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DOI
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Języki publikacji
Abstrakty
The COVID-19 pandemic is undoubtedly a global crisis that has forced the world economy to a standstill. Subsequent lockdowns have caused downtime in all industries and all transportation sectors. The removal of the restrictions has made it possible to begin a slow return to pre-pandemic conditions, but research indicates that this will be a long process. Therefore, an indication of the development trends of passenger maritime transport in Poland, considering the impact of the COVID-19 pandemic, is the purpose of the article. Two specific objectives are identified: (1) To visualize the impact of the COVID-19 pandemic on passenger maritime transport in Poland; (2) To make long-term forecasts of passenger maritime traffic in Poland. The analyses showed that the COVID-19 pandemic had a very negative impact on passenger streams. It may take several more years to recover from the pre-pandemic state.
Słowa kluczowe
Rocznik
Tom
Strony
42--47
Opis fizyczny
Bibliogr. 33 poz., rys., tab.
Twórcy
autor
- West Pomeranian University of Technology in Szczecin Department of Management and Marketing 47 Żołnierska St., 71-210 Szczecin, Poland
Bibliografia
- 1. Barczak, A. (2016) Wykorzystanie analizy harmonicznej w procesie prognozowania ruchu pasażerskiego w transporcie lotniczym na przykładzie portu lotniczego Szczecin– Goleniów. Folia Pomeranae Universitatis Technologiae Stetinensis Oeconomica 329(84)3, pp. 24–26, doi: 10.21005/ oe.2016.84.3.02.
- 2. Barczak, A. (2018) Models of time series with seasonal fluctuations in the forecasting of passenger traffic in air transport based on the study of Wrocław Airport. Transport Economics and Logistics 80, pp. 17–25, doi: 10.26881/ etil.2018.80.02.
- 3. Barczak, A., Dembińska, I., Rozmus, D. & Szopik-Depczyńska, K. (2022) The impact of COVID-19 pandemic on air transport passenger markets – Implications for selected EU airports based on time series models analysis. Sustainability 14(7), 4345, doi: 10.3390/su14074345.
- 4. Bates, J.M. & Granger, C.W.J. (1969) The combining of forecasts. Operational Research Quarterly 20.
- 5. Billah, B., King, M.L., Snyder, R. & Koehler, A.B. (2006) Exponential smoothing model selection for forecasting. International Journal of Forecasting 22(2), pp. 239– 247, doi: 10.1016/j.ijforecast.2005.08.002.
- 6. Bodo, G. & Signorini, L.F. (1987) Short-term forecasting of the industrial production index. International Journal of Forecasting 3(2), pp. 245–259, doi: 10.1016/0169- 2070(87)90006-9.
- 7. Brown, R.G. & Meyer, R.F. (1961) The fundamental theorem of exponential smoothing. Operations Research 9(5), pp. 673–685, doi: 10.1287/opre.9.5.673.
- 8. Bunn, D.W. (1978) The Synthesis of Forecasting Models in Decision Analysis. Basel: Birkhiuser Verlag.
- 9. Cieślak, M. (1970) Metody analizy rozwoju zjawisk w czasie. In: Hellwig, Z. (ed.) Zarys ekonometrii. Warszawa: PWE
- 10. Cieślak, M. (ed.) (1997) Prognozowanie gospodarcze, metody i zastosowania. Warszawa: PWN.
- 11. Clemen, R.T. (1989) Combining forecasts: A review and annotated bibliography. International Journal of Forecasting 5(4), pp. 559–583, doi: 10.1016/0169-2070(89)90012-5.
- 12. Dickinson, J.P. (1973) Some statistical results in the combination of forecasts. Operational Research Quarterly 24(2), pp. 253–260, doi: 10.2307/3007853.
- 13. Dickinson, J.P. (1975) Some comments on the combination of forecasts. Operational Research Quarterly 26(1), pp. 205–210, doi: 10.2307/3008402.
- 14. Dittmann, P. (2003) Prognozowanie w przedsiębiorstwie. Metody i ich zastosowanie. Kraków: Oficyna Wydawnicza.
- 15. European Commission (2020) Communication from the Commission Guidelines on the progressive restoration of transport services and connectivity – COVID-19 (2020/C 169/02). Official Journal of the European Union C 169/17.
- 16. German, M. (2022) Zamiast przeceniać rejsy wycieczkowe, lepiej zainwestować w agenta turystycznego. [Online] 26 May. Available from: https://turystyka.rp.pl/promy-i-statki/ art36371461-zamiast-przeceniac-rejsy-wycieczkowe-lepiej -zainwestowac-w-agenta-turystycznego [Accessed: October 18, 2023].
- 17. Jóźwiak, J. & Podgórski, J. (2009) Statystyka od podstaw. Warszawa: PWE.
- 18. Kovačević, S., Rebić, M. & Kurušić, D. (2021) The Impact of the COVID-19 Pandemic on the Labor Market of Bosnia and Herzegovina: Application of the Exponential Equalization Methods. In: 8th REDETE Conference Researching Economic Development and Entrepreneurship in Transition Economies, Geopolitics and the Political Economy of Conflict in the Balkans and the Eastern Mediterranean: Refugees, Energy Sector and Prospects for the Future. Conference Proceedings: PDF on CD ROM with full papers edited by Faculty of Economics, University of Banja Luka, pp. 106–129, available from: https://www.redete.org/assets/ content/conf-prog/conf-proceedings-2021.pdf#page=106.
- 19. Kukuła, K. (ed.) (2004) Wprowadzenie do ekonometrii w przykładach i zadaniach. Warszawa: PWN.
- 20. Łukasiewicz, A. (2022) Konsekwencje ograniczeń związanych z pandemią COVID-19 dla transportu pasażerskiego. Studia BAS 1(69), pp. 85–108.
- 21. Mancuso, A.C.B. & Werner, L. (2013) Review of combining forecasts approaches. Independent Journal of Management & Production 4(1), pp. 248–277, doi: 10.14807/ijmp. v4i1.59.
- 22. Montgomery, D.C., Gardiner, J.S. & Johnson, L.A. (1978) Forecasting & time series analysis. Journal of the Operational Research Society 29(6), p. 618, doi: 10.2307/ 3009830.
- 23. Newbold, P. & Granger, C.W.J. (1974) Experience with forecasting univariate time series and the combination of forecasts. Royal Statistical Society. Series A: General 137(2), pp. 131–146, doi: 10.2307/2344546.
- 24. Ostertagova, E. & Ostertag, O. (2011) The Simple Exponential Smoothing Model. 4th International Conference: Modelling of Mechanical and Mechatronic Systems 2011, September 20–22, 2011, Herľany, Slovak Republic.
- 25. Ostertagova, E. & Ostertag, O. (2012) Forecasting using simple exponential smoothing method. Acta Electrotechnica et Informatica 12(3), pp. 62–66, doi: 10.2478/v10198-012- 0034-2.
- 26. Pawłowski, Z. (1966) Ekonometria. Warszawa: PWN.
- 27. Poliński, J. & Ochociński, K. (2021) Wpływ pandemii COVID-19 na funkcjonowanie pasażerskiego transportu kolejowego. Problemy Kolejnictwa 190, pp. 31–43.
- 28. Statistics Poland (2021) Gospodarka morska w Polsce w 2020 r. Główny Urząd Statystyczny, Informacje sygnalne, 27.04.2021.
- 29. Statistics Poland (2022) Gospodarka morska w Polsce w 2021 r. Główny Urząd Statystyczny, Informacje sygnalne, 27.04.2022.
- 30. Üyesi, Ö. & Orkun Oralpp, I. (2019) Comparison of the winters’ seasonality exponential smoothing method with the Pegels’ Classification: Forecasting of Turkey’s economic growth rates. Anadolu Üniversitesi Sosyal Bilimler Dergisi 19, 3, pp. 281–284, https://dergipark.org.tr/en/download/ article-file/828959
- 31. Winkler, R.L. & Makridakis, S. (1983) The combination of forecasts. Journal of the Royal Statistical Society Series A (General) 146(2), pp. 150–157, doi: 10.2307/2982011.
- 32. Zawadzki, J. (ed.) (2003) Zastosowanie hierarchicznych modeli szeregów czasowych w prognozowaniu zmiennych ekonomicznych z wahaniami sezonowymi. Szczecin: Wyd. Akademii Rolniczej w Szczecinie.
- 33. Zeliaś, A., Pawełek, B. & Wanat, S. (2003) Prognozowanie ekonomiczne. Teoria, przykłady, zadania. Warszawa: PWN.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-9a8894ad-efd5-4b47-baba-20891432beb0