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The Technological Elements of Artificial Intelligence

Citations

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Cited by:

  1. J. Klinger & J. Mateos-Garcia & K. Stathoulopoulos, 2018. "Deep learning, deep change? Mapping the development of the Artificial Intelligence General Purpose Technology," Papers 1808.06355, arXiv.org.
  2. Gordon H. Hanson, 2021. "Immigration and Regional Specialization in AI," NBER Working Papers 28671, National Bureau of Economic Research, Inc.
  3. Ayoubi, Charles, 2020. "Machine learning in healthcare: Mirage or miracle for breaking the costs dead-lock?," Thesis Commons tc24d, Center for Open Science.
  4. Joel Klinger & Juan Mateos-Garcia & Konstantinos Stathoulopoulos, 2021. "Deep learning, deep change? Mapping the evolution and geography of a general purpose technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5589-5621, July.
  5. Jens Prüfer & Patricia Prüfer, 2020. "Data science for entrepreneurship research: studying demand dynamics for entrepreneurial skills in the Netherlands," Small Business Economics, Springer, vol. 55(3), pages 651-672, October.
  6. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "Economic Policy for Artificial Intelligence," Innovation Policy and the Economy, University of Chicago Press, vol. 19(1), pages 139-159.
  7. Andrea Szalavetz, 2019. "Artificial Intelligence-Based Development Strategy in Dependent Market Economies - Any Room amidst Big Power Rivalry?," Central European Business Review, Prague University of Economics and Business, vol. 2019(4), pages 40-54.
  8. Dominic Chalmers & Niall G. MacKenzie & Sara Carter, 2021. "Artificial Intelligence and Entrepreneurship: Implications for Venture Creation in the Fourth Industrial Revolution," Entrepreneurship Theory and Practice, , vol. 45(5), pages 1028-1053, September.
  9. Su Jung Jee & So Young Sohn, 2023. "A firm’s creation of proprietary knowledge linked to the knowledge spilled over from its research publications: the case of artificial intelligence," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 32(4), pages 876-900.
  10. Li, Chengming & Xu, Yang & Zheng, Hao & Wang, Zeyu & Han, Haiting & Zeng, Liangen, 2023. "Artificial intelligence, resource reallocation, and corporate innovation efficiency: Evidence from China's listed companies," Resources Policy, Elsevier, vol. 81(C).
  11. Xueyuan Gao & Hua Feng, 2023. "AI-Driven Productivity Gains: Artificial Intelligence and Firm Productivity," Sustainability, MDPI, vol. 15(11), pages 1-21, June.
  12. Xueling Li & Xiaoyan Zhang & Yuan Liu & Yuanying Mi & Yong Chen, 2022. "The impact of artificial intelligence on users' entrepreneurial activities," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(3), pages 597-608, May.
  13. Nils Grashof & Alexander Kopka, 2023. "Widening or closing the gap? The relationship between artificial intelligence, firm-level productivity and regional clusters," Bremen Papers on Economics & Innovation 2304, University of Bremen, Faculty of Business Studies and Economics.
  14. Aránzazu Guillán Montero & David Le Blanc, 2019. "Lessons for Today from Past Periods of Rapid Technological Change," Working Papers 158, United Nations, Department of Economics and Social Affairs.
  15. Alexander Kopka & Dirk Fornahl, 2024. "Artificial intelligence and firm growth — catch-up processes of SMEs through integrating AI into their knowledge bases," Small Business Economics, Springer, vol. 62(1), pages 63-85, January.
  16. Knudsen, Eirik Sjåholm & Lien, Lasse B. & Timmermans, Bram & Belik, Ivan & Pandey, Sujit, 2021. "Stability in turbulent times? The effect of digitalization on the sustainability of competitive advantage," Journal of Business Research, Elsevier, vol. 128(C), pages 360-369.
  17. Eliseo Sciarretta & Riccardo Mancini & Emilio Greco, 2022. "Artificial Intelligence for Healthcare and Social Services: Optimizing Resources and Promoting Sustainability," Sustainability, MDPI, vol. 14(24), pages 1-9, December.
  18. Verstappen, Ksenia, 2018. "Economics of big data: review of best papers for January 2018," MPRA Paper 85520, University Library of Munich, Germany.
  19. Davide Proserpio & John R. Hauser & Xiao Liu & Tomomichi Amano & Alex Burnap & Tong Guo & Dokyun (DK) Lee & Randall Lewis & Kanishka Misra & Eric Schwarz & Artem Timoshenko & Lilei Xu & Hema Yoganaras, 2020. "Soul and machine (learning)," Marketing Letters, Springer, vol. 31(4), pages 393-404, December.
  20. Lili Yan Ing & Gene Grossman & David Christian, 2022. "Digital Transformation:‘Development for All’?," Chapters, in: Lili Yan Ing & Dani Rodrik (ed.), New Normal, New Technologies, New Financing, chapter 7, pages 75-88, Economic Research Institute for ASEAN and East Asia (ERIA).
  21. Lee, Chien-Chiang & Yan, Jingyang, 2024. "Will artificial intelligence make energy cleaner? Evidence of nonlinearity," Applied Energy, Elsevier, vol. 363(C).
  22. repec:osf:socarx:9a45d_v1 is not listed on IDEAS
  23. Yang Yi-wen & Tian Kai, 2024. "How Industrial Intelligence Affects High-Quality Economic Development," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 8495-8512, June.
  24. Jin Liu & Xingchen Xu & Xi Nan & Yongjun Li & Yong Tan, 2023. ""Generate" the Future of Work through AI: Empirical Evidence from Online Labor Markets," Papers 2308.05201, arXiv.org, revised Jun 2024.
  25. Lenz, Fulko, 2020. "Plattformökonomie – zwischen Abwehr und Wunschdenken," Zeitthemen 03, Stiftung Marktwirtschaft / The Market Economy Foundation, Berlin.
  26. Kopka, Alexander & Grashof, Nils, 2022. "Artificial intelligence: Catalyst or barrier on the path to sustainability?," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
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