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Purpose: The main purpose of the work is to present the impact of standardisation methods on the ranking results. The second purpose of the article was to present Warsaw’s position in comparison with the capitals of countries from the Eurozone. Design/methodology/approach: Major European cities were assessed using Eurostat data. The proprietary Smart City Index (SCI) indicator is proposed for the study, referring to six areas of Smart City assessment. Two measures are indicated in each of them. The first is an objective measure, while the second is a subjective measure, based on the opinion of the city’s residents about the situation in the city, or their own situation. Building rankings of the cities, following normalisation methods were used and compared: unitisation, unitisation with zero minimum, normalisation in range [-1, 1], classical standardisation, Weber standardisation and two quotient methods. Findings: The best results were obtained for the classical standardisation. For this method we obtained the smallest number of consistent positions in rankings and the minimal maximum of distance between the positions in rankings. The position of Warsaw as a city in 16th position (20 of all) was confirmed regardless of the standardization method used. Originality/value: There is proposed an original method to assess cities based on Eurostat data. This method allows construction of Smart City ranking. The main value of the work is that the classical standardisation is recommended to transform the original values of individual indicators.
Słowa kluczowe
Rocznik
Tom
Strony
83--94
Opis fizyczny
Bibliogr. 18 poz.
Twórcy
autor
- Silesian University of Technology, Poland
autor
- Silesian University of Technology, Poland
Bibliografia
- 1. Ahvenniemi, H., Huovila, A., Pinto-Seppä, I., & Airaksinen, M. (2017). What are the differences between sustainable and smart cities? Cities, 60, pp. 234-245.
- 2. Albino, V., Berardi, U., & Dangelico, R.M. (2015). Smart cities: Definitions, dimensions, performance, and initiatives. Journal of urban technology, 22(1), pp. 3-21.
- 3. Berrone P., Ricart J.E., Duch A., Carrasco C. (2019). IESE Cities in Motion Index 2019, IESE, ST-509-E, 05/2019. DOI: https://dx.doi.org/10.15581/018.ST-509.
- 4. Bosch, P., Jongeneel, S., Neumann H.-M., Branislav I., Huovila, A., Airaksinen M., Pinto-Seppä I. (2017a). Recommendations for a Smart City index. CITYkeys - Smart city performance measurement framework. DOI: 10.13140/RG.2.2.20190.74562, 15.03.2019.
- 5. Bosch, P., Jongeneel, S., Rovers, V., Neumann, H.-M., Airaksinen, M., & Huovila, A. (2017b). CITYkeys indicators for smart city projects and smart cities. CITYkeys - Smart city performance measurement framework. DOI: 10.13140/RG.2.2.17148.23686, 15.03.2019.
- 6. Bosch, P., Jongeneel, S., Rovers, V., Neumann, H.-M., Airaksinen, M., & Huovila, A. (2017c). CITYkeys indicators for smart city projects and smart cities. DOI: 10.13140/RG.2.2.17148.23686, 15.03.2019.
- 7. Giffinger, R., Fertner, C., Kramar, H., Kramar, H., Kalasek, R., Pichler-Milanovic, N., Meijers, E. (2007). Smart Cities. Ranking of European medium-sized cities. Centre for Regional Science, Vienna University of Technology, http://www.smart-cities.eu/download/smart_cities_final_report.pdf, 15.03.2019.
- 8. Huovila, A., Penttinen, T., Airaksinen, M., Pinto-Seppä, I., Piira, K., & Penttinen, T. (2016, September). Smart city performance measurement system. Proceedings of the 41th IAHS World Congress Sustainability Innovation for the Future, Algarve, Portugal, pp. 13-16.
- 9. Kukuła, K. (1989). Statystyczna analiza strukturalna i jej zastosowanie w sferze usług produkcyjnych dla rolnictwa. Zeszyty Naukowe AE w Krakowie, Seria specjalna: Monografie, 89, p. 256.
- 10. Kukuła, K. (2000) Metoda unitaryzacji zerowanej. Warszawa: PWN.
- 11. Lombardi, P., Giordano, S., Caragliu, A., Del Bo, C., Deakin, M., Nijkamp, P., & Kourtit, K. (2011). An advanced triple-helix network model for smart cities performance. Vrije Universiteit Amsterdam, Research Memorandum, 2011-45, http://degree.ubvu.vu.nl/repec/vua/wpaper/pdf/20110045.pdf, 15.03.2019.
- 12. Smart City PROFILES (2013). Ergebnisse. 7.6.2013. http://www.smartcities.at/assets/03-Begleitmassnahmen/SmartCity-PDF-INTRO.pdf, 15.03.2019.
- 13. Sojda A., Owczarek T., Wolny M. (2018). Smart City w ujęciu zorientowanym na dane - Polska w bazie Eurostat. Zeszyty Naukowe Politechniki Śląskiej, seria Organizacja i Zarządzanie, 130. http://dx.doi.org/10.29119/1641-3466.2018.130.46.
- 14. Stankovic, J., Dzunic, M., Džunić, Ž., & Marinkovic, S. (2015). A multi-criteria evaluation of the European cities’ smart performance: Economic, social and environmental aspects. Zbornik radova Ekonomskog fakulteta u Rijeci, časopis za ekonomsku teoriju i praksu-Proceedings of Rijeka Faculty of Economics. Journal of Economics and Business, 35(2), pp. 519-550.
- 15. Svítek, M., Skobelev, P., & Kozhevnikov, S. (2020). Smart City 5.0 as an Urban Ecosystem of Smart Services. 10.1007/978-3-030-27477-1_33.
- 16. Szczech-Pietkiewicz, E. (2015). Smart city-próba definicji i pomiaru. Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu. Gospodarka lokalna w teorii i praktyce, 391.
- 17. Tahir, Z., & Malek, J.A. (2016). Main criteria in the development of smart cities determined using analytical method. Planning Malaysia Journal, 14(5).
- 18. UCLG (2012). Smart Cities Study: International study on the situation of ICT, innovation and knowledge in cities. Bilbao. http://www.uclg-digitalcities.org/app/uploads/2015/06/en_smartcitiesstudy.pdf, 15.03.2019.
Uwagi
PL
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-44621954-b88a-47d1-a706-857b02c9aba7