Open for Innovation: How Does Open Innovation Impact National Laboratories?

American organizational theorist Dr. Henry Chesbrough coined the term “open innovation,” defining it as “the use of purposive inflows and outflows of knowledge to accelerate internal innovation.” In today’s era of rapid knowledge creation, many organizations have found themselves embracing this paradigm, cooperating with other companies, universities, and public research organizations to promote internal industrial development. However, most literature has focused only on business organizations, studying their successes and failures. The question of whether open innovation benefits national laboratories deserves more attention and discussion.

Ping Lv, an associate professor at the University of Chinese Academy of Science, sheds some light on this question in a recent study about the ways in which openness affects innovation in national, key laboratories in China. Her research shows that a laboratory’s level of openness has mixed effects on its capacity to innovate. Such results provide an empirical basis for management practitioners and policymakers to promote scientific and technological advancement.

Lv uses data from China’s National Key Laboratory Annual Report Database System, which provides detailed information for all 212 existing national laboratories in China from 2006 through 2009. To better understand the relationship between level of openness and innovation, the study carefully selects measures of evaluation. Referencing Nicolas Carayol and Mireille Matt’s findings on research organizations and universities, Lv uses the number of papers indexed by the Science Citation Index (SCI) and the number of patents granted to a laboratory as the main indicators for scientific and technological innovations, respectively. Furthermore, Lv argues that a laboratory’s level of openness depends on three aspects: its academia-industry links, international collaborations, and employment of non-permanent staff. She finds that all three factors have significant effects on scientific and technological innovations, but the magnitudes and directions of the effects vary.

Statistical analysis suggests some intriguing relationships between level of openness and a laboratory’s capacity to innovate. First, when analyzing only the laboratory’s links with industry, the results show a U-shaped relationship with scientific innovation (the number of publications is the lowest when the proportion of industry funding ranges from 42 percent to 53 percent) but an inverted U-shaped relationship with technological innovation (the number of patents is the highest when the proportion of industry funding ranges from 33 percent to 41 percent). Lv explains that the initial drop in scientific publications is due to the introduction of market-oriented projects from the industry. However, as the proportion of public funding exceeds a certain threshold (42 percent to 53 percent), it benefits the laboratory’s basic research and increases the quality of its publications. On the other hand, patent output suffers from too much interaction with industries (when 33 percent to 41 percent of funding comes from industries).

The results also suggest an inverted U-shaped relationship between a laboratory’s level of international collaboration and its scientific innovation. The number of scientific publications begins to decrease when the number of international collaboration projects reaches approximately 28 at the time of observation. Lv’s reasoning is that excessive reliance on international collaboration may hamper a laboratory’s capacity to innovate internally. A similar, inverted, U-shaped relationship exists. The same reasoning holds when considering the case of technological innovation.

Finally, Lv looks at the effect of employing non-permanent staff on innovation. The relationship between scientific innovation and percentage of temporary employees is represented by an inverted U-shape: the level of scientific innovation is the highest when four percent of the total employment is temporary employees. In comparison, the study suggests that the proportion of non-permanent staff is negatively correlated with patent outputs at a laboratory. This result is unexpected and inconsistent with Lv’s hypothesis, which predicts a curvilinear relationship. This may be due to the fact that non-permanent staff are more often hired for their skills in basic research, rather than technological development.

Contrary to the popular belief that openness accelerates both scientific and technological innovations, there is no singular answer for laboratories looking to maximize their innovational power. This study suggests that a laboratory focusing on basic research should invest extensively in building academia-industry links to attract public funding, while moderating its level of international cooperation and non-permanent staff employment. Conversely, a technological, innovation-driven laboratory may benefit from maintaining the percentage of industry funding and number of international collaborations at the advised threshold levels and limiting non-permanent, academic staff. In short, management practitioners and policymakers should cautiously consider this double-edged sword of open innovation when seeking to maximize the effectiveness of national laboratories.

Article Source: “How Does Openness Affect Innovation? Evidence from National Key Laboratories in China,” Ping Lv. Science and Public Policy, June 2014.

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