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The purpose of this paper is as follows: studying a case for technological innovation in Iran; studying the process of network creation; studying different challenges in finding, forming and performing of a collaboration network; studying comprehensive identification and analysis of the challenges in the network creation process; studying an active collaboration network in the field of medical equipment; and studying a network with different partners (consisting of a large company, a small- and medium-sized company, two subcontractors, three universities, a start-up, an accelerator and a venture capital fund).

The qualitative research method has been used because of a deep and rich analysis of the studied network. The study also provides an overview of finding and forming of partners and details of collaborations in the network, including partner’s goals from network entry, initial negotiations between members, business plan, shared resources and final results are expressed. The data used in this study has been collected by a totally seven semi-structured interviews. To analyze the collected data by open coding, the MAXQDA12 software was used and the basic concepts were identified and were categorized based on their similarities.

The studied network was identified as a strategic alliance. Details of finding, forming and performing of the studied network were explained. In total, 4 collaboration models and 28 different challenges in the network creation process were identified. In total, 28 different challenges were divided into 7 categories (based on their existence or absence in each of the 4 identified collaboration models). In total, seven categories of challenges were analyzed completely and the relations between challenges and partners of collaboration models were studied.

The collaboration network studied in this research involves several technological collaborations among different actors. Saadat, as the hub of this network, has been involved in all these collaborations, and other members have joined the network in accordance with network requirements and their capabilities. This network has been formed and developed with the aim of developing and producing various modules of vital signs monitoring since 2009. Some of the collaborations in this network, which are for production of a specific module and require long-term collaboration between the partners (such as the production of electrocardiograph or heart attack rapid diagnostic module), continue to be ongoing and some of them that focus on research and development or acquisition of technical knowledge (such as academic collaboration) after the specified result has been ended.

This study aims to compare the level of organizational capabilities of the exporter and non-exporter Iranian knowledge-based firms in the sector of chemical technology.

By combining 18 different indicators, a framework is designed to demonstrate organizational capabilities. The technological, manufacturing, R&D, marketing, organizing and financial capabilities of 732 Iranian knowledge-based firms in the sector of chemical technology (90 exporters and 642 non-exporter firms) are identified between 2015 and 2020. The analysis is based on the Chi-square test and logistic and probit regression.

The results indicate that technological capability, unlike the other five capabilities, is higher in non-exporter firms, and the level of marketing capability is greater in exporter firms, with the highest difference between the two groups.

The research suggests that knowledge-based firms should be evaluated based on export history; there should be some specialized export facilitating packages for both exporter and non-exporter firms; and some baskets from products with related and specialized fields of application should be formed to facilitate international marketing. The results can be a basis for managers and policymakers to improve the firm’s capabilities and competitiveness at the international level.

This study aims to design a national innovation capability appraisal model. This would indicate Iran’s competitiveness situation among regional countries and suggest factors influencing Iran’s performance promotion.

The methodology included four sections: bibliometric analysis to discover intellectual evolution of innovation capability and related concepts; construction of a multi-division structure of national innovation capability according to the clusters extracted from bibliometric results, and experts’ opinions; creating dynamic network data envelope analysis (DEA) according to designed structure, and analysis of Iran’s performance among regional countries; identification and prioritization of the factors extracted from experts’ opinions that improve Iran’s performance in created network using Fuzzy decision-making trial and evaluation laboratory method.

The contemporary bibliometric analysis by its extracted clusters proved the necessity of a multi-division for measuring national innovation capability performance that each division and indicators of each step were designed according to clusters concepts. In designed structure, dynamic network DEA results revealed the weakness of Iran’s performance in the third division in the transformation of patents and high-tech imports to high-tech and creative exports, which led to proposing improving factors by getting experts’ opinions to enhance Iran’s performance in this division by prioritizing them.

One of the limitations of this research was that the indicators used in three phases of national innovation capability in DEA were extracted only from the World Intellectual Property Organization database. Another limitation was the number of experts in focus group sessions because due to the difficulty of gathering them in one session, the researchers lost the participation of some of these recognized experts. Also, the research concentration was on the improvement of the third phase of national innovation capability, in which Iran’s performance was weak.

Creating a relationship between the divisions of dynamic network DEA, as a national innovation capability appraisal model, and the concepts of clusters extracted from reviewing the intellectual structure and evolution of innovation capability and related concepts.