Research Policy最新文献

To promote a more environmentally sustainable economy, countries need to broaden their innovation activities to include green technologies. In this process, the increasing global interconnectedness and internationalisation of innovative activities underlines the growing importance of external knowledge linkages. This paper examines how different categories of countries - technological leaders, catching-up countries and follower countries - diversify into green technologies by exploiting different types of external linkages through co-inventions with international partners. The dataset covers 49 countries over a period of 40 years. The results show that it is complementary linkages, rather than external linkages alone, that facilitate related diversification in the green sector. Moreover, while complementary linkages have a significant impact on the ability of catching-up countries and followers to diversify into less complex and widely diffused green technologies, the diversification pattern of leaders is more oriented towards complex technologies in their early stages. Therefore, green technology development policies should actively promote international cooperation as it has the potential to catalyse green catching-up and foster sustainable growth.

Previous research on interfirm collaboration indicates that networks tend to be structurally stable due to path dependence and embedded firms' incentives to preserve their positional advantages. As a result, industry networks often resemble a core-periphery structure where peripheral firms seem to have little or no opportunity to access the core. Yet, under certain conditions, peripheral firms do manage to cross over to the industry center. In this paper, we examine one such condition: a sudden and unexpected change in the external environment. More specifically, we examine the relationship between the occurrence of an industry-level disruptive event and the dynamics of tie formation/dissolution facilitating or inhibiting peripheral firms' progress toward the center of the industry network. We substantiate our investigation by using longitudinal data on the alliance activities of 258 airlines and applying Stochastic Actor-Oriented Models (SAOM). We integrate our statistical analysis with interview material and descriptive network analysis. The findings reveal a variety of patterns of network entry, contributing novel insights to theories on network dynamics, innovation, as well as policy and practice.

This paper studies the potentially heterogeneous effects that innovative asset-seeking foreign direct investments (FDIs) pursued through different entry modes have on the technological innovation of receiving economies. The analysis covers a balanced panel of European regions receiving FDIs between 2003 and 2016, and accounts for the endogeneity of FDI inflows by means of an instrumental variable approach. For greenfield FDIs, we find a negative effect on the patenting output of receiving regions. This is driven by a drop in the patenting output of inventors who have never patented before, in regions with historically high co-patenting of new and experienced inventors. This is consistent with the idea that greenfield subsidiaries recruit some of the best local inventors, disrupting local teams, so that less experienced inventors miss out on interactions with more experienced collaborators. In the case of cross-border mergers and acquisitions, the patenting activity of receiving regions remains unchanged, but for a slight increase in the patenting activity of experienced inventors in the first few years after the acquisition, possibly to show their value to the entrant multinational enterprise (MNE). Our findings suggest that policies aimed at attracting greenfield FDIs could be combined with those aimed at embedding newly established subsidiaries in the local environment. For instance, entrant MNEs could be required to engage with local actors in collaborative R&D activities and in the development of local skills, in order to access the economic incentives (e.g., R&D tax credits, grants and subsidies) that are often devised to attract innovative greenfield FDIs.

The current state of scientific research is disappointing due to the lack of significant breakthroughs, despite an ever-increasing number of publications and substantial resources invested in R&D activities. This paper proposes a signaling model as a complementary explanation to this phenomenon. If managers of research institutions can observe publications but are unable to observe breakthrough innovations, low-skilled scholars might reduce their investment in exploratory research and instead invest time in publishing as many papers as high-skilled scholars. This would allow them to claim the same level of compensation. In response to the imitation by low-skilled scholars, high-skilled scholars would publish even more, reaching a point where low-skilled scholars would abandon the imitation strategy. This mechanism leads to an equilibrium with (1) insufficient investment in exploratory research by high-skilled scholars, (2) excessive focus on publishing papers, (3) reduced effectiveness of resource-based incentives for exploratory research, and (4) reduced effectiveness of reward-based incentives for research.

Building on the case of European Union (EU) regions, we study the macroeconomic impact of related diversification. We use an indicator of technological related variety in combination with stochastic frontier estimation and a well-established general equilibrium model to assess the rationale for related diversification and to understand the relevance of different region-specific policies. The results suggest that related diversification has a greater potential for less advanced regions than for more advanced ones. This has interesting implications for industrial policy, calling for a differentiated approach depending on the technological space and level of development of different regions.

Today, scientific knowledge is predominantly disseminated in English. We show that global universities’ research performance, as measured by publications in top journals, declines as the differences between their local language and English increase. This effect is robust to controls for university factors like proportion of international staff and faculty-to-student ratio, as well as country-level factors like economic development, youth academic achievement, university degree rate, politics, culture, trade with and geographic distance to English-speaking countries, among others. This quantification of the research performance penalties induced by linguistic distance from the lingua franca may inform policy makers who must balance trade-offs between embracing English against cultural and local labor market pressures to orient around the local language.

A growing body of research documents that the size and growth of an industry in a location depends on how much related activity is found there. This fact is commonly referred to as the “principle of relatedness”. However, there is no consensus on why we observe the principle of relatedness, how to best operationalize it empirically or how this empirical regularity can help inform local industrial policy. We try to make progress by performing a structured search over tens of thousands of specifications to identify robust procedures to determine how well industries fit the local economies of US cities that perform well in terms of out-of-sample predictions. To do so, we use data that allow us to derive relatedness from observing which industries co-occur in the portfolios of establishments, firms, cities and countries. Portfolios of these different productive entities yield different relatedness matrices, each of which helps predict the size and growth of local industries. However, our specification search not only identifies ways to improve the performance of such predictions, but also reveals new facts about the principle of relatedness and important trade-offs between predictive performance and interpretability. We use these insights to deepen our theoretical understanding of what underlies path-dependent development in cities and expand existing policy frameworks that leverage information from inter-industry relatedness analysis.

How does the increasing use of robots affect the mental health of workers? To investigate this question, we combine individual mental health data from the German Socioeconomic Panel with data on the stock of robots in 14 manufacturing sectors provided by the International Federation of Robotics for the period 2002–2018. Using mediation analysis and an instrumental variable approach, we find that higher robot intensity is associated with deteriorating mental health, an effect that is mainly driven by worries about job security and a lower sense of achievement on the job. A heterogeneity analysis reveals that higher robot intensity has particularly severe negative effects on the mental health of workers close to retirement, in low-skilled occupations and performing routine jobs. Women and men are affected similarly, as are workers of all educational levels. Our results indicate the presence of hidden (health) costs of automation that policymakers need to address.

Counterfeiting challenges firms to capture the value created by product innovation. We characterize style and quality as key dimensions of product innovation strategy in contexts where aesthetic attributes drive product success. We examine distinct aesthetic innovation strategies that firms may use to innovate their existing products — developing new style variants, using higher quality attributes, or both. Our empirical test exploits unique data on authentic plastic model kits matched to product-specific counterfeits. Controlling for several confounders, we find that new style variants that include higher quality attributes are 20 % more likely to be copied relative to style variants that do not. We discuss implications for aesthetic innovation strategies in weak appropriability regimes.

This paper provides new evidence on the increasing dispersion in wages and productivity using a unique micro-aggregated firm-level data source, representative for the full population of firms in 12 countries. First, we document an increase in wage and productivity dispersions, for both manufacturing and market services, and show that the increase is mainly driven by the bottom of the wage and productivity distributions. Second, we show that between-firm wage dispersion increased more in sectors that experienced an increase in productivity dispersion; the estimated elasticity is larger at the bottom than at the top of the wage/productivity distributions, consistent with a framework in which more productive firms charge higher mark-ups and/or larger wage mark-downs. Third, we find that both globalisation and digitalisation strengthen the link between productivity and wage dispersion. Our results suggest that policies designed to mitigate wage inequality must take into consideration gaps between firms of the same sectors, and how both globalisation and digitalisation affect these gaps.