Tytuł artykułu
Treść / Zawartość
Pełne teksty:
Identyfikatory
Warianty tytułu
Usability evaluation of the qualitative method of estimating the demand for inland shipping serving the seaport hinterland
Języki publikacji
Abstrakty
Znane metody prognozowania zapotrzebowania na transport towarów oparte są na danych szeregów czasowych, które nie zawsze są dostępne. Celem artykułu jest ocena użyteczności metody jakościowej szacowania popytu na przewozy ładunków żeglugą śródlądową na zapleczu portów morskich w przypadku niedostępności danych historycznych. Oceniana metoda obejmuje pięć etapów i opiera się na badaniu popytu, które przeprowadzono wśród gestorów ładunków. Weryfikację przeprowadzono na przykładzie Odrzańskiej Drogi Wodnej, analizując potencjalne operacje wykonywane w ramach żeglugi śródlądowej do/z portów morskich w Szczecinie i Świnoujściu, przy założeniu, że droga wodna została zmodernizowana do klasy żeglowności III. Uzyskane wyniki badań pozwoliły określić zalety i wady prognozowania opartego na badanej metodzie jakościowej, wskazując na jej użyteczność, i mogą być przydatne dla zarządów portów morskich, spedytorów, firm transportowych i instytucji rządowych podejmujących decyzje w zakresie rozwoju infrastruktury śródlądowych dróg wodnych.
Known methods of forecasting the demand for goods transport are based on given time series, which are not always available. The article aims to assess the usefulness of the qualitative method of estimating the demand for cargo transport by inland waterways in seaports hinterland when historical data are unavailable. The assessed method consists of five stages and is based on a demand survey, which was carried out among cargo senders. The verification performed on the Oder Waterway example, analysing potential operations performed in inland shipping to/from seaports in Szczecin and Świnoujście, on the assumption that the Waterway has been modernized to navigability class III. Obtained research results allowed to determine the strengths and weaknesses of predicting using analysed qualitative method pointing to its usability and can be useful for seaports authorities, forwarders, transport companies and government institutions making decisions regarding the development of inland waterway infrastructure.
Wydawca
Czasopismo
Rocznik
Tom
Strony
76--86
Opis fizyczny
Bibliogr. 46 poz., rys., tab., wykr.
Twórcy
- Wydział Techniki Morskiej i Transportu, Zachodniopomorski Uniwersytet Technologiczny w Szczecinie, Al. Piastów 41, 71-065 Szczecin
autor
- Wydział Inżynieryjno-Ekonomiczny Transportu, Akademia Morska w Szczecinie, Henryka Pobożnego 11, 70-507 Szczecin
autor
- Instytut Zarządzania, Uniwersytet Szczeciński, Al. Papieża Jana Pawła II 22A, 70-453 Szczecin
autor
- Instytut Zarządzania, Uniwersytet Szczeciński, Al. Papieża Jana Pawła II 22A, 70-453 Szczecin
Bibliografia
- [1] Abdelwahab W., Sargious M., 1992, Modelling the demand for freight transport: a new approach, Journal of Transport, Economics and Policy, 26, 49-70.
- [2] Achmadi T., Nur H. I., Rahmadhon L. R., 2018, Analysis of inland waterway transport for container shipping: Cikarang to port of TanjungPriok, in 4th International Seminar on Ocean and Coastal Engineering, Environmental and Natural Disaster Management (ISOCEEN) Book Series: IOP Conference Series-Earth and Environmental Science, 135, UNSP 012015.
- [3] Archer B. H., 1980, Forecasting demand: quantitative and intuitive techniques, International Journal of Tourism Management, 1, 5-12.
- [4] Atasoy B., Glerum A., Hurtubia R., Bierlaire M., 2010, Demand for public transport services: Integrating qualitative and quantitative methods, 10th Swiss Transport Research Conference.
- [5] Chrobok R., Kaumann O., Wahle J., Schreckenberg M., 2004, Different methods of traffic forecast based on real data. European Journal of Operational Research, 155, 558-568.
- [6] Dai Q., Yang J. Q., Li D., 2018, Modeling a three-mode hybrid port-hinterland freight intermodal distribution network with environmental consideration: The case of the Yangtze economic belt river in China, Tainability, 10(9), 3081.
- [7] Daziano R. A., Bolduc D., 2013, Incorporating pro-environmental preferences towards green automobile technologies through a Bayesian hybrid choice model, Transportmetrica A: Transport Science, 9, 74-106.
- [8] De Jong G., Gunn H., Walker W., 2004, National and international freight transport models: an overview and ideas for future development, Transport Reviews, 24, 103-124.
- [9] De Jong G., Kouwenhoven M., Ruijs K., van Houwe P., Borremans D., 2016, A time-period choice model for road freight transport in Flanders based on stated preference data. Transportation Research Part E: Logistics and Transportation Review, 86, 20-31.
- [10] Deng A.M., Tao B., 2012, The Coordinated Development of Inland Shipping and Comprehensive Transportation System [w:] M. Nelles, K. Wu, I. Cai, J. J. Cheng (eds.), Proceedings of The 4th International Conference on Environmental Technology and Knowledge Transfer, 754-758.
- [11] El Zarwi F., Vij A., Walker J. L., 2017, A discrete choice framework for modeling and forecasting the adoption and diffusion of new transportation services, Transportation Research Part C: Emerging Technologies, 79, 207-223.
- [12] Filina-Dawidowicz L., Kotowska I., Mańkowska M., Pluciński M., 2018, A method to estimate the demand for freight transport in absence of historical data. A case study of the Oder Waterway, SHS Web of Conferences, 58, 01009, 1-10.
- [13] Filina-Dawidowicz L., Postan M. Ya., 2018, Stochastic model of deteriorating cargo transshipment at port’s terminal under irregular arrival of ships, SHS Web of Conferences, 58, 01010 (2018), 1-10.
- [14] Hann M., Piotrowski L., Woś K., 2016, A new concept for utilising the Oder waterway in intermodal container transport. Scientific Journals of the Maritime University of Szczecin, 47, 129-135.
- [15] Hensher D. A., Button K. J. (eds.), 2007, Handbook of transport modelling, Emerald Group Publishing Limited.
- [16] Howe C. W., Carroll J. L., Hurter Jr A. P., Leininger W.J., Ramsey S. G., Schwartz N.L., Silberberg E., Steinberg R. M., 2016, Inland waterway transportation: studies in public and private management and investment decisions, Routledge.
- [17] Konings R., 2006, Hub-and-spoke networks in container-on-barge transport [w:] Inland Waterways, Ports, And Shipping, Book Series: Transportation Research Record, 1963, 23-32.
- [18] Kotowska I., Mańkowska M., Pluciński M., 2018a, The Competitiveness of Inland Shipping in Serving the Hinterland of the Seaports: A Case Study of the Oder Waterway and the Szczecin-Świnoujście Port Complex [w:] Scientific And Technical Conference Transport Systems Theory And Practice, Springer, Cham, 252-263.
- [19] Kotowska I., Mankowska M., Plucinski M., 2018b, Inland shipping to serve the hinterland: the challenge for seaport authorities, Sustainability, 10(10), 3468.
- [20] Li Y.-T., Schmöcker J.-D., Fujii S., 2015, Demand adaptation towards new transport modes: The case of high-speed rail in Taiwan, Transportmetrica B, 3(1), 27-43.
- [21] Li J. Y., Notteboom T. E., Wang J. J., 2017, An institutional analysis of the evolution of inland waterway transport and inland ports on the Pearl River, GeoJournal, 82(5), 867-886.
- [22] Liu J., Guan W., 2004, A summary of traffic flow forecasting methods, Journal of Highway and Transportation Research and Development, 3, 82-85.
- [23] Liu S. M., Zheng K., Wu Z. L., Wang N., 2015, New inland river channel transit capacity evaluation method based on dynamic quaternion ship domain model, 54th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE), 652-656.
- [24] Matsumoto R., Okuda D., Fukasawa N., 2018, Method for forecasting fluctuation in railway passenger demand for high-speed rail services, Quarterly Report of RTRI (Railway Technical Research Institute), 59(3), 194-200.
- [25] Meißner D., Klein B., Ionita M., 2017, Development of a monthly to seasonal forecast framework tailored to inland waterway transport in central Europe, Hydrology and Earth System Sciences, 21(12), 6401-6423.
- [26] MGMiŻŚ, 2016, Założenia do planów rozwoju śródlądowych dróg wodnych w Polsce na lata 2016-2020 z perspektywą do roku 2030, dokument przyjęty Uchwałą nr 79 Rady Ministrów dnia 14 czerwca 2016 r.
- [27] Ortuzar J. D. D., Willumsen L. G., 2011, Modelling transport, John Wiey & Sons Ltd., New Delhi.
- [28] Patriksson M., 2015, The traffic assignment problem: models and methods, Courier Dover Publications.
- [29] Postan M., Filina-Dawidowicz L., 2016, Dynamic optimization model for planning of supply, production, and transportation of perishable product [w:] M. Suchanek (eds.), Sustainable Transport Development, Innovation and Technology. TranSopot 2016, Springer Proceedings in Business and Economics, Springer, 235-244.
- [30] Qin J., He Y. X., Ni L. L., 2014, Quantitative efficiency evaluation method for transportation networks, Sustainability, 6(12), 8364-8378.
- [31] Rashed Y., Meersman H., Sys C., Van de Voorde E., Vanelslander T., 2018, A combined approach to forecast container throughput demand: Scenarios for the Hamburg-Le Havre range of ports, Transportation Research Part A: Policy and Practice, 117, 127-141.
- [32] Rolbiecki R., 2012, Badania popytu na przewozy ładunków transportem wodnym śródlądowym, Zeszyty Naukowe Uniwersytetu Gdańskiego. Ekonomika Transportu i Logistyka, 43, 41-50.
- [33] Sihn W., Pascher H., Ott K., Stein S., Schumacher A., Mascolo G., 2015, A green and economic future of inland waterway shipping [w:] S. Kara (ed.), 22ND CIRP Conference On Life Cycle Engineering, Procedia CIRP, 29, 317-322.
- [34] Sun Y., Liang X., Li X. Y., Zhang C., 2019, A Fuzzy Programming method for modeling demand uncertainty in the capacitated road-rail multimodal routing problem with time windows, Symmetry-Basel, 11(1), 91.
- [35] Szeto W. Y., 2016, Guest Editorial: Special Issue on Quantitative Approaches to Environmental Sustainability in Transportation Networks, Networks and Spatial Economics, 16, 1-8 (DOI 10.1007/s11067-015-9296-4).
- [36] Szeto W. Y., Jiang Y., Wang D. Z. W., Sumalee A., 2015, A sustainable road network design problem with land use transportation interaction over time, Networks and Spatial Economics, 15, 791-822.
- [37] Tan Z. J., Li W., Zhang X. N., Yang H., 2015, Service charge and capacity selection of an inland river port with location-dependent shipping cost and service congestion, Transportation Research Part E-Logistics and Transportation Review, 76, 13-33.
- [38] Tan Z. J., Meng Q., Wang F., Kuang H. B., 2018b, Strategic integration of the inland port and shipping service for the ocean carrier, Transportation Research Part E-Logistics and Transportation Review, 110, 90-109.
- [39] Tan Z. J., Wang Y. D., Meng Q., Liu Z. X., 2018a, Joint ship schedule design and sailing speed optimization for a single inland shipping service with uncertain dam transit time, Transportation Science, 52(6), 1570-1588.
- [40] Tortum A., Yayla N., Gokdag M., 2009, The modeling of mode choices of intercity freight transportation with the artificial neural networks and adaptive neuro-fuzzy inference system, Expert Systems With Applications, 36(3), 6199-6217.
- [41] Valdas A., Ruus R., Poldaru R., Roots J., 2016, Forecasting road freight transport alternatives for sustainable regional development in Estonia, Economic Science for Rural Development Conference Proceedings, 42, 171-178.
- [42] Vlahogianni E. I., Golias J. C., Karlaftis M. G., 2004, Short-term traffic forecasting: Overview of objectives and methods, Transport Reviews, 24, 533-557.
- [43] Washington S. P., Karlaftis M. G., Mannering F., 2010, Statistical and econometric methods for transportation data analysis, CRC press.
- [44] Wegener M., 2004, Overview of land use transport models, Handbook of transport geography and spatial systems, Emerald Group Publishing Limited, 127-146.
- [45] Wiegmans B., Konings R., 2015, Intermodal inland waterway transport: modelling conditions influencing its cost competitiveness, The Asian Journal of Shipping and Logistics, 31, 273-294.
- [46] Xu X., Li R.-W., Zhao Y., Wu X.-L., Nyberg T., 2018, Demand forecasting of transportation service network of food cold chain based on a combined model of trend double exponential smoothing and improved grey methods, International Journal of Wireless and Mobile Computing, 15(1), 1-9.
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-979fdfdb-b524-4b5f-89c9-baf6147a0ded