research in different sectors could help validate these findings.

This study introduces a novel enhancement to the Nonaka and Takeuchi KM model by incorporating a comprehensive analysis of institutional and infrastructural factors. Unlike existing models, which primarily focus on generalized KM principles, this research uniquely integrates specific factors such as organizational culture, leadership and technological infrastructure. The originality of this work lies in its tailored approach for product-oriented organizations, offering a more precise and actionable framework for improving KM practices. This advancement not only deepens theoretical insights but also provides practical value by addressing the specific needs and dynamics of the target organizations.

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.

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.

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.

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.