create a website

The US university-industry link in the R&D of AI: Back to the origins?. (2024). Llerena, Patrick ; Borsato, Andrea.
In: Working Papers of BETA.
RePEc:ulp:sbbeta:2024-46.

Full description at Econpapers || Download paper

Cited: 0

Citations received by this document

Cites: 65

References cited by this document

Cocites: 37

Documents which have cited the same bibliography

Coauthors: 0

Authors who have wrote about the same topic

Citations

Citations received by this document

    This document has not been cited yet.

References

References cited by this document

  1. Abbonato, D., Bianchini, S., Gargiulo, F., & Venturini, T. (2024). Interdisciplinary Research in Artificial Intelligence: Lessons from COVID-19. Quantitative Science Studies, 1-20.
    Paper not yet in RePEc: Add citation now
  2. Aghion, P., Jones, B. F., & Jones, C. I. (2019). 9. Artificial Intelligence and Economic Growth. University of Chicago Press.
    Paper not yet in RePEc: Add citation now
  3. Agrawal, A., McHale, J., & Oettl, A. (2019). 5. Finding Needles in Haystacks: Artificial Intelligence and Recombinant Growth. University of Chicago Press.
    Paper not yet in RePEc: Add citation now

  4. Agrawal, A., McHale, J., & Oettl, A. (2023). Superhuman science: How artificial intelligence may impact innovation. Journal of Evolutionary Economics, 33(5), 1473-1517.

  5. Ahmed, N., & Wahed, M. (2020). The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research. arXiv preprint arXiv:2010.15581.
    Paper not yet in RePEc: Add citation now
  6. AI Adoption in America: Who, What, and Where. National Bureau of Economic Research. https://www.nber.org/papers/w31788 Mowery, D. C. (1992). The US national innovation system: Origins and prospects for change. research policy, 21(2), 125–144.
    Paper not yet in RePEc: Add citation now
  7. Bianchini, S., Bottero, P., Colagrossi, M., Damioli, G., Ghisetti, C. & Michoud, K., Mapping the Scientific Base for SDGs and Digital Technologies, Publications Office of the European Union, Luxembourg, 2023, doi:10.2760/237170, JRC133613.
    Paper not yet in RePEc: Add citation now

  8. Bianchini, S., Müller, M., & Pelletier, P. (2022). Artificial intelligence in science: An emerging general method of invention. Research Policy, 51(10), 104604.

  9. Boden, M. A. (2016). AI: Its nature and future. Oxford University Press.
    Paper not yet in RePEc: Add citation now

  10. Borsato, A. (2024). Does the Secular Stagnation hypothesis match the data? Evidence from the USA. Journal of Post Keynesian Economics, 47(2), 346-374.

  11. Borsato, A., & Lorentz, A. (2023). Data production and the coevolving AI trajectories: an attempted evolutionary model. Journal of Evolutionary Economics, 33(5), 1427-1472.

  12. Bresnahan, T. (2019). Artificial intelligence technologies and aggregate growth prospects. Prospects for Economic Growth in the United States.
    Paper not yet in RePEc: Add citation now
  13. Bresnahan, T. F., & Trajtenberg, M. (1995). General purpose technologies ‘Engines of growth’? Journal of econometrics, 65(1), 83–108. https://doi.org/10.1016/0304-4076(94)01598-T Brynjolfsson, E., Rock, D., & Syverson, C. (2018). Artificial intelligence and the modern productivity paradox: A clash of expectations and statistics. In The economics of artificial intelligence: An agenda (pp. 23–57). University of Chicago Press. https://www.nber.org/system/files/chapters/c14007/c14007.pdf Bush, V. (1945). Science, the endless frontier. In Science, the Endless Frontier. Princeton University Press.
    Paper not yet in RePEc: Add citation now
  14. Callaway, E. (2022). What’s next for the AI protein-folding revolution. Nature, 604, 234–238.
    Paper not yet in RePEc: Add citation now
  15. Chandler, A. D. (1990). Scale and scope: The dynamics of industrial capitalism. Harvard University Press.
    Paper not yet in RePEc: Add citation now
  16. Cobban, A. B. (1992). Universities: 1100-1500. González Cuevas, Oscar Manuel, El Concepto de Universidad, México: Universidad Autónoma Metropolitana.
    Paper not yet in RePEc: Add citation now

  17. Cockburn, I. M., Henderson, R., & Stern, S. (2018). The impact of artificial intelligence on innovation. National bureau of economic research.

  18. Cohendet, P., & Llerena, P. (2010). The knowledge-based entrepreneur: The need for a relevant theory of the firm. In Knowledge Intensive Entrepreneurship and Innovation Systems, ed. Malerba, F. (pp. 55–75). Routledge.
    Paper not yet in RePEc: Add citation now
  19. DeCost, B. L., Hattrick-Simpers, J. R., Trautt, Z., Kusne, A. G., Campo, E., & Green, M. L. (2020). Scientific AI in materials science: A path to a sustainable and scalable paradigm. Machine learning: science and technology, 1(3), 033001.
    Paper not yet in RePEc: Add citation now

  20. Dosi, G., Llerena, P., & Labini, M. S. (2006). The relationships between science, technologies and their industrial exploitation: An illustration through the myths and realities of the so-called ‘European Paradox’. Research policy, 35(10), 1450–1464.

  21. Etzkowitz, H., & Leydesdorff, L. (1997). Universities and the global knowledge economy: A triple helix of university-industry relations. Preprint Version of: Etzkowitz, H., & Leydesdorff, L.(1997).
    Paper not yet in RePEc: Add citation now

  22. Etzkowitz, H., & Leydesdorff, L. (2000). The dynamics of innovation: From National Systems and “Mode 2” to a Triple Helix of university–industry–government relations. Research policy, 29(2), 109–123.

  23. Flamm, K. (1988). Creating the computer: government, industry, and high technology. Brookings Institution Press.
    Paper not yet in RePEc: Add citation now

  24. Furman, J. L., & Teodoridis, F. (2020). Automation, research technology, and researchers’ trajectories: Evidence from computer science and electrical engineering. Organization Science, 31(2), 330–354.

  25. Furman, J., & Seamans, R. (2019). AI and the Economy. Innovation policy and the economy, 19(1), 161–191. https://doi.org/10.1086/699936 Geuna, A. (1999). The economics of knowledge production: funding and the structure of university research. Edward Elgar Publishing.
    Paper not yet in RePEc: Add citation now
  26. Gibney, E. (2022). Is AI fuelling a reproducibility crisis in science? Nature, 608, 250–251.
    Paper not yet in RePEc: Add citation now

  27. Godin, B., & Gingras, Y. (2000). The place of universities in the system of knowledge production. Research policy, 29(2), 273–278.

  28. Gordon, R. J. (2015). Secular stagnation: A supply-side view. American economic review, 105(5), 54-59.

  29. Gundersen, O. E., & Kjensmo, S. (2018). State of the art: Reproducibility in artificial intelligence.
    Paper not yet in RePEc: Add citation now

  30. Holm, J. R., Hain, D. S., Jurowetzki, R., & Lorenz, E. (2023). Innovation dynamics in the age of artificial intelligence: Introduction to the special issue. Industry and Innovation, 30(9), 1141–1155. https://doi.org/10.1080/13662716.2023.2272724 Hounshell, D. A., & Smith, J. K. (1989). Science and corporate strategy. Cambridge Books.

  31. https://doi.org/10.48550/arXiv.2010.15581 Ahmed, N., Wahed, M., & Thompson, N. C. (2023). The growing influence of industry in AI research.
    Paper not yet in RePEc: Add citation now
  32. Johnson, R. (2021). Artificial, augmented and automated chemistry. Nature Chemistry, 13(9), 811– 813.
    Paper not yet in RePEc: Add citation now
  33. Jurowetzki, R., Hain, D., Mateos-Garcia, J., & Stathoulopoulos, K. (2021). The Privatization of AI Research (-ers): Causes and Potential Consequences–From university-industry interaction to public research brain-drain? arXiv preprint arXiv:2102.01648.
    Paper not yet in RePEc: Add citation now
  34. Klinger, J., Mateos-Garcia, J., & Stathoulopoulos, K. (2020). A narrowing of AI research? arXiv preprint arXiv:2009.10385. https://doi.org/10.48550/arXiv.2009.10385 Klinger, J., Mateos-Garcia, J., & Stathoulopoulos, K. (2021). Deep learning, deep change? Mapping the evolution and geography of a general purpose technology. Scientometrics, 126, 5589–5621.
    Paper not yet in RePEc: Add citation now
  35. LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444. https://doi.org/10.1038/nature14539 Leslie, S. W. (1993). The Cold War and American science: The military-industrial-academic complex at MIT and Stanford. Columbia University Press.
    Paper not yet in RePEc: Add citation now

  36. Liu, N., Shapira, P., Yue, X., & Guan, J. (2021). Mapping technological innovation dynamics in artificial intelligence domains: Evidence from a global patent analysis. Plos one, 16(12), e0262050.

  37. Lohr, S. (2019). At tech’s leading edge, worry about a concentration of power. The New York Times, 26, 2019.
    Paper not yet in RePEc: Add citation now
  38. Lou, B., & Wu, L. (2021). AI on drugs: Can artificial intelligence accelerate drug development? Evidence from a large-scale examination of bio-Pharma firms. Evidence from a Large-scale Examination of Bio-pharma Firms,(March 15, 2021). MISQ Forthcoming.
    Paper not yet in RePEc: Add citation now
  39. MacLeod, B. P., Parlane, F. G., Brown, A. K., Hein, J. E., & Berlinguette, C. P. (2022). Flexible automation accelerates materials discovery. Nature Materials, 21(7), 722–726.
    Paper not yet in RePEc: Add citation now
  40. Malerba, F. (1985). The semiconductor business: The economics of rapid growth and decline. University of Wisconsin Press.
    Paper not yet in RePEc: Add citation now
  41. Martin, B. R. (2003). The changing social contract for science and the evolution of the university. Science and innovation: Rethinking the rationales for funding and governance, 7–29.
    Paper not yet in RePEc: Add citation now

  42. Martin, B. R. (2012). Are universities and university research under threat? Towards an evolutionary model of university speciation. Cambridge journal of economics, 36(3), 543–565.

  43. Mazzucato, M., Schaake, M., Krier, S., & Entsminger, J. (2022). Governing artificial intelligence in the public interest. UCL Institute for Innovation and Public Purpose, Working Paper Series (IIPP WP 2022-12).
    Paper not yet in RePEc: Add citation now
  44. Mowery, D. C. (1995). The Boundaries of the US Firm in R&D. In Coordination and information: Historical perspectives on the organization of enterprise (pp. 147-182). University of Chicago Press.
    Paper not yet in RePEc: Add citation now
  45. Mowery, D. C., & Rosenberg, N. (1993). The US national innovation system. National innovation systems: A comparative analysis, 29–75.
    Paper not yet in RePEc: Add citation now
  46. Mowery, D. C., & Rosenberg, N. (1999). Paths of innovation: Technological change in 20th-century America. Cambridge University Press.
    Paper not yet in RePEc: Add citation now

  47. Nelson, R. R. (1988). Institutions Supporting Technical Change in the United States. In Technical Change and Economic Theory, ed. G. Dosi, C. Freeman, R. Nelson, G. Silverberg, and L. Soete. London: Pinter.

  48. Nelson, R. R. (1990). US technological leadership: Where did it come from and where did it go? Research policy, 19(2), 117–132.

  49. OECD. (2019). Artificial Intelligence in Society. https://www.oecdilibrary. org/content/publication/eedfee77-en Orsenigo, L. (1989). The emergence of biotechnology: Institutions and markets in industrial innovation. Pinter Publishers Ltd. https://www.cabdirect.org/cabdirect/abstract/19891607693 Pagano, U. (2014). The crisis of intellectual monopoly capitalism. Cambridge Journal of Economics, 38(6), 1409-1429.
    Paper not yet in RePEc: Add citation now

  50. Pavitt, K. (1998). Technologies, products and organization in the innovating firm: What Adam Smith tells us and Joseph Schumpeter doesn’t. Industrial and Corporate change, 7(3), 433–452.

  51. Petruzzelli, A. M., Murgia, G., & Parmentola, A. (2023). Opening the black box of artificial intelligence technologies: Unveiling the influence exerted by type of organisations and collaborative dynamics. Industry and Innovation, 30(9), 1213–1243. https://doi.org/10.1080/13662716.2023.2213182 Readings, B. (1996). The university in ruins. Harvard University Press.
    Paper not yet in RePEc: Add citation now
  52. Proceedings of the AAAI Conference on Artificial Intelligence, 32. https://doi.org/10.1609/aaai.v32i1.11503 Hagendorff, T., & Meding, K. (2021). Ethical considerations and statistical analysis of industry involvement in machine learning research. AI & SOCIETY, 1–11. https://doi.org/10.1007/s00146021 -01284-z Ho, D. E., King, J., Wald, R. C., & Wan, C. (2021). Building a national AI research resource. White paper (Stanford University Human-Centered Artificial Intelligence, 2021).
    Paper not yet in RePEc: Add citation now
  53. Rosenberg, N. (1985). The commercial exploitation of science by American industry.
    Paper not yet in RePEc: Add citation now

  54. Rosenberg, N., & Nelson, R. R. (1994). American universities and technical advance in industry. Research policy, 23(3), 323–348.

  55. Russell, S. (2019). Human compatible: Artificial intelligence and the problem of control. Penguin.
    Paper not yet in RePEc: Add citation now
  56. Schwab, K. (2016). The Fourth Industrial Revolution: What it Means, How to Respond.
    Paper not yet in RePEc: Add citation now
  57. Science, 379(6635), 884–886. https://doi.org/10.1126/science.ade2420 Babbage, C. (1832). On the economy of machinery and manufactures. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science, 1(3), 208–213. https://doi.org/10.1080/14786443208647876 Benner, M., & Sandström, U. (2000). Institutionalizing the triple helix: Research funding and norms in the academic system. Research policy, 29(2), 291–301.
    Paper not yet in RePEc: Add citation now
  58. Shinn, T. (2002). The Triple Helix and New Production of Knowledge: Prepackaged Thinking on Science and Technology. Social Studies of Science, 32(4), 599–614. https://doi.org/10.1177/0306312702032004004 Smith, A. (1776). The Wealth of Nations: An inquiry into the nature and causes of the Wealth of Nations. Harriman House Limited.
    Paper not yet in RePEc: Add citation now
  59. Solow, R. (1987). We’d Better Watch Out. The New York Times Book Review, 37.
    Paper not yet in RePEc: Add citation now
  60. Stigler, G. J. (1956). Industrial organization and economic progress. The state of the social sciences, 269-82.
    Paper not yet in RePEc: Add citation now

  61. Sultana, N., Turkina, E., & Cohendet, P. (2023). The mechanisms underlying the emergence of innovation ecosystems: The case of the AI ecosystem in Montreal. European Planning Studies, 31(7), 1443–1465. https://doi.org/10.1080/09654313.2023.2185502 Swann, J. P. (1988). Academic scientists and the pharmaceutical industry: Cooperative research in twentieth-century America (p. 25). Baltimore: Johns Hopkins University Press.

  62. Thackray, A. (1982). University-industry connections and chemical research: an historical perspective. University-industry research relationships: Selected studies, 193-234.
    Paper not yet in RePEc: Add citation now
  63. Universities and the Global Knowledge Economy: A Triple Helix of University-Industry-Government Relations. London: Pinter.[Archival Reprint]. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3404823 Etzkowitz, H., & Leydesdorff, L. (1998). The endless transition: A triple helix of universityindustry -government relations: Introduction. Minerva, 203–208.
    Paper not yet in RePEc: Add citation now
  64. Urbina, F., Lentzos, F., Invernizzi, C., & Ekins, S. (2022). Dual use of artificial-intelligence-powered drug discovery. Nature Machine Intelligence, 4(3), 189–191.
    Paper not yet in RePEc: Add citation now
  65. Vannuccini, S., & Prytkova, E. (2023). Artificial Intelligence’s new clothes? A system technology perspective. Journal of Information Technology, 02683962231197824. https://doi.org/10.1177/02683962231197824 Vincenti, W. G. (1990). What engineers know and how they know it (Vol. 141). Baltimore: Johns Hopkins University Press.
    Paper not yet in RePEc: Add citation now

Cocites

Documents in RePEc which have cited the same bibliography

  1. Decoding AI: Nine facts about how firms use artificial intelligence in France. (2025). Fontanelli, Luca ; Calvino, Flavio.
    In: LEM Papers Series.
    RePEc:ssa:lemwps:2025/13.

    Full description at Econpapers || Download paper

  2. Predictive AI and productivity growth dynamics: evidence from French firms. (2025). Secchi, Angelo ; Fontanelli, Luca ; Miniaci, Raffaele ; Guerini, Mattia.
    In: LEM Papers Series.
    RePEc:ssa:lemwps:2025/12.

    Full description at Econpapers || Download paper

  3. Discovering AI adoption patterns from big academic graph data. (2025). Kim, Sang Yoon ; Lee, Won Kyung ; Sohn, So Young ; Jee, Su Jung.
    In: Scientometrics.
    RePEc:spr:scient:v:130:y:2025:i:2:d:10.1007_s11192-024-05228-4.

    Full description at Econpapers || Download paper

  4. Knowledge Innovation Effect of University Computing Power in China: Evidence from the top500 Supercomputers. (2025). Gaofeng, Wang ; Jialin, Liu ; Haodong, Yang.
    In: Research in Higher Education.
    RePEc:spr:reihed:v:66:y:2025:i:1:d:10.1007_s11162-024-09822-6.

    Full description at Econpapers || Download paper

  5. Predictive AI and productivity growth dynamics: evidence from French firms. (2025). Secchi, Angelo ; Fontanelli, Luca ; Miniaci, Raffaele ; Guerini, Mattia.
    In: Working Papers.
    RePEc:fem:femwpa:2025.11.

    Full description at Econpapers || Download paper

  6. Impact of AI literacy and adaptability on financial analyst skills among prospective Thai accountants: The role of critical thinking. (2025). Yaacob, Zulnaidi ; Aujirapongpan, Somnuk ; Yordudom, Tanakrit ; Imjai, Narinthon ; Hasliza, Nor.
    In: Technological Forecasting and Social Change.
    RePEc:eee:tefoso:v:210:y:2025:i:c:s0040162524006875.

    Full description at Econpapers || Download paper

  7. Is artificial intelligence leading to a new technological paradigm?. (2025). Vivarelli, Marco ; Damioli, Giacomo ; Vertesy, Daniel ; van Roy, Vincent.
    In: Structural Change and Economic Dynamics.
    RePEc:eee:streco:v:72:y:2025:i:c:p:347-359.

    Full description at Econpapers || Download paper

  8. The impact of AI adoption on R&D productivity: Evidence from Chinese pharmaceutical manufacturing industry. (2025). Yuan, Yiming ; Wu, Yifan ; Song, Xueyin.
    In: Journal of Asian Economics.
    RePEc:eee:asieco:v:97:y:2025:i:c:s1049007825000144.

    Full description at Econpapers || Download paper

  9. How Small is Big Enough? Open Labeled Datasets and the Development of Deep Learning. (2025). Geuna, Aldo ; Rodraiguez, Jeff ; Souza, Daniel.
    In: Carlo Alberto Notebooks.
    RePEc:cca:wpaper:738.

    Full description at Econpapers || Download paper

  10. Predictive AI and productivity growth dynamics: evidence from French firms. (2025). Secchi, Angelo ; Fontanelli, Luca ; Miniaci, Raffaele ; Guerini, Mattia.
    In: FEEM Working Papers.
    RePEc:ags:feemwp:355806.

    Full description at Econpapers || Download paper

  11. KI-Einsatz in Unternehmen in Deutschland: Strategische Ausrichtung und internationale Position. (2024). Doherr, Thorsten ; Rammer, Christian ; Lenz, David ; Kinne, Jan.
    In: ZEW Expertises.
    RePEc:zbw:zewexp:303033.

    Full description at Econpapers || Download paper

  12. AI as a new emerging technological paradigm: evidence from global patenting. (2024). Vivarelli, Marco ; Vertesy, Daniel ; Van Roy, Vincent ; Damioli, Giacomo.
    In: GLO Discussion Paper Series.
    RePEc:zbw:glodps:1467.

    Full description at Econpapers || Download paper

  13. The US university-industry link in the R&D of AI: Back to the origins?. (2024). Llerena, Patrick ; Borsato, Andrea.
    In: Working Papers of BETA.
    RePEc:ulp:sbbeta:2024-46.

    Full description at Econpapers || Download paper

  14. Artificial intelligence and shapeshifting capitalism. (2024). Mariotti, Sergio ; Grilli, Luca ; Marzano, Riccardo.
    In: Journal of Evolutionary Economics.
    RePEc:spr:joevec:v:34:y:2024:i:2:d:10.1007_s00191-024-00865-7.

    Full description at Econpapers || Download paper

  15. AI technology specialization and national competitiveness. (2024). Chun, Youngsam ; Hwang, Junseok ; Hur, Jisoo.
    In: PLOS ONE.
    RePEc:plo:pone00:0301091.

    Full description at Econpapers || Download paper

  16. EU-funded investment in Artificial Intelligence and regional specialization. (2024). Molica, Francesco ; Salinas, Carlos Torrecilla ; Santos, Anabela Marques.
    In: GEE Papers.
    RePEc:mde:wpaper:181.

    Full description at Econpapers || Download paper

  17. Is Artificial Intelligence Generating a New Paradigm? Evidence from the Emerging Phase. (2024). Vivarelli, Marco ; Van Roy, Vincent ; Damioli, Giacomo ; Vertesy, Daniel.
    In: IZA Discussion Papers.
    RePEc:iza:izadps:dp17183.

    Full description at Econpapers || Download paper

  18. Artificial Intelligence and the Discovery of New Ideas: Is an Economic Growth Explosion Imminent?. (2024). Sequeira, Tiago ; Naudé, Wim ; Almeida, Derick ; Naude, Wim.
    In: IZA Discussion Papers.
    RePEc:iza:izadps:dp16766.

    Full description at Econpapers || Download paper

  19. The role of human capital for AI adoption: Evidence from French firms. (2024). Fontanelli, Luca ; Verdolini, Elena ; Nesta, Lionel ; Criscuolo, Chiara ; Calvino, Flavio.
    In: Post-Print.
    RePEc:hal:journl:hal-05029748.

    Full description at Econpapers || Download paper

  20. Bibliometric Overview of ChatGPT: New Perspectives in Social Sciences. (2024). Oliski, Marian ; Krukowski, Krzysztof ; Sieciski, Kacper.
    In: Publications.
    RePEc:gam:jpubli:v:12:y:2024:i:1:p:9-:d:1360866.

    Full description at Econpapers || Download paper

  21. The role of human capital for AI adoption: evidence from French firms. (2024). Verdolini, Elena ; Nesta, Lionel ; Criscuolo, Chiara ; Calvino, Flavio ; Fontanelli, Luca.
    In: LSE Research Online Documents on Economics.
    RePEc:ehl:lserod:126787.

    Full description at Econpapers || Download paper

  22. Unpacking the intellectual structure and evolution trend of general-purpose technologies development in innovation studies. (2024). Zhou, Yiting ; Sun, Yaowu ; Xu, Yanan.
    In: Technological Forecasting and Social Change.
    RePEc:eee:tefoso:v:209:y:2024:i:c:s0040162524006383.

    Full description at Econpapers || Download paper

  23. Did the COVID-19 pandemic propel usage of AI in pharmaceutical innovation? New evidence from patenting data. (2024). Rathi, Sawan ; Chatterjee, Chirantan ; Majumdar, Adrija.
    In: Technological Forecasting and Social Change.
    RePEc:eee:tefoso:v:198:y:2024:i:c:s004016252300625x.

    Full description at Econpapers || Download paper

  24. University procurement-led innovation: Sources, procedures, and effects. Some field-study evidence. (2024). Patsali, Sofia.
    In: Technovation.
    RePEc:eee:techno:v:130:y:2024:i:c:s0166497223002122.

    Full description at Econpapers || Download paper

  25. The yin yang of AI: Exploring how commercial and non-commercial orientations shape machine learning innovation. (2024). Brea, Edgar.
    In: Research Policy.
    RePEc:eee:respol:v:53:y:2024:i:6:s004873332400057x.

    Full description at Econpapers || Download paper

  26. Artificial intelligence and scientific discovery: a model of prioritized search. (2024). McHale, John ; Oettl, Alexander ; Agrawal, Ajay.
    In: Research Policy.
    RePEc:eee:respol:v:53:y:2024:i:5:s0048733324000386.

    Full description at Econpapers || Download paper

  27. Algorithmic management in scientific research. (2024). Koehler, Maximilian ; Sauermann, Henry.
    In: Research Policy.
    RePEc:eee:respol:v:53:y:2024:i:4:s0048733324000349.

    Full description at Econpapers || Download paper

  28. AI as a new emerging technological paradigm: evidence from global patenting. (2024). Vivarelli, Marco ; Van Roy, Vincent ; Damioli, Giacomo ; Vertesy, Daniel.
    In: DISCE - Working Papers del Dipartimento di Politica Economica.
    RePEc:ctc:serie5:dipe0038.

    Full description at Econpapers || Download paper

  29. AI Users Are Not All Alike: The Characteristics of French Firms Buying and Developing AI. (2024). Fontanelli, Luca ; Calvino, Flavio.
    In: CESifo Working Paper Series.
    RePEc:ces:ceswps:_11466.

    Full description at Econpapers || Download paper

  30. The role of human capital for AI adoption: Evidence from French firms. (2024). Verdolini, Elena ; Fontanelli, Luca ; Calvino, Flavio ; Criscuolo, Chiara ; Nesta, Lionel.
    In: CEP Discussion Papers.
    RePEc:cep:cepdps:dp2055.

    Full description at Econpapers || Download paper

  31. How Small is Big Enough? Open Labeled Datasets and the Development of Deep Learning. (2024). Geuna, Aldo ; de Souza, Daniel ; Rodr, Jeff.
    In: Papers.
    RePEc:arx:papers:2408.10359.

    Full description at Econpapers || Download paper

  32. Drivers and Barriers of AI Adoption and Use in Scientific Research. (2024). Bianchini, Stefano ; Pelletier, Pierre ; Muller, Moritz.
    In: Papers.
    RePEc:arx:papers:2312.09843.

    Full description at Econpapers || Download paper

  33. Data production and the coevolving AI trajectories: an attempted evolutionary model. (2023). Lorentz, André ; Borsato, Andrea.
    In: Journal of Evolutionary Economics.
    RePEc:spr:joevec:v:33:y:2023:i:5:d:10.1007_s00191-023-00837-3.

    Full description at Econpapers || Download paper

  34. The environmental effects of the “twin” green and digital transition in European regions. (2023). Damioli, Giacomo ; Bianchini, Stefano ; Ghisetti, Claudia.
    In: Environmental & Resource Economics.
    RePEc:kap:enreec:v:84:y:2023:i:4:d:10.1007_s10640-022-00741-7.

    Full description at Econpapers || Download paper

  35. AI-Driven Productivity Gains: Artificial Intelligence and Firm Productivity. (2023). Gao, Xueyuan ; Feng, Hua.
    In: Sustainability.
    RePEc:gam:jsusta:v:15:y:2023:i:11:p:8934-:d:1161805.

    Full description at Econpapers || Download paper

  36. Artificial intelligence adoption in the physical sciences, natural sciences, life sciences, social sciences and the arts and humanities: A bibliometric analysis of research publications from 1960-2021. (2023). Hajkowicz, Stefan ; Karimi, Sarvnaz ; Sanderson, Conrad ; Naughtin, Claire ; Bratanova, Alexandra.
    In: Technology in Society.
    RePEc:eee:teinso:v:74:y:2023:i:c:s0160791x23000659.

    Full description at Econpapers || Download paper

  37. The Economics of Copyright in the Digital Age. (2023). Windisch, Margaritha ; Peukert, Christian.
    In: CESifo Working Paper Series.
    RePEc:ces:ceswps:_10687.

    Full description at Econpapers || Download paper

Coauthors

Authors registered in RePEc who have wrote about the same topic

Report date: 2025-10-04 17:24:30 || Missing content? Let us know

CitEc is a RePEc service, providing citation data for Economics since 2001. Last updated August, 3 2024. Contact: Jose Manuel Barrueco.