Research Policy最新文献

One of the key challenges for innovative companies is reducing innovation failures and the loss of scarce resources. This study investigates two under-explored aspects of innovation failure: training for innovative activities and public support for innovation. It uses data from five waves of the Community Innovation Survey (2008–2018) on more than 29,000 firms in seven emerging European innovation systems known for their weak innovation capacity, information asymmetries, and systemic failures, which increase the risk of innovation failure. We employ a matching treatment analysis method and assess the robustness of our findings with the help of multi-valued treatment, the lasso machine learning treatment technique, and entropy balancing. This study identifies the diverse effects of training for innovative activities and national and EU public support for innovation on groups of innovation incumbents and entrants. The findings show that a combination of training for innovative activities and EU innovation support helps firms reduce their chances of innovation failure. The results reaffirm the strong reliance of firms in these economies on EU funding and the limitations of national innovation policies. The findings can inform the design and implementation of innovation policies in emerging innovation systems and multi-level contexts, such as the EU.

Prior studies examining the democracy-innovation relationship have reported mixed results. To resolve this tension, our framework grounded in information processing and institutional theory proposes two mechanisms through which democracy influences innovation—pro-market institutions and information processing. Our analysis reveals that democracy indirectly affects innovation primarily through information processing rather than pro-market institutions. While gradually or increasingly democratizing states tend to focus on adopting pro-market systems without considering information freedom (e.g., lifting censorship), our results underscore the importance of information processing for strengthening the democracy-innovation relationship. Our study extends the literature on national innovation rates by shedding light on the information processing implications of democratic institutions.

Intermediaries include actors playing multiple and often different roles in the innovation process, but comparatively little scholarship has characterized intermediation for technology diffusion in remote or hard-to-reach contexts. This paper uses mixed methods to characterize the relationships and associated activities required for diffusion intermediaries to support the local embedding of solar technologies in rural Kenya and argues for a focus on the informal processs that guide intermediaries in solar technology diffusion. Findings confirm the value of close social ties for technology diffusion but further show that informal relationships with on-the-ground service provider staff support the social ties that enable technology adoption. These informal configurations of social and service ties are characterized by layered partnerships that overcome gaps in knowledge while remaining flexible enough to meet evolving local needs. Further, informal ties step in to vet technology in contexts where formal pathways and institutions are weak. Informality in intermediation is often overlooked compared to more formal firms and traditional innovation processes, but for technology diffusion in Kenya, these informal relationships provide critical links for off-grid solar access.

The number, scale and ambition of transdisciplinary research initiatives between the global north and the global south is increasing, yet there is very little theoretical or empirical scholarship on how to lead and manage implementation to promote responsible practice. Within science, technology and innovation (STI) studies and decolonising research frameworks, and utilising collaborative autoethnography, this study codifies experience with implementing the ‘Revitalising Informal Settlements and their Environments’ (RISE) program (2017–2020). Our specific aim is to explore the leadership and management tensions and challenges of implementing transboundary transdisciplinary research. The findings reaffirm the importance of research leaders and managers carefully operationalising north–south research by critically reflecting on power asymmetries between disciplines, partners and locations, leveraging the potential for transdisciplinary consortia to build research capabilities in the global south, and creating a culture of reflexivity on the historical and social positionality in which research is designed, funded, implemented and evaluated. The findings foreground the role of boundary-spanning ‘integrators’ and ‘pracademics’, roles that have received little attention to date but are essential for effective delivery and societal impact beyond scientific advances. A framework for implementing north–south transdisciplinary research is outlined with five domains: (1) collaborative leadership; (2) agile management; (3) flexible consortia; (4) researcher positionality; and (5) co-design and participation. The framework can support efforts for responsibly designing and implementing large, transdisciplinary, cross-country research programs in line with ambitions for decolonising north–south research.

We explore the relationship between government-supported science and its translation into inventive activities, focusing on the European Research Council (ERC), the principal funding mechanism for top-quality research in Europe. We show that, compared to similar European research, ERC science accrues a greater number of patent citations. Moreover, patents that draw upon ERC research are of superior quality, measured by forward citations. Compared to similar European research, inventive activities arising from ERC science are more likely to be housed within universities and public research organizations. In absolute terms, however, US organizations, especially US companies, still lead in deriving the greatest benefits from ERC science. The significant disparity in corporate sector patenting linked to ERC science in the US and EU is fueled by inventions undertaken by startups, highlighting the crucial role of a dynamic startup landscape in driving inventions at the frontier of science. Overall, our findings suggest that ERC science continues to face challenges associated with the so-called European Paradox.

The impact of religiosity on innovation has been a topic of great interest among scholars, yet its inherent complexity and endogeneity render empirical analysis a challenging task. In order to untangle these issues, our study employs a multi-faceted approach, drawing on various measures of religiosity and implementing an instrumental variable strategy within an individual-level innovation framework. We analyse the effect of religiosity on individual attitudes that are either favourable or unfavourable to innovation, capturing different aspects of an individual’s propensity to innovate. The results strongly suggest that each measure of religiosity has a somewhat negative effect on innovation attitudes. The robustness checks and sensitivity analyses support the main findings. We propose three channels from religion to innovation: time allocation, the fear of uncertainty, and conventional roles reinforced by religion.

There has been a significant increase in the number of academic studies published on the relationship between corruption and innovation in recent years. Various relationships have been conceptualized, including the “sand” and “grease” perspectives which propose that corruption reduces and increases innovation, respectively. In light of interest in the topic showing growing momentum, we review the literature on corruption and innovation for the purpose of reconciling these proposed theoretical perspectives. Following a systematic literature review methodology, we explain the composition of the literature and map the key conceptualizations of the corruption-innovation relationship. We link the variables, measures, and theories employed in the literature to proposed conceptual relationships. Furthermore, we outline the key patterns in which the sanding or greasing impact is more likely to be observed. Based on the systematic review, we propose a research agenda for corruption-innovation research and discuss policy implications.

Although there are opposing theoretical arguments on the relationship between the strength of a country's employment protection laws (EPLs) and innovation, empirical evidence tilts towards a positive relationship. However, research has mainly focused on the early stages of the innovation process, such as R&D and patenting. This study examines the role of EPLs in the later stages of the innovation process: the commercialization of new products. In particular, we focus on EPLs' relationship with two different new product commercialization outcomes: the launch and subsequent sales of new products. Using data on small European firms, we find that, controlling for invention, stricter EPLs are negatively associated with firms' likelihood of launching new products, but positively associated with the sales from new products. We discuss the implications of our results for theory and practice.

The COVID-19 pandemic exogenously hit many economies early 2020. Exploiting treatment heterogeneity, we use a conditional difference-in-differences design to causally identify how COVID-19 impacted firms’ innovation spending in the short and medium term. Based on a representative sample of German firms, we find that firms that were strongly negatively treated by COVID-19 substantially reduced innovation spending not only in the first year of the pandemic (2020) but also in the two subsequent years, indicating ‘Long COVID’ effects on innovation. Firms with higher pre-treatment digital capabilities showed higher innovation resilience during the pandemic. Moreover, COVID-19 also led to a decrease in innovation spending in those firms that were positively treated by COVID-19 through an unexpected positive demand shock, presumably to increase production capacity. Overall, these short and medium-term innovation reactions have a substantial repercussion on the macro level. In 2020, innovation expenditure fell by 4.7% due to COVID-19. In 2022, innovation spending was even 5.4% lower compared to the counterfactual scenario without the pandemic.

Since its emergence around 2010, deep learning has rapidly become the most important technique in Artificial Intelligence (AI), producing an array of scientific firsts in areas as diverse as protein folding, drug discovery, integrated chip design, and weather prediction. As scientists and engineers adopt deep learning, it is important to consider what effect widespread deployment would have on scientific progress and, ultimately, economic growth. We assess this impact by estimating the idea production function for AI in two computer vision tasks that are considered key test-beds for deep learning and show that AI idea production is notably more capital-intensive than traditional R&D. Because increasing the capital-intensity of R&D accelerates the investments that make scientists and engineers more productive, our work suggests that AI-augmented R&D has the potential to speed up technological change and economic growth.