Keywords
subjective quality of life
intuitionistic fuzzy sets
aggregated ordinal data
European cities
How to Cite
Abstract
The paper aims to measure and assess changes regarding the SQoL experienced by the residents of selected European cities over time. An Intuitionistic Fuzzy Synthetic Measure (IFSM) was applied to measure the SQoL. The measure allows taking into account the element of uncertainty expressed in the lack or refusal to answer. The analysis uses the results of studies on the SQoL conducted by the European Commission in the selected European cities. The method of constructing a pattern object proposed in the article allowed for assessing changes in the SQoL level of European city residents over time. The analysis showed that the subjective quality of life of the residents of European cities is systematically increasing during the period 2006-2019. However, we still observe large differences in the level of this phenomenon among the cities. The results of the research can be used to formulate assumptions or modify urban policies in EU cities to improve the quality of life of citizens.
References
Angur, M. G., Widgery, R., & Angur, S. G. (2004). Congruence among objective and subjective Quality-of-Life (QOL) indicators. Alliance Journal of Business Research, 47-54.
Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20, 87-96. https://doi.org/10.1016/S0165-0114(86)80034-3
Atanassov, K. T. (1999). Intuitionistic Fuzzy Sets. In K.T. Atanassov (Ed.), Intuitionistic Fuzzy Sets. Theory and Applications (pp. 1-137). Heidelberg: Physica. https://doi.org/10.1007/978-3-7908-1870-3_1
Castelli, C., d’Hombres, B., de Dominicis, L., Dijkstra, L., Montalto, V., & Pontarollo, N. (2022). What makes people in Europe satisfied with the city where they live? Evidence from the 2019 European Commission perception survey on the quality of life in European cities. https://ec.europa.eu/regional_policy/sources/work/2022_05_satis_cities.pdf
Chen, Z., & Davey, G. (2009). Subjective Quality of Life in Zhuhai City, South China: A Public Survey Using the International Wellbeing Index. Social Indicators Research, 91(2), 243-258, https://doi.org/10.1007/s11205-008-9280-1
Coronicova Hurajova, J., & Hajduova, Z. (2021). Multiple-Criteria Decision Analysis Using TOPSIS and WSA Method for Quality of Life: The Case of Slovakia Regions. Mathematics, 9(19), 2440. https://doi.org/10.3390/math9192440
Costa, D. S. J. (2015). Reflective, causal, and composite indicators of quality of life: A conceptual or an empirical distinction? Quality of Life Research, 24(9), 2057-2065. https://doi.org/10.1007/s11136-015-0954-2
Costanza, R., Fisher, B., Ali, S., Beer, C., Bond, L., Boumans, R., & Farley, J. (2007). Quality of life: An approach integrating opportunities, human needs, and subjective well-being. Ecological Economics, 61(2-3), 267-276. https://doi.org/10.1016/j.ecolecon.2006.02.023
Cummins, R. A. (2000). Objective and subjective quality of life: An interactive model. Social Indicators Research, 52(1), 55-72. https://doi.org/10.1023/A:1007027822521
de Guimarães, J. C. F., Severo, E. A., Júnior, L. A. F., da Costa, W. P. L. B., & Salmoria, F. T. (2020). Governance and quality of life in smart cities: Towards sustainable development goals. Journal of Cleaner Production, 253, 119926. https://doi.org/10.1016/j.jclepro.2019.119926
de la Cruz, P. M., Cabral, P., & Mateu, J. (2011). Mapping the Quality of Life Experience in Alfama: A Case Study in Lisbon, Portugal. In B. Murgante, O. Gervasi, A. Iglesias, D. Taniar & B.O. Apduhan (Eds.), Computational Science and Its Applications—ICCSA 2011 (pp. 269-283). Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-21928-3_19
Diener, E., & Suh, E. (1997). Measuring quality of life: Economic, social, and subjective indicators. Social Indicators Research, 40(1), 189-216. https://doi.org/10.1023/A:1006859511756
Diener, E., Diener, M., & Diener, C. (2009). Factors Predicting the Subjective Well-Being of Nations. In E. Diener (Ed.), Culture and Well-Being: The Collected Works of Ed Diener (pp. 43-70). Dordrecht: Springer. https://doi.org/10.1007/978-90-481-2352-0_3
Diener, E., Suh, E. M., Lucas, R. E., & Smith, H. L. (1999). Subjective well-being: Three decades of progress. Psychological Bulletin, 125(2), 276-302. https://doi.org/10.1037/0033-2909.125.2.276
European Commission (2023, February 1). https://ec.europa.eu/regional_policy/information-sources/maps_en.
Feneri, A.-M., Vagiona, D., & Karanikolas, N. (2015). Multi-criteria decision making to measure quality of life: An integrated approach for implementation in the urban area of Thessaloniki, Greece. Applied Research in Quality of Life, 10(4), 573-587. https://doi.org/10.1007/s11482-014-9335-1
Garcia-Bernabeu, A., Cabello, J. M., & Ruiz, F. (2021). A Reference Point-Based Proposal to Build Regional Quality of Life Composite Indicators. Social Indicators Research, 164(1), 11-30. https://doi.org/10.1007/s11205-021-02818-0
Ge, J., & Hokao, K. (2006). Research on residential lifestyles in Japanese cities from the viewpoints of residential preference, residential choice and residential satisfaction. Landscape and Urban Planning, 78(3), 165-178. https://doi.org/10.1016/j.landurbplan.2005.07.004
Głowicka-Wołoszyn, R., Wołoszyn, A., & Wysocki, F. (2018). Quality Of Life In Polish Farmers’ Households Assessment With Topsis Method. Proceedings of the International Scientific Conference ‘Economic Sciences for Agribusiness and Rural Economy’, Warsaw, Poland, (2), 257-263. https://js.wne.sggw.pl/index.php/esare/article/view/1523. https://doi.org/10.22630/ESARE.2018.2.34
Haslauer, E., Delmelle, E. C., Keul, A., Blaschke, T., & Prinz, T. (2015). Comparing subjective and objective quality of life criteria: A case study of green space and public transport in Vienna, Austria. Social Indicators Research, 124(3), 911-927. https://doi.org/10.1007/s11205-014-0810-8
Jefmański, B. (2020). Intuitionistic Fuzzy Synthetic Measure for Ordinal Data. In: K. Jajuga, J. Batóg, M. Walesiak (Eds.) Classification and Data Analysis. SKAD 2019. Studies in Classification, Data Analysis, and Knowledge Organization. Cham: Springer. https://doi.org/10.1007/978-3-030-52348-0_4
Jefmański, B., Roszkowska, E., & Kusterka-Jefmańska, M. (2021). Intuitionistic Fuzzy Synthetic Measure on the Basis of Survey Responses and Aggregated Ordinal Data. Entropy, 23(12), 1636. https://doi.org/10.3390/e23121636
Jenks, G. F. (1967). The Data Model Concept in Statistical Mapping. International Yearbook of Cartography, 7, 186-190.
Lee, Y.-J. (2008). Subjective quality of life measurement in Taipei. Building and Environment, 43(7), 1205-1215. https://doi.org/10.1016/j.buildenv.2006.11.023
Macke, J., Casagrande, R. M., Sarate, J. A. R., & Silva, K. A. (2018). Smart city and quality of life: Citizens’ perception in a Brazilian case study. Journal of Cleaner Production, 182, 717-726. https://doi.org/10.1016/j.jclepro.2018.02.078
Marans, R. W. (2015). Quality of urban life & environmental sustainability studies: Future linkage opportunities. Habitat International, 45(1), 47-52. https://doi.org/10.1016/j.habitatint.2014.06.019
Nanor, M. A., Poku-Boansi, M., & Adarkwa, K. K. (2018). An objective analysis of the relationship between quality of life and socio-economic characteristics in Kumasi, Ghana. GeoJournal, 83(4), 835-851. https://doi.org/10.1007/s10708-017-9795-6
Roszkowska, E., & Filipowicz-Chomko, M. (2021). Measuring Sustainable Development Using an Extended Hellwig Method: A Case Study of Education. Social Indicators Research, 153, 299-322. https://doi.org/10.1007/s11205-020-02491-9
Roszkowska, E., Jefmański, B., & Kusterka-Jefmańska, M. (2022). On Some Extension of Intuitionistic Fuzzy Synthetic Measures for Two Reference Points and Entropy Weights. Entropy, 24(8), 1081. https://doi.org/10.3390/e24081081
Roszkowska, E., Kusterka-Jefmańska, M., & Jefmański, B. (2021). Intuitionistic Fuzzy TOPSIS as a Method for Assessing Socioeconomic Phenomena on the Basis of Survey Data. Entropy, 23(5), 563. https://doi.org/10.3390/e23050563
Royuela, V., Suriñach, J., & Reyes, M. (2003). Measuring quality of life in small areas over different periods of time. Social Indicators Research, 64(1), 51-74. https://doi.org/10.1023/A:1024789306734
Santos, L. D., Martins, I., & Brito, P. (2007). Measuring Subjective Quality of Life: A Survey to Porto’s Residents. Applied Research in Quality of Life, 2(1), 51-64. https://doi.org/10.1007/s11482-007-9029-z
Sőrés, A., & Pető, K. (2015). Measuring of subjective quality of life. Procedia Economics and Finance, 32, 809-816. https://doi.org/10.1016/S2212-5671(15)01466-5
Strahl, D. (Ed.). (2006). Metody oceny rozwoju regionalnego. Wrocław. Wydawnictwo Akademii Ekonomicznej im. Oskara Langego we Wrocławiu. (in Polish).
Szmidt, E. (2014). Distances and Similarities in Intuitionistic Fuzzy Sets. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-01640-5
von Wirth, T., Grêt-Regamey, A., & Stauffacher, M. (2015). Mediating Effects Between Objective and Subjective Indicators of Urban Quality of Life: Testing Specific Models for Safety and Access. Social Indicators Research, 122, 189–210. https://doi.org/10.1007/s11205-014-0682-y
Węziak-Białwolska, D. (2016). Quality of life in cities–Empirical evidence in comparative European perspective. Cities, 58, 87-96. https://doi.org/10.1016/j.cities.2016.05.016
Wysocki, F. (2010). Metody taksonomiczne w rozpoznawaniu typów ekonomicznych rolnictwa i obszarów wiejskich. Poznań: Wydawnictwo Uniwersytetu Przyrodniczego w Poznaniu. (in Polish).
Zadeh, L. A. (1965). Information and control. Fuzzy Sets, 8(3), 338-353. https://doi.org/10.1016/S0019-9958(65)90241-X
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