Research Policy最新文献

Based on the dynamic capabilities framework and the concept of entrepreneurial innovation, we identify a set of metrics that can be used to assess innovation and entrepreneurial ecosystems in an emerging economy. These metrics allow us to analyze how such ecosystems develop key capabilities and how they generate economic and social value. We also assess the relationship between entrepreneurial innovation, ecosystems, and socio-economic impact.

Despite tremendous growth in the volume of new scientific and technological knowledge, the popular press has recently raised concerns that disruptive innovation is slowing. These dire prognoses were driven in part by Park et al. (2023), a Nature publication that uses decades of data and millions of observations coupled with a novel quantitative metric (the CD index) that characterizes innovation in science and technology as either consolidating or disruptive. We challenge the (Park et al., 2023) patent findings, principally around concerns of truncation bias and exclusion bias. We show that 88 percent of the decrease in the average CD index over 1980–2010 reported by the authors can be explained by their truncation of all backward patent citations before 1976. We also show that this truncation bias varies by technology class. We further account for a change in U.S. patent law that allows for citations to patent applications in addition to patent grants—something ignored by the authors in their analysis—and update the analysis to 2016. We show that the number of highly disruptive patents has increased since 1980—particularly since 2008. Our results suggest caution in using the (Park et al., 2023) patent findings and conclusions as a basis for research and decision-making in public policy, industry restructuring or firm reorganization aimed at altering the current innovation landscape.

Artificial intelligence (AI) can perform core research tasks such as generating research questions, processing data, and solving problems. We shift the focus from AI as a “worker” to ask whether, how, and when AI can also “manage” human workers who perform such tasks. Focusing on the context of crowd science, we find examples of algorithmic management (AM) in five key functions highlighted in prior organizational literature: task division and task allocation, direction, coordination, motivation, and supporting learning. These applications benefit from the instantaneous, comprehensive, and interactive capabilities of AI, and reflect several more general underlying functions such as matching, clustering, and forecasting. Quantitative comparisons show that projects using AM are larger and more likely to be associated with platforms than projects not using AM, pointing to potentially important contingency factors. We conclude by outlining an agenda for future research on algorithmic management in scientific research.

This paper is the first to examine the impact of robotization on work meaningfulness, autonomy, competence, and relatedness, which are essential to motivation and well-being at work. Using surveys of workers and robotization data for 14 industries in 20 European countries spanning 2005–2021, we find a consistent negative impact of robotization on perceived work meaningfulness and autonomy. Using instrumental variables, we find that doubling robotization leads to a 0.9 % decrease in work meaningfulness and a 1 % decline in autonomy. To put this in perspective, if the robotization levels of the top 5 industry were to match those of the leading industry in terms of robot adoption in 2020 (equivalent to a 7.5-fold increase), it would result in a decline of 6.8 % in work meaningfulness and 7.5 % in autonomy. The link between robotization, competence, and relatedness is also negative but less robust. We also examine how tasks, skills, and socio-demographic characteristics moderate the main relationships. We find that workers with routine tasks experience an even greater negative effect of robotization in terms of declines in their autonomy, competence, and relatedness. However, we also discover that utilizing computers as tools for independent work can help workers maintain a sense of autonomy, competence, and relatedness in industries and job roles that adopt robots. Our results highlight that by deteriorating work meaningfulness and self-determination, robotization can impact work life above and beyond its consequences for employment and wages.

This paper investigates the effects of financial market integration on firm-level external debt financing and subsequent inventive activities. To this end, I exploit the implementation of the Financial Services Action Plan (FSAP) as a positive exogenous shift integrating European banking markets during the 2000s. My findings show that higher integration relaxes financing constraints, with significant positive effects on firms’ use of debt and interest burden, particularly for ex-ante financially constrained firms. Moreover, financial integration spurs innovative activities in terms of patenting of those firms that benefited from the reforms. Considering a variety of qualitative dimensions shows that lifting financing constraints improves patent quality for a subset of previously constrained firms with low ex-ante patenting intensities (entrants) while adversely affecting the inventive output of incumbent patentees in the spirit of a quantity–quality tradeoff. These findings highlight the key function of a conducive financing environment for inventive activities but also reveal unintended limitations of policy-induced improvements in access to financing.

User innovations are widely present in the household sector, but often do not spread to others because users lack incentives to sell and/or share. Previous studies of what alleviates this diffusion problem were empirically driven, while a theoretical framework that integrally explains alleviating factors is missing. We fill this void by proposing an identity perspective based on users' eudaimonic motivation: diffusion efforts may be in line with users' aspired ‘daimon’ or true self. An identity perspective unites previously unconnected alleviating factors (commercial motivation, community involvement, common cause motivation) and enables theorizing about interaction effects. We identify three types of user innovator identity with potential relevance for diffusion: professional, community-oriented and societal. Survey data of 999 Chinese user innovators confirm that aspired professional identity is associated with sales effort, and community-oriented and societal identity with free sharing. Moreover, community-oriented and professional identity interact positively with selling effort. We conclude that an identity perspective enhances our understanding of the diffusion of user innovations to everyone's benefit.

This paper asks how start-ups' participation in a mentoring program relates to finance and survival outcomes and how these outcomes differ for mentored firms compared to non-mentored and incubated firms in the same region. Drawing on the entrepreneurial support organization, mentoring, and innovation literatures, I posit that mentored firms will perform better than non-mentored firms, and that the specific micro-mechanisms of mentoring will lead to varied finance and survival outcomes for mentored as compared to incubated start-ups. Exploiting detailed data on the universe of entrepreneurial life sciences firms in the Research Triangle region of North Carolina over a 25-year time period and matching methods, results indicate that mentored firms perform better in terms of finance than non-mentored firms. Exploratory empirical extensions reveal mentored firms receive greater private and federal public funding than incubated firms, but not local public funding. Neither mentoring nor incubation services relate to survival outcomes. The paper concludes with practical implications for entrepreneurial support organization managers and economic development.

We investigate how two experiences of technology search and product component reuse singly and jointly drive firms to generate subsequent new product innovations. We conceptualize fine-grained types of product component reuse based on whether product components are reused for the first time or multiple times and are introduced internally or externally. Our baseline hypothesis is that firms' boundary-spanning search for technology will increase their generation of new product innovations. Then, we hypothesize that when firms first reuse product components, the reuse of internally introduced product components will generate more new product innovations than the reuse of externally introduced product components; when firms reuse product components multiple times, the reuse of externally introduced product components will generate more new product innovations than the reuse of internally introduced product components. For the interplay between two types of experiences—the technological search and product component reuse—we propose that when firms reuse their own product components for the first time, the positive effect of boundary-spanning search on new product innovations will weaken; when firms reuse other firms' product components multiple times, the positive effect of boundary-spanning search on new product innovations will be strengthened. We corroborate our hypotheses using data on patents of smartphone manufacturing firms and components of smartphone devices introduced worldwide from 2006 to 2018. We find broad support for our hypotheses. Our findings imply that firms' product component reuses have multifaceted effects on new product innovations and that the attentional coordination of firms' experiences across technology search and product component reuse is critical in shaping new product innovations.

Understanding how science and technology advance has long been of interest to diverse scholarly communities. Thus far, however, such understanding has not been easy to map to, and thus to improve, the operational practice of research and development. Indeed, one might argue that the operational practice of research and development, particularly its exploratory research half, has become less effective in recent decades. In this paper, we describe a rethinking of how science and technology advance, one that is consistent with many (though not all) of the perspectives of the scholarly communities just mentioned, and one that helps bridge the divide between theory and practice. The result is an architecture we call “Bell's Dodecants,” to reflect its six mechanisms and two flavors, and their balanced nurturing at Bell Labs, the iconic 20th century industrial research and development laboratory.

The digital transformation of industrial-age sectors changes product architectures and industry architectures, influencing how value is created and captured in emerging digital business ecosystems. In the industrial era, products were designed around modular architectures and complementary assets, and bottlenecks determined who profits from innovation. In the digital era, products emerge on a layered modular architecture, and profiting from innovation is shifting to those who own control points. Despite the centrality of the interplay between the product architecture and industry architecture for value creation and value capture in the digital age, the effects on competitiveness and industry dynamics remain unclear. To fill this void, we draw on the concept of control points, a novel lens to reflect bargaining positions on a layered modular architecture in digital business ecosystems. Based on a case study of 19 companies, industry associations, and consulting firms in the digital business ecosystem of smart farming, we identify strategic control points, technical control points, generic control points, and institutional boundaries as instrumental in determining value creation and value capture positions. We find that actors (i.e., incumbents, diversifying entrants, and new entrants) in emerging digital business ecosystems follow a seesaw pattern in setting control points and acquiring bargaining positions, and propose a framework that allows to analyze the dynamics within digital business ecosystems. Our study offers managerial implications for firms seeking to optimize their ecosystem strategy and policy makers to support the effective development of the institutional context.