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A Monitoring Framework for Progress in Artificial Intelligence Technology: A Research Based on Scientific and Technological Indicators

Year 2024, Volume: 74 Issue: 2, 427 - 459, 31.12.2024
https://doi.org/10.26650/ISTJECON2024-1393965

Abstract

In the past century, the key technologies that shaped societal and economic transformation were mechanical, electrical, and automation technologies. In the current century, there are strong trends indicating the prominence of artificial intelligence technology. Therefore, artificial intelligence technology has become more important for all countries. The success of countries in artificial intelligence technology is only possible with well-designed artificial intelligence policy tools. It is important to measure the level of technological advancement for the formulation of policies. However, efforts to measure the scientific and technological advancement of artificial intelligence technology are insufficient. Therefore, this study aims to develop a framework to measure the scientific and technological progress of AI technology. The developed framework includes the number of publications and citations, the number of high-impact scientific journals, the number of patent applications, the number of universities ranked in the top thousand in the field of computer science, the number of international high-impact conferences, and the total number of researchers in higher education. Through these criteria, the level of scientific and technological progress of the countries has been analysed in detail. The findings clearly revealed the leading position of the USA in this field. China followed the USA. These two countries are clearly and positively differentiated from the other countries. Other countries with good performance are the UK, the Netherlands and Germany.

JEL Classification : O31 , O32 , O33

References

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  • Kaloudis, A., Aspelund, A., Koch, P. M., Lauvâs, T. A., Mathisen, M. T., Strand, 0., ... Aadland, T. (2019). How universities contribute to innovation: A literature review-based analysis. Norway: Norwegian Ministry of Education and Research. google scholar
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  • Le, T., Pham, H., Mai, S., & Vu, N. (2022). Frontier academic research, industrial R&D and technological progress: The case of OECD countries. Technovation, 114, 102436. https://doi.org/10.1016/j. technovation.2021.102436 google scholar
  • Liu, H., Yang, G., Liu, X., & Song, Y. (2020). R&D performance assessment of industrial enterprises in China: A two-stage DEA approach. Socio-Economic Planning Sciences, 71, 100753. https://doi. org/10.1016/j.seps.2019.100753 google scholar
  • Mansfield, E. (1991). Academic research and industrial innovation. Research Policy, 20(1), 1-12. https://doi.org/10.1016/0048-7333(91)90080-A google scholar
  • Ministry Of Education, Culture, Sports, Science And Technology Japanese Government. (2005). Contributions of scientific and technological progress. Tokyo/Japan. Retrieved from https://www. mext.go.jp/en/publication/whitepaper/title03/detail03/1372835.htm google scholar
  • Moed, H. F. (2005). Citation Analysis in Research Evaluation (Vol. 9). Berlin/Heidelberg: Springer-Verlag. https://doi.org/10.1007/1-4020-3714-7 google scholar
  • Narin, F., Hamilton, K. S., & Olivastro, D. (1997). The increasing linkage between U.S. technology and public science. Research Policy, 26(3), 317-330. https://doi.org/10.1016/S0048-7333(97)00013-9 google scholar
  • National Research Council. (2007). A strategy for assessing science: Behavioral and social research on aging (I. Feller & P. C. Stern, Eds.). Washington, DC: National Academies Press. google scholar
  • National Research Council (NRCb). (1986). The Positive Sum Strategy: Harnessing Technology for Economic Growth (p. 612). Washington, D.C.: National Academies Press. https://doi. org/10.17226/612 google scholar
  • Nestor, M., Fattorini, L., Brynjolfsson, E., Etchemendy, J., Ligett, K., Lyons, T., ... Perrault, R. (2023). The AI Index 2023 Annual Report. Stanford, CA: AI Index Steering Committee, Institute for Human-Centered AI, Stanford University. Retrieved from AI Index Steering Committee, Institute for Human-Centered AI, Stanford University website: https://aiindex.stanford.edu/report/ google scholar
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  • OECD and SCImago Research Group. (2016). Compendium of bibliometric science indicators. Paris. Retrieved from http://oe.cd/scientometrics google scholar
  • OECDa. (1994). The Measurement of Scientific and Technical Activities: Standard Practice for Surveys of Research and Experimental Development - Frascati Manual 1993. OECD. https://doi. org/10.1787/9789264063525-en google scholar
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  • Samuelson, S., & Sarrico, C. (2017). Benchmarking Higher Education System Performance: Conceptual Framework and Data. Organisation for Economic Co-operation and Development (No. EDU/ EDPC(2017)1). Organisation for Economic Co-operation and Development(OECD). google scholar
  • Schreiber, M. (2007). Self-citation corrections for the Hirsch index. Europhysics Letters (EPL), 78(3), 30002. https://doi.org/10.1209/0295-5075/78/30002 google scholar
  • Sobral, S. R. (2021). The Universities Ranking World Cup: A Global View by Continent and Country from the Computer Science Perspective. International Journal of Information and Education Technology, 11(6), 277-285. https://doi.org/10.18178/ijiet.2021.11.6.1523 google scholar
  • Tan, X.-R. (2005). Applications of gray relational analysis in gastroenterology. World Journal of Gastroenterology, 11(22), 3457. https://doi.org/10.3748/wjg.v11.i22.3457 google scholar
  • Times Higher Education. (2022). Times Higher Education World University Rankings. THE World Universities Insights Limited. https://doi.org/10.1201/9781315155890-8 google scholar
  • Tsinghua University. (2018). China AI development report. google scholar
  • Uludağ, A. S., & Doğan, H. (2021). Üretim yönetiminde çok kriterli karar verme yöntemleri: Lİteratür, teori ve uygulama (1st ed.). Ankara: Nobel Yayınevi. google scholar
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Year 2024, Volume: 74 Issue: 2, 427 - 459, 31.12.2024
https://doi.org/10.26650/ISTJECON2024-1393965

Abstract

References

  • Akçiğit, U., & Tok, E. Ö. (2020). Türkiye Bilim Raporu (No. TÜBA Raporları No:43). Türkiye Bilimler Akademisi Yayınları. google scholar
  • Aksens, D. W. (2003). A macro study of self-citation. Scientometrics, 56(2). https://doi. org/10.1023/A:1021919228368 google scholar
  • Aslan, F. (2023). Teknoloji geliştirme sürecinin değerlendirilmesi için olgunluk modeli önerisi: ARGE-500 firmalarının faaliyet ve yaklaşımlarına yönelik bir uygulama (Dissertation). Fırat Üniversitesi, Elazığ. google scholar
  • Baruffaldi, S., B., Beuzekom, B. van, Dernis, H., Harhoff, D., Rao, N., Rosenfeld, D., & Squicciarini, M. (2020). Identifying and measuring developments in artificial intelligence: Making the impossible possible (OECD Science, Technology and Industry Working Papers No. 2020/05). OECD. https:// doi.org/10.1787/5f65ff7e-en google scholar
  • Bernanke, B. S. (2011, May 16). Promoting research and development—The Government’s role. Presented at the New Building Blocks for Jobs and Economic Growth, Washington DC. Washington DC. google scholar
  • Betz, F. (2011). Managing technological innovation: Competitive advantage from change (3rd ed). Hoboken, N.J: Wiley. google scholar
  • Campbell, D., Roberge, G., Ventimiglia, A., Labrosse, I., Lefebvre, C., Picard-Aitken, M., ... Archambault, E. (2015). Analysis of bibliometric indicators for European policies 2010-2013. (Science Metrix., Ed.). Luxembourg: European Union. Retrieved from https://data.europa.eu/ doi/10.2777/194026 google scholar
  • Cesareo, S., & White, J. (2023). The Global AI Index. Tortoise. Retrieved from Tortoise website: https://www.tortoisemedia.com/intelligence/global-ai/ google scholar
  • Costas, R., Van Leeuwen, T. N., & Bordons, M. (2010). Self-citations at the meso and individual levels: Effects of different calculation methods. Scientometrics, 82(3), 517-537. https://doi.org/10.1007/ s11192-010-0187-7 google scholar
  • Dwivedi, P. P., & Sharma, D. K. (2022). Application of Shannon entropy and CoCoSo methods in selection of the most appropriate engineering sustainability components. Cleaner Materials, 5, 100118. https://doi.org/10.1016/j.clema.2022.100118 google scholar
  • Eto, H. (2003). Interdisciplinary information input and output of a nano-technology project. Scientometrics, 58(1), 5-33. https://doi.org/10.1023/A:1025423406643 google scholar
  • Evans, K. M., Hazan, G., Kamepalli, S., & Matthews, K. R. W. (2021). U.S. Federal Scientific Research and Development: Budget Overview and Outlook. Rice University’s Baker Institute for Public Policy. Retrieved from Rice University’s Baker Institute for Public Policy website: https://www. bakerinstitute.org/research/us-federal-scientific-research-and-development-budget-overview-and-outlook/ google scholar
  • Everaers, P. (2022). Standards as the backbone for official statistics, how well do they fit within national and international systems?12 or Does the obsession with cross-national comparisons blind us to the weakly implemented standards behind them? Statistical Journal of the IAOS, 38(2), 675-680. https://doi.org/10.3233/SJI-220032 google scholar
  • Gonzâlez-Pereira, B., Guerrero-Bote, V. P., & Moya-Anegon, F. (2010). A new approach to the metric of journals’ scientific prestige: The SJR indicator. Journal of Informetrics, 4(3), 379-391. https:// doi.org/10.1016/j.joi.2010.03.002 google scholar
  • Guerrero-Bote, V. P., & Moya-Anegon, F. (2012). A further step forward in measuring journals’ scientific prestige: The SJR2 indicator. Journal of Informetrics, 6(4), 674-688. https://doi. org/10.1016/j.joi.2012.07.001 google scholar
  • Hellsten, I., Lambiotte, R., Scharnhorst, A., & Ausloos, M. (2007). Self-citations, co-authorships and keywords: A new approach to scientists’ field mobility? Scientometrics, 72(3), 469-486. https:// doi.org/10.1007/s11192-007-1680-5 google scholar
  • Hyland, K. (2003). Self-citation and self-reference: Credibility and promotion in academic publication. Journal of the American Society for Information Science and Technology, 54(3), 251259. https://doi.org/10.1002/asi.10204 google scholar
  • IBM Corporation. (2022). IBM Global AI Adoption Index 2022. Retrieved from https://www.ibm.com/ watson/resources/ai-adoption google scholar
  • Isaka, M. (2013). Intellectual Property Rights: The Role of Patents in Renewable Energy Technology Innovation (p. 34). Bonn, Germany: The International Renewable Energy Agency (IRENA). Retrieved from The International Renewable Energy Agency (IRENA) website: www.irena.org google scholar
  • Kaloudis, A., Aspelund, A., Koch, P. M., Lauvâs, T. A., Mathisen, M. T., Strand, 0., ... Aadland, T. (2019). How universities contribute to innovation: A literature review-based analysis. Norway: Norwegian Ministry of Education and Research. google scholar
  • Korinek, A., Schindler, M., & Stiglitz, J. E. (2021). Technological progress, artificial intelligence, and inclusive growth (Working Paper No. WP/21/166). International Monetary Fund. google scholar
  • Le, T., Pham, H., Mai, S., & Vu, N. (2022). Frontier academic research, industrial R&D and technological progress: The case of OECD countries. Technovation, 114, 102436. https://doi.org/10.1016/j. technovation.2021.102436 google scholar
  • Liu, H., Yang, G., Liu, X., & Song, Y. (2020). R&D performance assessment of industrial enterprises in China: A two-stage DEA approach. Socio-Economic Planning Sciences, 71, 100753. https://doi. org/10.1016/j.seps.2019.100753 google scholar
  • Mansfield, E. (1991). Academic research and industrial innovation. Research Policy, 20(1), 1-12. https://doi.org/10.1016/0048-7333(91)90080-A google scholar
  • Ministry Of Education, Culture, Sports, Science And Technology Japanese Government. (2005). Contributions of scientific and technological progress. Tokyo/Japan. Retrieved from https://www. mext.go.jp/en/publication/whitepaper/title03/detail03/1372835.htm google scholar
  • Moed, H. F. (2005). Citation Analysis in Research Evaluation (Vol. 9). Berlin/Heidelberg: Springer-Verlag. https://doi.org/10.1007/1-4020-3714-7 google scholar
  • Narin, F., Hamilton, K. S., & Olivastro, D. (1997). The increasing linkage between U.S. technology and public science. Research Policy, 26(3), 317-330. https://doi.org/10.1016/S0048-7333(97)00013-9 google scholar
  • National Research Council. (2007). A strategy for assessing science: Behavioral and social research on aging (I. Feller & P. C. Stern, Eds.). Washington, DC: National Academies Press. google scholar
  • National Research Council (NRCb). (1986). The Positive Sum Strategy: Harnessing Technology for Economic Growth (p. 612). Washington, D.C.: National Academies Press. https://doi. org/10.17226/612 google scholar
  • Nestor, M., Fattorini, L., Brynjolfsson, E., Etchemendy, J., Ligett, K., Lyons, T., ... Perrault, R. (2023). The AI Index 2023 Annual Report. Stanford, CA: AI Index Steering Committee, Institute for Human-Centered AI, Stanford University. Retrieved from AI Index Steering Committee, Institute for Human-Centered AI, Stanford University website: https://aiindex.stanford.edu/report/ google scholar
  • Ng, D. K. W. (1994). Grey system and grey relational model. ACM SIGICE Bulletin, 20(2). google scholar
  • OECD and SCImago Research Group. (2016). Compendium of bibliometric science indicators. Paris. Retrieved from http://oe.cd/scientometrics google scholar
  • OECDa. (1994). The Measurement of Scientific and Technical Activities: Standard Practice for Surveys of Research and Experimental Development - Frascati Manual 1993. OECD. https://doi. org/10.1787/9789264063525-en google scholar
  • OECDb. (1995). Measurement of Scientific and Technological Activities: Manual on the Measurement of Human Resources Devoted to S&T - Canberra Manual. Paris/France: OECD. https://doi. org/10.1787/9789264065581-en google scholar
  • OECDc. (2017). OECD Science, Technology and Industry Scoreboard 2017: The digital transformation. OECD. https://doi.org/10.1787/9789264268821-en google scholar
  • Oester, S., Cigliano, J. A., Hind-Ozan, E. J., & Parsons, E. C. M. (2017). Why Conferences Matter—An google scholar
  • Illustration from the International Marine Conservation Congress. Frontiers in Marine Science, 4, 257. https://doi.org/10.3389/fmars.2017.00257 google scholar
  • Okubo, Y. (1997). Bibliometric Indicators and Analysis of Research Systems: Methods and Examples (Working Papers No. 51765). Paris: OECD. https://doi.org/10.1787/208277770603 google scholar
  • Parsons, E. C. M. (2015). So you think you want to run an environmental conservation meeting? Advice on the slings and arrows of outrageous fortune that accompany academic conference planning. Journal of Environmental Studies and Sciences, 5(4), 735-744. https://doi.org/10.1007/ s13412-015-0327-8 google scholar
  • Pavel, A.-P. (2015). Global University Rankings—A Comparative Analysis. Procedia Economics and Finance, 26, 54-63. https://doi.org/10.1016/S2212-5671(15)00838-2 google scholar
  • Peng, X., Tang, X., Chen, Y., & Zhang, J. (2021). Ranking the Healthcare Resource Factors for Public Satisfaction with Health System in China—Based on the Grey Relational Analysis Models. International Journal of Environmental Research and Public Health, 18(3), 995. https://doi. org/10.3390/ijerph18030995 google scholar
  • Rogerson, A., Hankins, E., Nettel, P. F., & Rahim, S. (2022). Government AI readiness index. Oxford Insights. Retrieved from Oxford Insights website: https://www.oxfordinsights.com/government-ai-readiness-index2021 google scholar
  • Samuelson, S., & Sarrico, C. (2017). Benchmarking Higher Education System Performance: Conceptual Framework and Data. Organisation for Economic Co-operation and Development (No. EDU/ EDPC(2017)1). Organisation for Economic Co-operation and Development(OECD). google scholar
  • Schreiber, M. (2007). Self-citation corrections for the Hirsch index. Europhysics Letters (EPL), 78(3), 30002. https://doi.org/10.1209/0295-5075/78/30002 google scholar
  • Sobral, S. R. (2021). The Universities Ranking World Cup: A Global View by Continent and Country from the Computer Science Perspective. International Journal of Information and Education Technology, 11(6), 277-285. https://doi.org/10.18178/ijiet.2021.11.6.1523 google scholar
  • Tan, X.-R. (2005). Applications of gray relational analysis in gastroenterology. World Journal of Gastroenterology, 11(22), 3457. https://doi.org/10.3748/wjg.v11.i22.3457 google scholar
  • Times Higher Education. (2022). Times Higher Education World University Rankings. THE World Universities Insights Limited. https://doi.org/10.1201/9781315155890-8 google scholar
  • Tsinghua University. (2018). China AI development report. google scholar
  • Uludağ, A. S., & Doğan, H. (2021). Üretim yönetiminde çok kriterli karar verme yöntemleri: Lİteratür, teori ve uygulama (1st ed.). Ankara: Nobel Yayınevi. google scholar
  • WIPO. (2019). WIPO Technology Trends 2019: Artificial Intelligence. Geneva: World Intellectual Property Organization. google scholar
  • World Economic Forum. (2022). Empowering AI Leadership: AI C-Suite Toolkit. Switzerland: World Economic Forum. google scholar
  • Zhu, Y., Tian, D., & Yan, F. (2020). Effectiveness of Entropy Weight Method in Decision-Making. Mathematical Problems in Engineering, 2020, 1-5. https://doi.org/10.1155/2020/3564835 google scholar
There are 52 citations in total.

Details

Primary Language English
Subjects Business Systems in Context (Other)
Journal Section Research Article
Authors

Fethi Aslan 0000-0002-5567-9706

Publication Date December 31, 2024
Submission Date November 21, 2023
Acceptance Date October 16, 2024
Published in Issue Year 2024 Volume: 74 Issue: 2

Cite

APA Aslan, F. (2024). A Monitoring Framework for Progress in Artificial Intelligence Technology: A Research Based on Scientific and Technological Indicators. İstanbul İktisat Dergisi, 74(2), 427-459. https://doi.org/10.26650/ISTJECON2024-1393965
AMA Aslan F. A Monitoring Framework for Progress in Artificial Intelligence Technology: A Research Based on Scientific and Technological Indicators. İstanbul İktisat Dergisi. December 2024;74(2):427-459. doi:10.26650/ISTJECON2024-1393965
Chicago Aslan, Fethi. “A Monitoring Framework for Progress in Artificial Intelligence Technology: A Research Based on Scientific and Technological Indicators”. İstanbul İktisat Dergisi 74, no. 2 (December 2024): 427-59. https://doi.org/10.26650/ISTJECON2024-1393965.
EndNote Aslan F (December 1, 2024) A Monitoring Framework for Progress in Artificial Intelligence Technology: A Research Based on Scientific and Technological Indicators. İstanbul İktisat Dergisi 74 2 427–459.
IEEE F. Aslan, “A Monitoring Framework for Progress in Artificial Intelligence Technology: A Research Based on Scientific and Technological Indicators”, İstanbul İktisat Dergisi, vol. 74, no. 2, pp. 427–459, 2024, doi: 10.26650/ISTJECON2024-1393965.
ISNAD Aslan, Fethi. “A Monitoring Framework for Progress in Artificial Intelligence Technology: A Research Based on Scientific and Technological Indicators”. İstanbul İktisat Dergisi 74/2 (December 2024), 427-459. https://doi.org/10.26650/ISTJECON2024-1393965.
JAMA Aslan F. A Monitoring Framework for Progress in Artificial Intelligence Technology: A Research Based on Scientific and Technological Indicators. İstanbul İktisat Dergisi. 2024;74:427–459.
MLA Aslan, Fethi. “A Monitoring Framework for Progress in Artificial Intelligence Technology: A Research Based on Scientific and Technological Indicators”. İstanbul İktisat Dergisi, vol. 74, no. 2, 2024, pp. 427-59, doi:10.26650/ISTJECON2024-1393965.
Vancouver Aslan F. A Monitoring Framework for Progress in Artificial Intelligence Technology: A Research Based on Scientific and Technological Indicators. İstanbul İktisat Dergisi. 2024;74(2):427-59.