Research Policy最新文献

Despite growing calls for a greater internationalization of management research, the discipline still struggles with the challenge of integrating diverse national contexts. While recent decades have seen a change toward a more equitable treatment of all national contexts, the belief that research conducted outside the United States is less generalizable remains strong. In this research note, we explore the general perceptions of what is considered a “typical” study context by associating them with authors' variable tendencies to report threats to external validity. Using a sample of 400 papers from seven top-tier management journals, we find that research based on non-US data tends to report more external validity threats, which makes it appear less generalizable. While the belief that the US constitutes a “typical” study context is shared by both US and non-US author teams, non-US co-authors tend to exhibit a relatively stronger bias against the generalizability of non-US samples in their studies. Collectively, our results contribute to the literature on external validity threats, generalizability, and biases in peer review, while also responding to recent calls for a more diverse and inclusive management research program.

Incumbent firms utilize corporate venture capital (CVC) as a vehicle to enhance their innovative performance. Still, little is known about the central individual in this context: the CVC unit head, who acts as a knowledge broker between portfolio ventures and the parent organization. We combine human capital theory with the attention-based view to investigate the effects of various facets of CVC unit heads' experience on parent firms' innovative inputs in the form of explorative and exploitative patenting and innovative outputs, specifically market and technological breakthrough innovation. Drawing on a dataset of U.S.-listed firms with CVC units, our findings contribute to the CVC literature in three ways. First, we introduce CVC unit heads' career experiences as new individual-level antecedents of parent firms' innovative performance. Second, we enhance the understanding of the CVC-core paradox, which is the tension between exploration and exploitation in the parent firm. Finally, by employing a combination of patents and new product introductions as metrics for innovative performance, we bridge the gap between learning and innovation in extant CVC research, demonstrating that the effects of CVC unit heads include customer-facing outcomes.

Does ethnolinguistic diversity prevent policy adoption? The implementation of the Italian Start-up Act of 2012 in the bilingual (German and Italian) region of Trentino-Alto Adige offers the ideal setting to investigate this question. The Act sets up a scheme of benefits which young firms can access by registering as “innovative start-ups” on a voluntary basis. We find that policy take-up has been persistently lower in areas of the region with more German speakers, as local firms with German-named administrators are less likely to register as start-ups than firms with Italian-named ones. These findings are robust to firm characteristics and regional heterogeneity and are also visible within mixed-language municipalities. Furthermore, text analysis on press sources suggests that this national policy was much more extensively covered in the Italian-language local media, while a survey of local residents indicates that German speakers have lower knowledge of national policies unless they are embedded in multilingual networks.

This paper brings together the literature on regional variability in innovation activity with studies on the role of personality for regional innovativeness. Building on regionally aggregated levels of individual Big Five personality traits obtained from the German Socio-Economic Panel and the Big Five Project, we find that only extraversion has a positive effect on patenting in German regions. This effect is particularly strong in the case of lagging regions. We interpret this finding as an indication of the compensatory role of collaboration for the innovativeness of lagging regions characterized by low levels of business research and development (R&D) and a dominance of small and medium-sized enterprises (SMEs), which demonstrates the need for place-sensitive policies that consider different modes of innovation and emphasize interregional and intraregional learning.

Collaboration and research networks are nowadays central to innovation because they favor knowledge interactions and complex approaches to challenging problems. This study explores the factors underlying the emergence and evolution of innovation networks in the past, using as example the case of Spain, a backward country regarding R&D performance. Combining, for the first time, historical patent data, social network analysis, and discrete choice regression techniques we test distinct institutional, geographical, and sectoral factors that triggered or hampered collaboration over the long term, i.e., the growth in the connections of individual co-patentees within innovation groups. The findings are relevant and demonstrate, inter alia, that in the Spanish case the length of intellectual monopolies did not foster collaboration, while geographical/technological diversification was key to enhance collaborative patterns in the past. The analysis also demonstrates that the likelihood of increasing collaboration over time depended on the initial level of connections (degree) the patentee had, confirming the existence of preferential attachment, even within the context of an emerging and disconnected network. However, belonging to larger innovation groups (size of the network components) did not promote per se greater interactions, suggesting that institutional weaknesses and backward innovation trends prevented the existence of positive payoffs from increased connectivity. The results have direct R&D policy implications for both nowadays developing countries and innovation leaders.

One strategy for promoting female leaders in science and technology professions is to appoint more women to the committees that select leaders. Unfortunately, evidence from other settings, such as committees for selecting judges or professors, suggests this approach does not work. We use a natural experiment to test the idea that organizational norms supporting gender diversity are necessary for representation on “selectorates” to promote gender diversity among leaders in science and technology. Our empirical setting is the standard-setting organization that develops key protocols for Internet hardware and software. We find that when more women are randomly selected for the committee that appoints the organization's leaders, the committee appoints more female leaders, but only after a set of interventions meant to increase members' awareness of the benefits of gender diversity.

This paper estimates the effect of heterogeneous university funding programs within the German Excellence Initiative on a regional firm's probability to innovate by using a multi-valued two-way fixed effects difference-in-differences model. The estimations show that funding an additional Excellence Cluster focused on internationally competitive research within a labor market region increases a regional firm's probability to innovate. This effect is driven by firms within labor market regions receiving a high number of Excellence Clusters. There is no statistically significant effect for receiving a low number of Excellence Clusters. Moreover, we find no consistent statistically significant effect of funding Graduate Schools concentrating on training scientists nor of funding University Strategies promoting the overall long-term plan of a university.

This study represents the first empirical attempt to conduct a cross-country comparison of social economy (SE) enterprises with other enterprises in the development of social and environmental innovation. Using data from a European survey with >16,000 respondents, we estimate a bivariate probit model with correlated random effects to identify the direct and indirect effects of the SE on social and environmental innovation. We demonstrate that the primary impact of SE enterprises on environmental innovation is through their influence on other enterprises. We also identify the specific levers of innovation in SE and non-SE enterprises. Our empirical findings are consistent with previous research on the SE as a laboratory of innovation and a yardstick for transformative change. Our original findings regarding contextual effects highlights a strong implication advocating public policies to promote SE for its assumed benefits as well as the tendency of SE to foster innovation within non-SE enterprises.

We model a key step in the innovation process, hypothesis generation, as the making of predictions over a vast combinatorial space. Traditionally, scientists and innovators use theory or intuition to guide their search. Increasingly, however, they use artificial intelligence (AI) instead. We model innovation as resulting from sequential search over a combinatorial design space, where the prioritization of costly tests is achieved using a predictive model. The predictive model's ranked output is represented as a hazard function. Discrete survival analysis is used to obtain the main innovation outcomes of interest – the probability of innovation, expected search duration, and expected profit. We describe conditions under which shifting from the traditional method of hypothesis generation, using theory or intuition, to instead using AI that generates higher fidelity predictions, results in a higher likelihood of successful innovation, shorter search durations, and higher expected profits. We then explore the complementarity between hypothesis generation and hypothesis testing; potential gains from AI may not be realized without significant investment in testing capacity. We discuss the policy implications.

Our understanding of how and under what conditions organizational innovative climate unfolds its impact on employees' innovative behaviors remains at a nascent stage. To address these questions, this study developed a moderated mediation model of organizational innovative climate and tested it using a three-level, time-lagged design with a sample of 93 organizations, 269 working groups, and 1146 employees. The results show that organizational innovative climate is positively and indirectly related to employees' innovative behaviors through managers' proactive goal regulation. We also find that the indirect linkage between organizational innovative climate and employees' innovative behaviors via managers' proactive goal regulation only emerge in the organizations that faced highly competitive intensity, but not in those with low competitive intensity. These findings provide important insights into how organizational innovative climate diffuses within organizations and which factors may enhance or limit its impact on employees' actions.