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The purpose of this paper is to develop a commercialization model based on gaining economic benefits through the transfer of technological capabilities in the oil and gas industry. Since commercialization models are mostly based on the implement of technology to produce and sell new products, this study focuses on developing a specific independent technology commercialization model.

The method of this research is qualitative based on the grounded theory. For this purpose, general variables with content analysis were extracted by reviewing documents (Literature review) and then for identifying special components, interviewing experts in the Iranian oil and gas industry. Participations were selected using snowball sampling for semistructured interviews.

The findings of this research were extracted based on grounded theory with data analysis in MAXQDA software. In this research, first, 210 open codes were identified based on qualitative content analysis of relevant documents and results of interviews with experts. Then the classification of open codes was done, and 46 subcategories (variables) were determined in the commercialization model. Finally, 46 subcategories were classified into 10 categories as axial codes in grounded theory as components of the commercialization model.

The results of this research have led to the creation of new practical and theoretical implications. In this research, a new perspective of commercialization with the aim of transferring technology and obtaining its economic benefits for oil and gas industry companies was discussed. Also, based on the practical implications explained in this research, policymakers can use the suggested model to effectively implement independent technology commercialization to acquire economic benefits.

This study is purely original and the outcome of the research conducted by the authors. The research findings are the outcome of in-depth study on technology commercialization in the Iranian oil and gas industry.

Knowledge protection (KP) is one of the main knowledge management (KM) processes that aim to protect the organization’s knowledge from any inside and outside force leakage. In higher education institutions (HEIs), KP is rarely being discussed and covered in contrast to knowledge sharing (KS) in terms of its determinants. The purpose of this paper is to provide a deep analysis of previous research articles from 1980 to 2019 and examine the associated institutional factors on KP determinants within HEIs as a research objective.

The preferred reporting items for systematic reviews and meta-analysis was a well-established approach for analyzing the systematic literature review methodology. Several articles were published over the past decades collected from 5 different databases, but after the screening, 101 articles were reviewed and only 22 articles were relevant to the research objective.

The findings indicated that KP is under academic research topic in KM and has received minimal attention in HEIs compared to KS, which has been frequently studied in HEIs. The literature categorized KP determinants into four areas: technological, organizational structure, behavioral and ethics and organizational culture. It will open the door for academics to investigate further into the factors, theories and models of KP in general and HEIs from a particular perspective.

As evident from the paper finds, with few pieces of literature covered in this topic, HEIs have to protect the knowledge from any illegal usage or any expert’s knowledge loss after leaving the institutions. This study can help university leaders to understand how the different KP determinants can maximize KP without affecting the KS and develop the KP phenomenon for a strategic fit to enhance their institutions’ safe knowledge usage.

This is the first research of its type which has extensively examined the literature on KP related to HEIs. Also, this paper provides theoretical and practical insights through understanding the determinants that affect KP practices among academic staff.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.