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on Innovation |
| By: | D’Alessandro, Francesco (Department of Sociology and Business Law, University of Bologna); Santarelli, Enrico (Department of Economics, University of Bologna); Vivarelli, Marco (Università Cattolica del Sacro Cuore) |
| Abstract: | This study examines how regional technological relatedness and local AI knowledge influence regional innovative activity, as measured by patenting activity. Using a novel three-way longitudinal dataset and leveraging a deep learning-based identification of AI patents, we show that two broad mechanisms operate in parallel. First, in accordance with the extant literature, technologies that are cognitively close to a region’s existing patent portfolio enjoy higher patenting activity, confirming that relatedness remains a strong and persistent predictor of innovative output. Second, local AI endowments are positively associated with patenting across technological fields, even after conditioning on relatedness, indicating that AI plays an enabling and cross-cutting role in a given regional innovation system. Moreover, the interaction between relatedness and AI turns out to be negative and statistically significant, implying that AI attenuates the extent to which local innovative efforts depend on the technology’s proximity to the regional portfolio. In sum, AI appears to enhance overall local innovative activity while reducing its reliance on pre-existing regional knowledge structures. |
| Keywords: | Artificial Intelligence, AI, technological change, regional innovation, relatedness |
| JEL: | O31 R11 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18817 |
| By: | Bergeaud, Antonin; Deter, Max; Greve, Maria; Wyrwich, Michael |
| Abstract: | We investigate the causal relationship between inventor migration and regional innovation in the context of the large-scale migration shock from East to West Germany between World War II and the construction of the Berlin Wall in 1961. Leveraging a newly constructed, century-spanning dataset on German patents and inventors, along with an innovative identification strategy based on surname proximity, we trace the trajectories of East German inventors and quantify their impact on innovation in West Germany. Our findings demonstrate a significant and persistent boost to patenting activities in regions with higher inflows of East German inventors, predominantly driven by advancements in chemistry and physics. We further validate the robustness of our identification strategy against alternative plausible mechanisms. We show in particular that the effect is stronger than the one caused by the migration of other high skilled workers and scientists. |
| Keywords: | Patents; Migration; Germany; Innovation |
| JEL: | H10 N44 P20 D31 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19837 |
| By: | Martinez, Marco; Nuvolari, Alessandro; Vasta, Michelangelo |
| Abstract: | This paper provides new evidence on the nexus between railroads and inventive activities in Italy in the period 1861-1936. We develop two new georeferenced datasets on railway stations and patents. By adopting the staggered difference in differences identification strategy by Callaway and Sant’Anna (2021), we show that the impact of railroad construction on innovation is only visible for the first wave of construction of the period of the Destra storica (1861-1878), when the network was expanded following a state building strategy. However, these effects became noticeable only after more than two decades and concern mostly independent inventors and low-quality patents. |
| Keywords: | Italy |
| JEL: | O31 O33 N73 L92 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19812 |
| By: | Carioli, Paolo (KU Leuven, Dept. of Management, Strategy and Innovation); Czarnitzki, Dirk (KU Leuven, Dept. of Management, Strategy and Innovation; Center for R&D Monitoring (ECOOM) at KU Leuven, and Leibniz Centre for European Economic Research (ZEW), Mannheim); Fernández, Gastón P. (Luxembourg Institute of Socio-Economic Research (LISER)) |
| 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 shortage on academic qualifications and STEM skills relates to firms adopting AI. |
| Keywords: | Artificial Intelligence, skills shortage, CIS data |
| JEL: | J23 J24 O33 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18793 |
| By: | Carvalho, V. M.; Freund, L. B. |
| Abstract: | We develop a theory of growth in which firms forage in idea space. A firm exploits a patch of related ideas, gradually exhausting opportunities for quality improvement, and then searches for a new patch. We cast this explore-exploit tradeoff as a tractable optimal-stopping problem and embed it in an endogenous-growth model. The composition of innovation—improving existing ideas versus discovering new ground—emerges as an equilibrium object. To construct an empirical representation of the idea space, we apply natural language processing to patent text data. The data support the theory’s central premises: returns to local exploitation diminish; firms stay longer on richer patches; and entry into new patches yields more and better patents. We calibrate the model to U.S. data and establish two results, on the composition of growth and on its pace. First, at a twenty-year horizon, patenting in new clusters accounts for over half of growth from quality improvements: sustained growth rests on firms continually entering new territory. Second, the model sign-identifies the origins of the productivity slowdown of the last four decades: exploitation spells have not shortened, weighing against worsening exploitation and tentatively pointing to harder exploration. |
| Keywords: | Innovation, Growth, Firm Dynamics, Foraging, Exploration and Exploitation, Patents, Natural Language Processing, Artificial Intelligence |
| JEL: | O31 O41 O33 O40 O47 |
| Date: | 2026–06–15 |
| URL: | https://d.repec.org/n?u=RePEc:cam:camdae:2659 |
| By: | Taghizadeh, Rahim (Department of Industrial Engineering, Urmia University of Technology, West Azerbaijan, Urmia, Iran.); Babazadeh Behestani, Salar (Allameh Tabatabaei University, Tehran, Iran.); Arabsheibani, Reza (London School of Economics) |
| Abstract: | generally a consensus remains elusive regarding the optimal method for measuring the effects of technological change and innovation on employment. This study introduces a Technological Change Composite Indicator (TCI), constructed using Principal Component Analysis (PCA) to synthesize seven firm-level innovation metrics. This methodology mitigates issues associated with multicollinearity in regression analyses involving correlated variables. The proposed TCI serves as a proxy for technological change to examine its association with employment in manufacturing sectors across 10 European Union countries and 17 seventeen manufacturing sectors with country fixed effects and a one‑year time lag. We find that a one‑unit increase in the TCI corresponds to a 0.58% higher employment level. The association is positive and statistically significant, indicating that a multidimensional measure of technological change outperforms traditional single proxies such as R&D expenditure or patent counts. By moving beyond narrow indicators, our approach offers a more reliable empirical basis for understanding the employment implications of technological change, including emerging technologies such as AI. |
| Keywords: | composite indicator, latent approach, technological change, employment, manufacturing industry, PCA analysis, regression method |
| JEL: | O33 J23 O14 C38 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18814 |
| By: | Fulvio Castellacci; Tommaso Ciarli; Yuan Gao; Marianna Marino; Giacomo Marzi; Massimo Riccaboni; Maria Savona; Simone Vannuccini |
| Abstract: | This paper examines the tension between the benefits of generative artificial intelligence (AI) for scientific research and the unresolved governance questions that accompany its rapid adoption. Drawing on an academic roundtable held at the AI for Science and Innovation Workshop (Scuola IMT Alti Studi Lucca, April 2026) and on a fast-expanding empirical literature, it maps the disagreement within the research community across four stages of the research process: funding, research tasks, publication and peer review, and use and uptake. The empirical case for AI's productivity, augmentation, and democratization effects has strengthened. The picture changes once productivity is disaggregated: AI-assisted work shows measurable gains in publication volume and citation share, while the evidence on novelty, disruption, and breakthrough output remains ambiguous or negative. We argue that the divergence between private and social returns arises through three analytically distinct mechanisms, namely information asymmetry, negative externalities on a shared knowledge base, and depletion of research capacity, and that each calls for a different governance instrument. We propose Responsible Research with AI (RRAI), an extension of the Responsible Research and Innovation tradition organized around four principles that operate at different levels of the research system: disclosure, differentiation, narrative, and proportionality. RRAI builds on existing institutional scaffolding, including the EU AI Act, UNESCO, and the OECD, and aims to preserve AI's productivity gains while addressing systemic risks that individual researchers can neither observe nor manage on their own. |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.24879 |
| By: | OECD |
| Abstract: | The ability of innovative start-ups to scale is a key driver of productivity and economic growth. This paper examines the factors associated with successful scaling among start-ups founded between 2000 and 2025 in the European Union (EU) and the United States (US). It distinguishes between growth-oriented firms (raising at least USD 50 million) and rising superstars (valuations above USD 1 billion), comparing their characteristics across innovation, finance, market expansion, talent, and local ecosystems. Differences in scaling outcomes relate to the timing and commercialisation of innovation (rather than inventive capacity per se), the depth of late-stage financing, and the ability to mobilise managerial capabilities and acquisitions. Scaling events are also associated with distinct ecosystem spillovers, though these depend on ecosystem depth and type of scaling event. Overall, scaling is a cumulative, selective process in which firms progressively overcome interrelated constraints, underscoring the need for stage- and ecosystem-specific scale-up policies. |
| Keywords: | entrepreneurial ecosystems, innovation, scale-up gap, scale-ups, start-ups, unicorns, venture capital |
| JEL: | G24 G28 L25 L26 R11 |
| Date: | 2026–08–07 |
| URL: | https://d.repec.org/n?u=RePEc:oec:stiaaa:2026/08-en |
| By: | Anna D’annunzio (UNINT - Università degli Studi Internazionali di Roma = University of International Studies of Rome); Yassine Lefouili (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Bruno Jullien (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Leonardo Madio (Unipd - Università degli Studi di Padova = University of Padua) |
| Abstract: | This paper examines how horizontal mergers affect firms' incentives to invest in R&D leading to the development of new products. We characterize the impact of a merger to monopoly and a 3-to-2 merger on equilibrium innovation efforts and consumer surplus, absent efficiency gains and spillovers. We show that a 3-to-2 merger directly alters the outsider's innovation incentives by shifting its best-response function upward, and we analyze how this mechanism affects merger outcomes for innovation and consumer surplus. Finally, we examine how efficiency gains and remedies modify post-merger innovation efforts. |
| Keywords: | R&D Investments, Amp, Product Innovation, Horizontal Mergers |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05680914 |
| By: | Fey, Sascha |
| Abstract: | Carrying out innovation projects is no easy task in a world characterized by constant change and uncertainty. Adversities such as saving targets, budget cuts, interpersonal conflicts, absenteeism, or employee turnover can significantly impact project progress. Given these circumstances, the question is not "if" but rather "when" a project will be affected by such problems. The concept of resilience is a promising approach to dealing with difficulties in everyday project management. The goal of Innovation Resilience Behaviour, a specific form of resilience, is to equip projects with the necessary tools to detect deviations from the project plan as early as possible and take all necessary measures to get back on track. The existing literature on resilience has shown increasing interest in the topic during recent years. Emanating from social psychology, the construct has demonstrated relevance in other fields as well, such as organizational research. However, Innovation Resilience Behaviour as a specialized field in project management has not yet been examined in depth or empirically tested on a large scale beyond the seminal articles. As part of this study, the author examined 87 innovation projects of a large German logistics service provider, analyzing the relationship between Innovation Resilience Behaviour and project success, as well as four potential moderators (adversities, dispersion, use of communication media, technological innovativeness) and four possible antecedents (trust, identification, goal clarity, top management support) of Innovation Resilience Behaviour. The results show a clear and positive relationship between Innovation Resilience Behaviour and project success. However, three of the four expected moderators did not exhibit the predicted effects—only adversity had a moderating influence on the relationship between Innovation Resilience Behaviour and project success. Regarding the antecedents, this study demonstrates that Identification, goal clarity, and top management support have a significant positive influence on the development of Innovation Resilience Behaviour. The findings of this study contribute to the existing literature, particularly in the following ways: They expand and provide empirical validation of Innovation Resilience Behaviour beyond the previously published seminal articles. The study is conducted at the team level. Several researchers have previously pointed out that the team level has been largely neglected in studies on (innovation) projects in the corporate sector. Confirming Innovation Resilience Behaviour as an important factor for project success also provides team leaders, project managers, and executives with a useful and practical set of tools that allows them to respond individually and effectively to threats or deviations from the project plan. |
| Date: | 2026–05–27 |
| URL: | https://d.repec.org/n?u=RePEc:dar:wpaper:160986 |