Cluster analysis of research and development value chain knowledge collaborations Innovation in the national system

Regarding the daily developments achieved in science and technology, Research and Development is now known as the key to success for industries. Moreover, the production of knowledge and its distribution and application play a vital role in creating noble commodities and can finally lead to technological innovation within industrial complexes’ R&D units. Having acknowledged scientific collaboration’s vitality en-route the achievement of products’ know-how and paying cautious attention to modeling acceleration plus creating differentiation for the end product, the present study has taken an inter-disciplinary approach to finding the best way of applying knowledge to industry. It also seeks a proper counter to the challenging question of “What are the varieties to knowledge-based collaborations within the Research and Development value chain?”

The present study is descriptive-dynamic in terms of coherence and a functional one in terms of objectives. The employed statistical society comprises 15 elites chosen judgmentally. Being a composition of two qualitative methods, utilizing Delphi and Fuzzy methods and quantitative by Cluster Analysis employing SPSS and R softwares, the study has tried its best to examine theoretical basics in real-life situations so that the most tangible results are obtained and presented.

the gained results from elites’ approaches over Delphi’s twin levels that identify the required criteria as well as scientific collaborations in addition to the cluster analysis on knowledge-based cooperation over the value chain all depict that four questionnaires plus 12 components together form the varieties of knowledge-based collaborations within the R&D value chain.

The results of the 3-level analyses depict that knowledge-based collaborations within Iran’s national innovation system can be categorized into four groups: leading, creation, distribution, and science absorption. The mentioned categories possess 12 sub-branches leading to knowledge-based collaborations via 4 clusters—the varieties, including strategic innovations and sciences, together with cover 15 activities. In comparison, the varieties including scientific creations and innovations cover 33 activities, and those concerning strategic innovations and sciences seem to cover 13 activities. Last but not least, absorbing sciences and innovation strategies cover 26 activities out of the total 80 activities throughout the research and development value chain. Knowledge-based collaborations can expand cooperation in 4 various clusters, which itself can reduce errors throughout the process of achieving the know-how and modeling and evolution acceleration plus creating differentiation for the end product. R&D sections’ Knowledge-based collaborations bear 4 clusters and 3 levels. The 4-elemented 1st level utters the knowledge-based nature of interactions within productions chains and innovative services resulting in the production, spread and absorption of knowledge throughout the national system of innovation if proper strategies are determined. The 12-elemented 2nd level displays interactions’ variety plus R&D’s complexity covering the production cycle from ideas formation until its abrogation. The 80-elemented 3rd level depicts the conducted efforts within the R&D value chain aligned with interior and exterior interactions that together lead to innovative technologies.