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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.

The activities of the oil industry from discovery to distribution of oil products have adverse effects on human and environment. Thus, the companies that are active in this industry should identify and manage their risks. The purpose of this paper is to prioritize the identified risks based on different measures such as cost, occurrence, etc. Then, selecting the most important corrective actions using goal-programming approach is another objective of this study.

To identify the health, safety and environment (HSE) risks, the Fuzzy Delphi method was used. The failure mode and effects analysis (FMEA) and fuzzy Vlse Kriterijumsk Optimizacija Kompromisno Resenje (VIKOR) methods covering the deficits of FMEA were used to rank the HSE risks. Unlike similar researches, in the proposed FMEA–VIKOR method, the risk priority number was not calculated. In addition to severity, occurrence and detection, the parameters such as time, cost and quality, being considered for ranking the risks, were weighted by the Eigenvector method. Then, a fuzzy goal-programming model was developed for determining the best solutions of risk response.

The research findings indicated that the most important risks include fire and blast because of tank and pipeline, leakage of connections and pipelines and industrial waste. Also, the most important risk responses include using and strengthening the alarm and fire extinguishing systems, using fiberglass tanks to prevent pipeline corrosion, using modern technology to have more efficient oil refining.

The main contribution of this paper is using hybrid approach of FMEA–VIKOR for risk ranking by considering different measures such as time, cost and quality besides severity, occurrence and detection. Providing a fuzzy goal-programming framework for determining the main risk responses is another value for this research.