PAMETAN PRIVREDNI RAZVOJ U EVROPSKIM ZEMLJAMA
Ključne reči:
Industrija 4.0, Privredni razvoj, Indeks Industrije 4.0, Pametan razvoj, Evropa
Sažetak
Industrija 4.0 je skup digitalnih i fizičkih tehnologija i sajber-fizičkih sistema koji nude nove vrednosti na makro i mikro nivou ekonomije. To izaziva značajne promene i razvoj u okviru industrijskog sektora širom sveta. Ovo istraživanje ima za cilj da utvrdi uticaj Industrije 4.0 na društveno-ekonomski razvoj uspostavljanjem korelacije između Indeksa industrije 4.0 i Indeksa humanog razvoja UNDP-a (HDI). Nakon analize korelacije, biće formirani klasteri zemalja prema njihovim rezultatima u implementaciji I4.0 i društveno-ekonomskom razvoju. Postoji jaka korelacija između implementacije Industrije 4.0 i društveno-ekonomskog razvoja na nivou evropskih zemalja, dok se sve zemlje mogu svrstati u tri značajna klastera. Ovaj rad potvrđuje pozitivan uticaj industrije 4.0 na društveno-ekonomski razvoj. Takođe pruža institucionalnim i poslovnim akterima objektivan podsticaj za bržu primenu osnovnih tehnologija I4.0.
Reference
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Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3–4), 591–611. https://doi.org/10.1093/biomet/52.3-4.591
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Vrchota, J., & Pech, M. (2019). Readiness of enterprises in Czech Republic to implement industry 4.0: Index of industry 4.0. Applied Sciences, 9(24), 5405.
Zhou, K., Liu, T., & Zhou, L. (2015). Industry 4.0: Towards future industrial opportunities and challenges. In 2015 12th International Conference on fuzzy systems and knowledge discovery (FSKD) (pp. 2147-2152). IEEE. Zhangjiajie, China.
Atik, H., & Ünlü, F. (2019). The measurement of industry 4.0 performance through industry 4.0 index: an empirical investigation for Turkey and European countries. Procedia Computer Science, 158, 852-860.
BCG. (2020). Industry 4.0. Boston Consulting Group. Accessed August 15th, 2021, available at: https://www.bcg.com/capabilities/manufacturing/industry-4.0
Bruce, P., & Bruce, A. (2017). Practical statistics for data scientists: 50 essential concepts. "O'Reilly Media, Inc.
Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences. (3rd ed.). Mahwah, NJ: Lawrence Erlbaum Associates.
Czifra, G., & Molnár, Z. (2020). Covid-19 and industry 4.0. Res. Pap. Fac. Mater. Sci. Technol. Slovak Univ. Technol, 28(46), 36-45.
Deloitte. (2020). The Fourth Industrial Revolution: At the intersection of readiness and responsibility. Deloitte Development LLC. Accessed August 15th, 2021, available at: https://www2.deloitte.com/za/en/pages/about-deloitte/articles/industry-4-0-readiness-report.html
Freedman, D., Pisani, R., & Purves, R. (2007). Statistics (international student edition). Pisani, R. Purves, 4th Edn. WW Norton & Company, New York.
Gareth, J., Daniela, W., Trevor, H., & Robert, T. (2013). An introduction to statistical learning: with applications in R. Springer.
Kagermann, H., Wahlster, W., Helbig, J. (2013). Recommendations for implementing the strategic initiative INDUSTRIE 4.0. Final report of the Industrie 4.0 Working Group. Securing the future of German manufacturing industry. In: Communication Promoters Group of the Industry-Science Research Alliance. Germany.
Li, G., Hou, Y., & Wu, A. (2017). Fourth Industrial Revolution: technological drivers, impacts and coping methods. Chinese Geographical Science, 27(4), 626-637.
Lloyd, S. P. (1957). Least square quantization in PCM. Bell Telephone Laboratories Paper. Published in journal much later: Lloyd, SP: Least squares quantization in PCM. IEEE Trans. Inform. Theor.(1957/1982), 18.
Lucato, W. C., Pacchini, A. P. T., Facchini, F., & Mummolo, G. (2019). Model to evaluate the Industry 4.0 readiness degree in Industrial Companies. IFAC-PapersOnLine, 52(13), 1808-1813.
Machado, C. G., Winroth, M., Carlsson, D., Almström, P., Centerholt, V., & Hallin, M. (2019). Industry 4.0 readiness in manufacturing companies: challenges and enablers towards increased digitalisation. Procedia Cirp, 81, 1113-1118.
MacQueen, J. (1967, June). Some methods for classification and analysis of multivariate observations. In Proceedings of the fifth Berkeley symposium on mathematical statistics and probability (Vol. 1, No. 14, pp. 281-297).
Müller, J. M., Kiel, D., & Voigt, K. I. (2018). What drives the implementation of Industry 4.0? The role of opportunities and challenges in the context of sustainability. Sustainability, 10(1), 247.
Author 1. (2020). Implications of the Fourth Industrial Revolution on sustainable development. Economics of Sustainable Development, 4(1), 45-60.
PwC. (n.d.) Industry 4.0: Self Assessment. PwC. Accessed August 15th, 2021, available at: https://i40-self-assessment.pwc.de/i40/
Schwab, K. (2016). The Fourth Industrial Revolution. Switzerland. World Economic Forum.
Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3–4), 591–611. https://doi.org/10.1093/biomet/52.3-4.591
UNDP. (2021). Human Development Index. Human Development Data Center. Accessed August 14th, 2021 available at: http://hdr.undp.org/en/data
Vasin, S., Gamidullaeva, L., Shkarupeta, E., Finogeev, A., & Palatkin, I. (2018). Emerging trends and opportunities for industry 4.0 development in Russia.
Vrchota, J., & Pech, M. (2019). Readiness of enterprises in Czech Republic to implement industry 4.0: Index of industry 4.0. Applied Sciences, 9(24), 5405.
Zhou, K., Liu, T., & Zhou, L. (2015). Industry 4.0: Towards future industrial opportunities and challenges. In 2015 12th International Conference on fuzzy systems and knowledge discovery (FSKD) (pp. 2147-2152). IEEE. Zhangjiajie, China.
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2022/04/20
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