‘Cooperation with R&D Organizations and Universities Is Significantly Distinctive for Advanced Innovators’
The innovation performance of firms depends on their ability to innovate in cooperation with external partners. In their study, HSE researchers found that most of innovation in Russian manufacturing happens in a sort of open processes, but extensive cooperation networks are barely detectable. The study was published in the December issue of Foresight and STI Governance.
Using data collected in 2015 and 2018 from a specialized survey measuring the innovation activity of manufacturing enterprises, researchers from the Institute for Statistical Studies and Economics of Knowledge (ISSEK) of HSE University for the first time confirmed the widespread, but not unambiguously proven, hypothesis that the openness of innovation strategy contributes to better innovation performance.
The survey included manufacturing enterprises located in at least 40 regions of Russia. In 2015, the sample included 1,206 enterprises, of which 805 were innovation-active, meaning that they had innovation activities during the past three years, regardless of whether the activity resulted in the implementation of an innovation. In 2018, 545 enterprises of high- and medium-tech manufacturing industries (422 of which were innovation-active) were surveyed.
Valeriya Vlasova,
study co-author and Research Fellow of the Laboratory for Economics of Innovation at HSE University
With Russian data we have shown that firms able to create innovation of high degree of novelty usually interact with a wide range of partners, and, most importantly, closely cooperate with R&D organizations and universities in innovation.
In the innovation development process, firms may cooperate with different types of partners: with value chain members (clients and suppliers), competitors, public authorities, consulting firms, and institutional R&D performing organizations (universities and research organisations). The published paper examines 9 types of different partners with which businesses can work in a wide variety of combinations.
To identify patterns in the configuration of cooperation networks, the researchers investigated three aspects of network interaction: the choice of partners, the role of spatial distance, and the duration of joint projects. The analysis made it possible to demonstrate a positive relationship between the openness of an innovation strategy and enterprises’ innovation performance, in terms of innovation novelty and export capacity.
The results of the study indicate that in Russian manufacturing, almost all innovation-active enterprises cooperate with external counterparties in the process of innovation creation (98.5%), but only a few firms are integrated into extensive networks.
The most common cooperative strategy is vertical cooperation that is the involvement of clients and suppliers in the innovation process. The geography of cooperation rarely extends beyond the region's borders and is mostly of an irregular (short-term) nature. More than 40% of the surveyed enterprises follow this model.
Integration into international networks is weak (less than 5% of surveyed enterprises following this model). A small number of enterprises that engage in international cooperation tend to rely on long-term linkages with academia, which is a distinctive feature of the most innovative Russian companies.
Vitaliy Roud,
study co-author and Deputy Head of the HSE Laboratory for Economics of Innovation
Despite the stereotypes about the unreadiness of Russian science to provide quality applied results, it is the active cooperation with universities and research organizations that turns out to be a characteristic feature of enterprises capable to create highly innovative products that are competitive in global markets.
Innovation-active high-tech and medium high-tech enterprises that are engaged in industry-science cooperation are more often focused on the creation of new and significantly improved products or business processes; their strategic focuses also include searching for new client groups and expanding their product lines.
Cooperation network configurations (share of those who chose the corresponding model in the total number of innovation-active manufacturing enterprises, %)
