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Tytuł artykułu

Comparison of Japan and OECD Countries in Terms of Well-Being Resources

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PL
Porównanie Japonii i krajów OECD pod względem zasobów związanych z dobrostanem
Języki publikacji
EN
Abstrakty
EN
While evaluating the concept of well-being for sustainability, which is defined as the feeling of having the physical and psychological resources necessary for a good life, it is essential to benefit from different perspectives referring to socio-psychological factors or their possible effects as well as financial and economic data. The aim of this study, which deals with the well-being level in terms of sustainability resources, is to evaluate the OECD countries and examine the differences and similarities in Japan, one of the G8 countries. According to the results of the multidimensional scaling analysis conducted for this purpose, Japan is in the same cluster as Luxembourg, which has the highest positive value, while Germany is one of the countries with the highest rate of divergence from other G8 countries in the difference matrix.
PL
Oceniając koncepcję dobrostanu pod kątem zrównoważoności, którą definiuje się jako poczucie posiadania zasobów fizycznych i psychicznych niezbędnych do dobrego życia, istotne jest skorzystanie z różnych perspektyw odnoszących się do czynników społeczno-psychologicznych lub ich możliwych skutków a także danych finansowych i gospodarczych. Przeprowadzona analiza umożliwiła na wskazanie poziomu dobrobytu pod względem zrównoważonych zasobów w krajach OECD, a także określenie różnic i podobieństw pomiędzy tymi państwami a Japonią, jednym z krajów grupy G8. Zgodnie z wynikami analizy skalowania wielowymiarowego Japonia znajduje się w tym samym klastrze co mający najwyższą wartość dodatnią Luksemburg, podczas gdy Niemcy należą do jednego z krajów o najwyższym wskaźniku rozbieżności w stosunku do innych państwo G8 w macierzy różnic.
Czasopismo
Rocznik
Strony
78--85
Opis fizyczny
Bibliogr. 32 poz., fig., tab.
Twórcy
autor
  • Mersin University, Turkey (Turcja)
Bibliografia
  • 1. ALDABBAS M., TEUFEL S., TEUFEL B., SPYCHER J., 2022, Forecasting the Quality of Life in a Future Smart Society, the Case of Switzerland, International Journal of Social Science and Humanity 12(2): 107-112, https://doi.org/10.18178/ ijssh.2022.12.2.1075. DOI: https://doi.org/10.18178/ijssh.2022.V12.1075 Google Scholar
  • 2. AYDAN S., BAYIN-DONAR G., ARIKAN C., 2022, Impacts of Economic Freedom, Health, and Social Expenditures on Well-Being Measured by the Better Life Index in OECD Countries, Social Work in Public Health 37(5): 435-447, https://doi.org/10.1080/19371918.2021.2018083. DOI: https://doi.org/10.1080/19371918.2021.2018083 Google Scholar
  • 3. BÉRENGER V., VERDIER-CHOUCHANE A., 2007, Multidimensional Measures of Well-Being: Standard of Living and Quality of Life Across Countries, World Development 35(7): 1259-1276, https://doi.org/10.1016/j.worlddev.2006.10.011. DOI: https://doi.org/10.1016/j.worlddev.2006.10.011 Google Scholar
  • 4. BRZEZIŃSKA J., 2022, A Study on the OECD Better Life Index Using Multivariate Statistical Analysis, Argumenta Oeconomica 1(48): 235-245, https://doi.org/10.15611/aoe.2022.1.10. DOI: https://doi.org/10.15611/aoe.2022.1.10 Google Scholar
  • 5. BUJA A., SWAYNE D. F., LITTMAN M. L., DEAN N., HOFMANN H., CHEN L., 2008, Data Visualization with Multidimensional Scaling, Journal of Computational and Graphical Statistics 17(2): 444-472, https://doi.org/10.1198/106186008X318440. DOI: https://doi.org/10.1198/106186008X318440 Google Scholar
  • 6. FINK J., DUCOING C., 2022, Does Natural Resource Extraction Compromise Future Well-Being? Norwegian Genuine Savings, 1865-2018, The Extractive Industries and Society 10112: 1-15,https://doi.org/10.1016/j.exis.2022.101127. DOI: https://doi.org/10.1016/j.exis.2022.101127 Google Scholar
  • 7. GONZÁLEZ-CARRASCO M., VAQUÉ C., MALO S., CROUS G., CASAS F., FIGUER C., 2019, A Qualitative Longitudinal Study on the Well-Being of Children and Adolescents, Child Indicators Research 12(2): 479-499, https://doi.org/10.1007/s12187-018-9534-7. DOI: https://doi.org/10.1007/s12187-018-9534-7 Google Scholar
  • 8. HANSEN T., SLAGSVOLD B., 2012, The Age and Subjective Well-Being Paradox Revisited: A Multidimensional Perspective, Norsk Epidemiologi 22(2), https://doi.org/10.5324/nje.v22i2.1565. DOI: https://doi.org/10.5324/nje.v22i2.1565 Google Scholar
  • 9. HAQ S., 2003, Future of the G-8, Strategic Studies 23(3): 168-186, http://www.jstor.org/stable/45242486. Google Scholar
  • 10. HECK G., HESS S., 2017, Tracing the Effects of the EU-Turkey Deal Movements, Journal for Critical Migration and Border Regime Studies 3(2): 35-56. Google Scholar
  • 11. HENDERSON K., LOREAU M., 2023, A Model of Sustainable Development Goals: Challenges and Opportunities in Promoting Human Well-Being and Environmental Sustainability, Ecological Modelling 475: 110164, https://doi.org/10.1016/j.ecolmodel.2022.110164. DOI: https://doi.org/10.1016/j.ecolmodel.2022.110164 Google Scholar
  • 12. HOUT M. C., PAPESH M. H., GOLDINGER S. D., 2013, Multidimensional Scaling, Wiley Interdisciplinary Reviews: Cognitive Science 4(1): 93-103, https://doi.org/10.1002/wcs.1203. DOI: https://doi.org/10.1002/wcs.1203 Google Scholar
  • 13. INCE F., 2020, The Effects of COVID-19 Pandemic on the Workforce in Turkey, Smart Journal 6(32): 1125-1134, https://doi.org/10.31576/smryj.546. DOI: https://doi.org/10.31576/smryj.546 Google Scholar
  • 14. INCE F., 2023, Digital Transformation and Well-Being, Digital Psychology’s Impact on Business and Society, eds. Anshari M., Razzaq A., Fithriyah M., Kamal A.N., IGI Global, https://doi.org/10.4018/978-1-6684-6108-2. DOI: https://doi.org/10.4018/978-1-6684-6108-2 Google Scholar
  • 15. JAPANESE RED CROSS SOCIETY, 2022, Social Well-being Services: Annual Report of 2020-2021, https:// www.jrc.or.jp/english/activity/well-being/ (09.08.2022). Google Scholar
  • 16. KORONAKOS G., SMIRLIS Y., SOTIROS D., DESPOTIS D.K., 2022, The OECD Better Life Index: A Guide for Well-Being Based Economic Diplomacy, Modern Indices for International Economic Diplomacy, eds. Charles V., Emrouznejad A., Palgrave Macmillan, Cham, https://doi.org/10.1007/978-3-030-84535-3_2. DOI: https://doi.org/10.1007/978-3-030-84535-3_2 Google Scholar
  • 17. LAWRENCE J., ARIETTA S., KAZHDAN M., LEPAGE D., O’HAGAN C., 2010, A User-Assisted Approach to Visualizing Multidimensional Images, IEEE transactions on Visualization and Computer Graphics 17(10): 1487-1498, https://doi.org/10.1109/TVCG.2010.229. DOI: https://doi.org/10.1109/TVCG.2010.229 Google Scholar
  • 18. LIBERATI P., RESCE G., 2022, Regional Well-Being and Its Inequality in the OECD Member Countries, The Journal of Economic Inequality 20: 671-700, https://doi.org/10.1007/s10888-021-09521-7. DOI: https://doi.org/10.1007/s10888-021-09521-7 Google Scholar
  • 19. NAKAJIMA H., MORITA A., KANAMORI S., AIDA J., FUJIWARA T., 2022, The frequency of job participation and well-being of older people in Japan: Results from JAGES study, Archives of Gerontology and Geriatrics 104720: 1-10, https://doi.org/10.1016/j.archger.2022.104720. DOI: https://doi.org/10.1016/j.archger.2022.104720 Google Scholar
  • 20. NETO F., 2023, Brazilian International Students’ Satisfaction with Migration Life in Portugal, Journal of International Students 13(2), https://doi.org/10.32674/jis.v13i2.4782. DOI: https://doi.org/10.32674/jis.v13i2.4782 Google Scholar
  • 21. NISHAAT A., 2022, Understanding the Concepts of Subjective Well-being and Psychological Well-being, The Bulletin of the Graduate School, Soka University 43: 99-108, http://hdl.handle.net/10911/00040868. Google Scholar
  • 22. NOWAK-OLEJNIK A., SCHIRPKE U., TAPPEINER U., 2022, A Systematic Review on Subjective Well-Being Benefits ssociated with Cultural Ecosystem Services, Ecosystem Services, 57: 101467, https://doi.org/10.1016/j.ecoser.2022.101467. DOI: https://doi.org/10.1016/j.ecoser.2022.101467 Google Scholar
  • 23. OECD, 2022, Resources for Future Well-being, https://stats.oecd.org/ (09.08.2022). Google Scholar
  • 24. PATEL S. R., BAKKEN S., RULAND C., 2008, Recent Advances in Shared Decision Making for Mental Health, Current Opinion in Psychiatry 21(6): 606-612, https://doi.org/10.1097/YCO.0b013e32830eb6b4. DOI: https://doi.org/10.1097/YCO.0b013e32830eb6b4 Google Scholar
  • 25. SAEEDN., NAM H., HAQ M. I. U., MUHAMMAD-SAQIB D. B., 2018, A Survey on Multidimensional Scaling, ACM Computing Surveys (CSUR) 51(3): 1-25, https://doi.org/10.1145/3178155. DOI: https://doi.org/10.1145/3178155 Google Scholar
  • 26. SALOM-PÉREZ R., WULTSCH C., ADAMS J. R., SOTO-FOURNIER S., GUTIÉRREZ-ESPELETA G. A., WAITS L. P., 2022, Genetic Diversity and Population Structure for Ocelots (Leopardus Pardalis) in Costa Rica, Journal of Mammalogy 103(1): 68-81, https://doi.org/10.1093/jmammal/gyab146. DOI: https://doi.org/10.1093/jmammal/gyab146 Google Scholar
  • 27. SRIVASTAVA S., CHAUHAN S., MUHAMMAD T., SIMON D. J., KUMAR P., PATEL R., SINGH S. K., 2021, Older Adults’ Psychological and Subjective Well-Being as a Function of Household Decision Making Role: Evidence from Cross-Sectional Survey in India, Clinical Epidemiology and Global Health 10: 100676, https://doi.org/10.1016/j.cegh.2020.100676. DOI: https://doi.org/10.1016/j.cegh.2020.100676 Google Scholar
  • 28. SUN J., CROWE M., FYFE C., 2011, Extending Metric Multidimensional Scaling with Bregman Divergences, Pattern Recognition 44(5): 1137-1154, https://doi.org/10.1016/j.patcog.2010.11.013. DOI: https://doi.org/10.1016/j.patcog.2010.11.013 Google Scholar
  • 29. TAKAHASHI T., ASANO S., UCHIDA Y., TAKEMURA K., FUKUSHIMA S., MATSUSHITA K., OKUDA N., 2022, Effects of Forests and Forest-related Activities on the Subjective Well-Being of Residents in a Japanese Watershed: An Econometric Analysis Through the Capability Approach, Forest Policy and Economics 139: 102723, https://doi.org/10.1016/j.forpol.2022.102723. DOI: https://doi.org/10.1016/j.forpol.2022.102723 Google Scholar
  • 30. UN, 2022, The 17 UN Sustainable Development Goals, New York, https://sdgs.un.org/goals. Google Scholar
  • 31. WILLIAMS M., MUNZNER T., 2004, Steerable, Progressive Multidimensional Scaling, IEEE Symposium on Information Visualization: 57-64, Texas, USA, https://doi.org/10.1109/INFVIS.2004.60. DOI: https://doi.org/10.1109/INFVIS.2004.60 Google Scholar
  • 32. ZAND M. S., WANG J., HILCHEY S., 2015, Graphical Representation of Proximity Measures for Multidimensional Data: Classical and Metric Multidimensional Scaling, The Mathematica Journal 17(7): 1-61, https://doi.org/10.3888/tmj. DOI: https://doi.org/10.3888/tmj.17-7 Google Scholar
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-66f80dcf-c203-43fc-a65a-0c08846da992
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