Research Policy最新文献

This study examines how university-firm (U-F) interactions affect innovation speed in science-intensive small and medium-sized firms (SISMEs). We distinguish between formal and informal U-F interactions and build on dynamic capability theory to argue that (1) U-F R&D alliances enhance innovation speed through firm-level entrepreneurial orientation (EO), and (2) frequent U-F informal contacts weaken the effects of U-F R&D alliances on innovation speed. Analyzing a sample of 268 SISMEs from 10 science parks in China, the results of the partial least squares structural equation modeling (PLS-SEM) support our hypotheses. Furthermore, fuzzy-set qualitative comparative analysis (fsQCA) identifies various configurations of U-F R&D alliances, U-F informal contacts and EO, along with other organizational, science park and environmental conditions, that lead to higher or lower innovation speed in SISMEs. Our findings offer valuable theoretical and practical insights, advancing our understanding of the complex relationship between U-F interactions and innovation speed in SISMEs.

This paper aims to identify the factors contributing to the diffusion of ideas in econometrics by paying particular attention to connectivity in content and social networks. Considering a sample of 17,260 research papers in econometrics over the 1980-2020 period, we rely on Structural Topic Models to extract and categorize topics relevant to key domains in the discipline. Using a hurdle count model, we show that both content and social connectivity among the authors enhance the likelihood of non-zero citation counts and play a key role in shaping the diffusion of econometric ideas. We also find that high topic connectivity augmented by robust social connectivity among authors or authoring teams further enhances econometric ideas’ diffusion success. Finally, our findings unveil an inverted U-shaped relationship between connectivity and the success of idea diffusion; the latter initially escalates but starts to wane upon reaching a certain threshold.

I estimate employment multiplier effects by skill group from graduate employment and innovation at the NUTS1 and 2 level in France, Germany and the UK. Using local projections, I estimate the effects over 5-year horizons. Both graduate employment and patenting have temporary, positive impacts on non-graduate and mid-skilled employment. There is considerable heterogeneity in terms of the direction and magnitude of the effects across the three countries. The paper shows that innovation can be a source of regional employment growth, even for those without a graduate degree.

Innovation is cumulative in nature, and follow-on innovation is a way to extract value from existing technology. Thus, to appropriate the value of standard essential patents (SEPs), firms need to win the first race in pushing proprietary technologies to become SEPs and the second race in exploiting SEP-related opportunities in follow-on innovations. This study investigates how, when, and to what effect firms strategically maneuver in follow-on innovations to maximize the value appropriation from SEPs. Drawing from a resource-based logic, we argue that SEP firms’ winning strategic maneuver involves such moves: (a) engaging in early follow-on innovation targeting SEPs, (b) prioritizing the exploitation of SEPs over non-SEPs, and (c) exploiting cross-follow-on innovations to take advantage of the information and network resources they obtain from their participation in the standardization process. We further argue that SEP firms’ strategic maneuvering results in high-quality follow-on innovations, which together with SEPs form stronger patent portfolios. Analyzing a unique dataset of patents from leading Chinese ICT firms matched with forward citations, we find empirical evidence that supports our arguments. Our research has important theoretical and managerial implications for firms’ strategic innovation management with a focus on technology standardization.

Analyzing data from two randomized controlled trials (RCTs) involving 382 entrepreneurs, this study explores the implications of training a group of entrepreneurs in a scientific approach to decision-making on their project selection. It provides evidence that the documented increased likelihood of project termination by ‘scientific’ entrepreneurs is associated with higher accuracy in recognizing project value. Unlike the control group, they are quicker in adjusting their expectations on project value downward before making the termination decision. This study also fills an important gap in prior research by exploring the longer-term implications (up to five years after the training began) of a scientific approach. It shows that, over the longer term, the initial discrepancy in termination rates between treated and control entrepreneurs levels out, with the control group eventually exhibiting a higher rate of project termination. Scientific entrepreneurs generate a higher number of new ideas, and a higher proportion of their projects culminate in the launch of a venture. Overall, these findings support the notion that scientific entrepreneurs are not excessively critical in their project assessments; rather, by terminating lower-potential projects earlier, they can free up resources for redeployment elsewhere.

Firms rely on coopetition strategies (i.e., alliances with competitors), which combine cooperative and competitive behaviors to yield higher innovation outcomes. To allow for these combinations, seminal research on coopetition has considered competition and cooperation independent dimensions. However, recent contributions have suggested that they are interdependent constructs that can be either positively (balance view) or negatively (tension view) related. We claim that these two views are complementary, and that the degree of competition has an inverted U-shaped relationship (i.e., both positive and negative) with the degree of cooperation. Distinguishing between “current competition” and “proximity of future competition” and based on a sample of 180 coopetitive projects involving innovation and R&D in the biopharma industry, we show how current competition and the proximity of future competition impact the degree of cooperation in coopetitive projects. Specifically, we demonstrate the role of the proximity of future competition in directly reducing the degree of cooperation and moderating the impact of current competition on cooperation.

We investigate the unexplored relationship between robot technology adoption and product innovation. We exploit Spanish firm-level data on robot adoption and use a staggered timing difference-in-differences, supported by an instrumental variable approach. Instead of an enabling effect, we find a negative association between robot adoption and the probability to introduce product innovations, as well as their number. The result is particularly significant for larger, established, and non-high-tech firms. In line with industry evolution models, we rationalise and interpret the findings suggesting that a key mechanism at work in the robotisation-innovation nexus are diseconomies of scope fuelled by capacity-increasing investments. We also discuss whether industrial robots in our data feature enabling capabilities at all. Our results have important implications for understanding the role of robots in firms' operations and strategies, as well as for policy design.

The scale of the potential implications of machine learning (ML) has prompted discussions on the issues of corporate control and technological openness. However, how commercial and non-commercially oriented organisations each contribute to ML progress remains an open question. This study uses the recombinant innovation perspective as a lens to explore recombinant patterns across projects in an open source software (OSS) environment – where a great deal of ML innovation occurs – and assess how commercial orientation influences such patterns. It builds on a unique dataset containing data on 28,443 OSS projects, their code dependencies and the organisations owning them. Exploratory analyses reveal that ML projects combine larger and more diverse components, and produce more atypical combinations in shorter timeframes than other OSS projects, and that both company and non-company owned ML projects contribute to such recombinant atypicality. Regression analyses indicate that company owned ML projects tend to rely more on distant combinations of technical knowledge, whereas non-company owned ML projects tend to produce more novel combinations of application ideas. By extending the theories of recombinant innovation and motivation in OS innovation into a new setting – ML technology, this study contributes to both literatures by confirming that the link between distant recombination and innovation still holds in contexts characterised by complex search spaces, and by suggesting complementarities between commercial and non-commercial orientations in OSS environments rich in knowledge diversity and recombinant activity.

Economic theories have shown that industrial policy's effectiveness in fostering innovation hinges on its ability to address market failures, stimulate creative destruction, and avert adverse foreign reactions. Conversely, distortions induced by the policy and foreign countermeasures can impede its success. In this paper, we use information extracted from Chinese listed firms' financial reports and a difference-in-differences approach to examine how the “Made in China 2025” policy initiative has impacted firms' innovation and productivity outcomes. Our findings reveal that while targeted firms by the policy seem to receive increased innovation subsidies and display some indications of a heightened R&D/sales ratio, statistically significant improvements in patenting and productivity are lacking. These results cast doubt on the efficacy of the “Made in China 2025” initiative in achieving its intended goal of promoting the innovation capability of targeted firms, highlighting the theoretical and practical complexities of innovation-focused industrial policies.

We examine the change in status of three Swedish colleges to universities in 1999. This change greatly expanded the inflow of resources in the form of basic funding to the new universities. Using detailed individual data, we follow the careers of staff employed before 1999 at the treated institutions, examining their scientific performance, promotion, affiliation, and coauthorship behavior after the transition to university and comparing them to that of matched sample researchers at control colleges in a difference-in-differences analysis. We find an 89 percent increase in publication by publishing academics, an effect driven by increased funding. But we do not find an increased likelihood of publishing. Publication activity is concentrated among men, those working in technical sciences, and those holding research positions. The change to a university also led to a shift toward research-enhancing practices and organizations, manifested in coauthorship patterns, affiliations, and workforce composition. These changes altogether, enabled the new universities to begin converging in terms of research productivity to the level of established universities. Our results indicate that additional resources to institutions that historically received insufficient investment unlocked the research potential of aspiring researchers.