Forecasting performance of cruise passengers : the Spanish ports case
This contribution examines the passenger forecasting performance of the SARIMA method applied to cruise activities in the main Spanish ports. In this port system, the cruise activity market is characterized by different seasonal patterns (i.e., once- or twice-yearly peaks, which means unimodal or bi...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/343809 |
| Acceso en línea: | https://hdl.handle.net/2117/343809 https://dx.doi.org/10.1002/jtr.2433 |
| Access Level: | acceso abierto |
| Palabra clave: | Transportation -- Passenger traffic Passenger ships Bimodal cruise passengers forecasting seasonality spanish ports time series Transport de viatgers Vaixells de passatge Àrees temàtiques de la UPC::Nàutica::Navegació marítima::Transport marítim Àrees temàtiques de la UPC::Economia i organització d'empreses::Direcció d'operacions::Modelització de transports i logística |
| Sumario: | This contribution examines the passenger forecasting performance of the SARIMA method applied to cruise activities in the main Spanish ports. In this port system, the cruise activity market is characterized by different seasonal patterns (i.e., once- or twice-yearly peaks, which means unimodal or bimodal behavior) due to repositioning strategy. The outcome of standard indicators for accuracy testing reveals inconsistent prediction performances among ports. These inconsistencies are analyzed using an index of bimodality and seasonal variability. The forecasted values for a high-level of bimodality and seasonal variability show worse prediction performances than unimodal patterns and low seasonal variability. Ports with less passenger activity entail larger predictions errors. Exponential and linear models were adjusted between the error metrics and the mentioned indexes. |
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