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on Innovation |
| By: | Christoph Grimpe; Fuad Hasanov; Wolfgang Sofka; Geoffrey Borchardt; Philip Schulz |
| Abstract: | A well-functioning market for technology, or ideas, is an important determinant for the type, scope, and distribution of innovation activities. We use a panel of 20 industries across 24 European countries to study the key determinants driving the market for technology. We explore whether the expenditures on external knowledge depends on the sectoral pattern of innovation and an industry’s distance to the global technological frontier. Disseminating knowledge and technology within the industry, bringing it closer to the global technological frontier, tends to reduce the expenditures for external knowledge except in supplier-dominated industries. We also find important complementarity effects in the market for external knowledge. Industries with high R&D spending, with increasingly large firms, and with large investments in machinery and software foster growth of the market for technology. Our findings suggest tailoring innovation policies to help expand both the size of the market for technology and the use of these markets in specific industries. |
| Keywords: | Markets for technology; patterns of innovation; industry studies; R&D; external knowledge; industrial policy |
| Date: | 2025–01–17 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2025/020 |
| By: | Paolo Carioli; Dirk Czarnitzki; Gastón P Fernández Barros |
| Abstract: | Artificial Intelligence (AI) is considered to be the next general-purpose technology, with the potential of performing tasks commonly requiring human capabilities. While it is commonly feared that AI replaces labor and disrupts jobs, we instead investigate the potential of AI for overcoming increasingly alarming skills shortages in firms. We exploit unique German survey data from the Mannheim Innovation Panel on both the adoption of AI and the extent to which firms experience scarcity of skills. We measure skills shortage by the number of job vacancies that could not be filled as planned by firms, distinguishing among different types of skills. To account for the potential endogeneity of skills shortage, we also implement instrumental variable estimators. Overall, we find a positive and significant effect of skills shortage on AI adoption, the breadth of AI methods, and the breadth of areas of application of AI. In addition, we find evidence that scarcity of labor with academic education relates to firms exploring and adopting AI. |
| Keywords: | Artificial Intelligence, CIS data, skills shortage |
| Date: | 2024–02–08 |
| URL: | https://d.repec.org/n?u=RePEc:ete:ceswps:735893 |
| By: | Ruiz, Walter; Spinola, Danilo; Villalba, Maria Luisa |
| Abstract: | This paper develops an Agent-Based Model (ABM) to study the impact of Science, Technology, and Innovation (STI) policies on innovation systems. The model, which we call the Adaptive Innovation System Model (AdaptISM), simulates the technological innovation capabilities required for knowledge and technology generation, diffusion, and utilisation, integrating decision rules that capture the emergent behaviours of agents interacting with innovation opportunities. The model is empirically validated using data from the coffee and avocado agricultural production chains (APCs) in Antioquia, Colombia, which are two sectors of regional economic and local importance. The validation process allows the evaluation of individual and combined STI policy modes, identifying which policy strategies most effectively enhance innovation performance and economic outcomes. By enabling the exploration of “what-if” scenarios, the ABM provides a tool to assess STI policy contributions systematically and offers practical insights into resource allocation in local innovation systems. This approach addresses a critical challenge in innovation policy design: understanding how STI policies influence system performance. The findings highlight the utility of combining policy approaches to improve innovation and economic growth, offering a replicable framework for policymakers and researchers seeking to optimise the performance of innovation systems. |
| Keywords: | STI policy; innovation systems; agricultural production chains; Agent-based modelling |
| Date: | 2025–01–20 |
| URL: | https://d.repec.org/n?u=RePEc:akf:cafewp:32 |
| By: | Jean-Michel Benkert; Igor Letina |
| Abstract: | We provide a model of investment in innovation that is dynamic, features multiple heterogeneous research projects of which only one potentially leads to success, and in each period, the researcher chooses the set of projects to invest in. We show that if a search for innovation starts, it optimally does not end until the innovation is found -- which will be never with a strictly positive probability. |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2412.03227 |
| By: | Ga\'etan de Rassenfosse |
| Abstract: | This article is part of a Living Literature Review exploring topics related to intellectual property, focusing on insights from the economic literature. Our aim is to provide a clear and non-technical introduction to patent rights, making them accessible to graduate students, legal scholars and practitioners, policymakers, and anyone curious about the subject. |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2412.14370 |
| By: | Eric BOND; HOANG Trang; MA Yan; MAKIOKA Ryo |
| Abstract: | The paper studies the effect of R&D investments by parent multinational corporations (MNC) and their affiliates on the decisions of those affiliates to purchase intermediate inputs across different locations. We first develop a theoretical model of R&D and sourcing decisions to provide potential mechanisms and to guide our empirical analysis. Our fixed-effects regression results imply that, first, higher affiliate R&D expenditures are associated with a higher share of the affiliate’s purchases from local firms. Second, higher R&D expenditures by affiliates in other countries (i.e., those under the same parent firm but located in a different foreign country) are associated with a higher share of affiliate purchases from those countries. Third, we find that the affiliate’s R&D expenditures are negatively correlated with the purchase share from the parent home country and from the parent firm. |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:eti:dpaper:25007 |
| By: | Ginger Zhe Jin; Mario Leccese; Liad Wagman |
| Abstract: | This chapter examines the multifaceted interactions between top digital platforms and technology ventures across capital, labor, innovation, and product markets. Exploring how venture investments, talent flows, strategic alliances, and competitive behaviors can shape the innovation ecosystem, the chapter highlights both the complementary and competitive dynamics between large incumbents and smaller entrants, and the benefits and potential inefficiencies that may arise from them, as demonstrated by the empirical and theoretical literatures. Throughout, the chapter identifies key areas for research that can support a rigorous evaluation of policy proposals concerning evolving market structures in the digital economy. |
| JEL: | D4 L1 O3 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33370 |
| By: | Marina Martinelli; Andr\'e Tosi Furtado |
| Abstract: | This paper is a comprehensive exploring of technology capability in 5G/6G TIS, explicitly focusing on the potential of remote surgery globally and in Germany. The paper's main contribution is its ability to anticipate new debates on the interplay between TIS and contexts, with particular emphasis on the national and international levels. Our findings, derived from a Bibliometrics study of industry-academic relationships, highlight crucial collaborations in Germany, positioning the country as a strategic actor in international TIS and, by extension, in applying 5G/6G technological systems to remote surgery due to its knowledge production capability. We propose policies that can stimulate interaction between smaller suppliers and larger companies, which can act as intermediaries and provide access to international markets. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.17899 |
| By: | Huang, Jiayi (Cardiff Business School); Zhou, Peng (Cardiff Business School) |
| Abstract: | Open innovation serves as a critical pathway for aligning Sustainable Business Models (SBMs) with the dual imperatives of the sustainable economy and the digital economy. This editorial review synthesizes insights from theoretical frameworks, particularly the Resource-Based View (RBV) and Transaction Cost Theory (TCT), integrated with the Technology-Organization-Environment (TOE) framework to explore the mechanisms driving open innovation. Our editorial review highlights key dimensions influencing open innovation: technology (digital platforms, emerging technologies like AI, IoT, and blockchain), organization (stakeholder collaboration, governance mechanisms), and environment (regulatory frameworks, market dynamics, and industrial spillovers). This unified framework offers actionable insights for policymakers to foster enabling ecosystems and for business leaders to adopt open innovation strategies for resource optimization and governance improvement. The review concludes that the RBV-TCT-TOE framework provides a generalizable and robust tool for understanding and advancing open innovation across industries and regions, bridging theoretical and practical dimensions to address the challenges of sustainability and digital transformation. |
| Keywords: | Open Innovation; Entrepreneurship; Sustainable Business Model |
| JEL: | O36 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdf:wpaper:2025/2 |
| By: | Payal Malik (Indian Council for Research on International Economic Relations (ICRIER)); Nikita Jain; Shiva Kanwar; Bhargavee Das; Saloni Dhadwal |
| Abstract: | Artificial Intelligence (AI) technologies are becoming integral to businesses and public markets alike, enabling innovation and efficiency and creating avenues for economic growth. The emphasis in public discourse has been on the technological advances enabled by AI and the risks and benefits associated with them. It is equally important that discussions on market implications of firm behavior active in AI are also understood. This report explores the evolving market dynamics in India and the critical challenges faced by policymakers and regulators in creating a competitive and innovative AI ecosystem. The report also examines the AI technology stack, highlighting its distinct layers and their implications for industrial organization and market competition. Key themes include the role of major cloud providers in shaping the AI ecosystem, the complexities of open-source models, the expanding network of partnerships between global technology companies, AI startups, and domestic IT incumbents, and the creation of new dependencies. Drawing on global best practices, the report emphasizes the need for a nuanced mix of competition and industrial policies, including a Digital Public Infrastructure paradigm, to foster a competitive, inclusive, and innovative AI ecosystem in India. It also highlights India's push for technological sovereignty through initiatives like the IndiaAI Mission and investments in indigenous AI models and supercomputing capabilities. The recommendations proposed in the report include promoting interoperability, enhancing access to computing resources, strengthening data-governance frameworks while facilitating access to high-quality open datasets, and leveraging public-private partnerships to support emerging AI startups. |
| Keywords: | Artificial Intelligence, Competition Policy, Generative AI, Digital Public Infrastructure, Data Governance, AI Regulation, Prosus, icrier |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:bdc:report:25-r-01 |
| By: | Matthew R. Denes; Spyridon Lagaras; Margarita Tsoutsoura |
| Abstract: | Platform intermediation of goods and services has considerably transformed the U.S. economy. We use administrative data on U.S. tax returns to study the role of the gig economy on entrepreneurship. We find that gig workers are more likely to become entrepreneurs, particularly those who are lower income, younger, and benefit from flexibility. We track all newly created firms and show that gig workers start firms in similar industries as their gig experience, which are less likely to survive and demonstrate higher performance. Overall, our findings suggest on-the-job learning promotes entrepreneurial entry and shifts the types of firms started by entrepreneurs. |
| JEL: | G30 J21 J22 J24 L26 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33347 |
| By: | Bracht, Felix; Verhoeven, Dennis |
| Abstract: | If air pollution harms innovation — and therefore future productivity — existing assessments of its economic cost are incomplete. We estimate the effect of fine particulate matter concentration on inventive output in 977 European regions. Exploiting thermal inversions and weather-induced ventilation of pollutants for identification, we find that a decrease in air pollution equivalent to the average yearly drop in Europe leads to 1.2% more patented inventions in a given region. A back-of-the-envelope calculation suggests that accounting for the effect on innovation increases the economic cost of air pollution as assessed in prior work by about three quarters. |
| Keywords: | air pollution; air quality; innovation; productivity |
| JEL: | R14 J01 N0 |
| Date: | 2025–03–31 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:126875 |
| By: | Bello, S.; Reiner |
| Abstract: | Given the rapid increase in green hydrogen research funding and the hopes that this will help drive cost reductions, it is important to incorporate the latest RD&D spending into the estimation of the learning rate for electrolysis technologies. Thus, we develop a two-factor experience curve model with spillovers and economies of scale that allows us to estimate learning rates for both alkaline and PEM electrolysis technologies using both global- and country-level data from OECD countries. Our research strategy allows us to mitigate estimation or omitted variable bias from ignoring technology-push measures, unobserved country-specific characteristics, and knowledge spillovers. Using an OECD cross-country dataset over 2000-2022, we estimate global learning-by-doing rates of 17.5 %-46.8% and global learning-by-researching rate of 9%-42.3% for electrolysis technologies after incorporating learning parameter estimates into the progress equation. When we allow for spillovers, we find a linear relationship between PEM technology and alkaline technology improvements. Based on our OECD panel dataset, which incorporate more observations, we estimate learning-by-doing rates of 0.6%-9.4% and learning-by-researching rates of 4.0%-19.9%. In addition, country-level electrolysis cost is reduced by about 28% for the sample period 2000-2022 because of global experience spillover effects. Therefore, our empirical findings suggest that the role of technology-push measures remains critical for promoting and achieving cost improvements of electrolysis technologies. Furthermore, the absorptive capacity of a country should be improved to maximise the benefits of spillovers from global learning. |
| Keywords: | Green Hydrogen Technology, Experience Curves, RD&D Spending, Global and OECD, Cost Reductions |
| JEL: | O30 C50 Q42 Q55 |
| Date: | 2024–12–18 |
| URL: | https://d.repec.org/n?u=RePEc:cam:camdae:2476 |
| By: | Vanya Georgieva |
| Abstract: | Industrial policy has gained popularity in recent years and across all regions and income levels. Consequently, it is increasingly important to understand how governments choose the sectors they target. This analysis explores the role of domestic production networks in sector targeting, while controlling for other sector and global value chain characteristics. Combining datasets on industrial policy (Global Trade Alert) and input-output linkages (ICIO, OECD) provides novel insight into the network features of industrial policy. In particular, a sector’s ‘centrality’—i.e., its degree of connectedness - within the domestic production network is an important and significant predictor of sector intervention. The results indicate that industrial policy is used differently across regions, income groups, time periods, and types of policy tools. Notably, emerging economies tend to target more central sectors, while advanced economies target less central ones, on average. However, there has been a global shift toward more central sectors over time. Lastly, subsidies are deployed on more central sectors, while tariffs are used on less central ones. |
| Keywords: | Industrial Policy; Trade Policy; Subsidies; Global Value Chains; Production Networks; Spillovers |
| Date: | 2025–01–17 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2025/023 |