master's thesis
Unconstraining Methods for True Demand Estimation in Airline Revenue Management Systems

Petra Medved (2016)
Sveučilište u Zagrebu
Fakultet prometnih znanosti
Promet
Zavod za zračni promet
Metadata
TitleMetode za procjenu stvarne potražnje u sustavima za upravljanje kapacitetima zrakoplova
AuthorPetra Medved
Mentor(s)Ružica Škurla Babić (thesis advisor)
Abstract
Prognoziranje buduće potražnje za zračnim prijevozom predstavlja područje na kojem postoji velika mogućnost pogreške i velika nesigurnost. Ne postoji niti optimalna, niti jedinstvena metoda prognoziranja potražnje za zračnim prijevozom, već se radi o kombinacijama i varijacijama vrlo složenih metoda s ciljem što realnijeg predviđanja. Podaci o potražnji na realiziranim letovima u prošlosti, na kojima se temelji predviđanje buduće potražnje, najčešće ne predstavljaju stvarnu potražnju. Naime, kada se dosegne rezervacijski limit broj odbijenih zahtjeva se ne bilježi, a upravo ti podaci su bitni kako bi se dobila procijenjena stvarna potražnja. Učinkovitost neke prognostičke metode najčešće se određuje prema kriteriju točnosti, a ocjena prikladnosti izabranih metoda prognoziranja buduće potražnje zasniva se na promatranju razlika između stvarnih i predviđenih vrijednosti potražnje. Cilj rada je opisati elemente sustava za upravljanje kapacitetima zrakoplova i njihovu ulogu u procesu dodjele sjedala u pojedine klase prijevoza, te analizirati i usporediti metode za procjenu stvarne potražnje za uslugama u zračnom prometu.
Keywordsforecasting demand airline revenue management constraining data unconstraining methods statistical methods
Parallel title (English)Unconstraining Methods for True Demand Estimation in Airline Revenue Management Systems
Committee MembersStanislav Pavlin (committee chairperson)
Ružica Škurla Babić (committee member)
Mirko Tatalović (committee member)
Andrija Vidović (committee member)
GranterSveučilište u Zagrebu
Fakultet prometnih znanosti
Lower level organizational unitsPromet
Zavod za zračni promet
PlaceZagreb
StateCroatia
Scientific field, discipline, subdisciplineTECHNICAL SCIENCES
Traffic and Transport Technology
Air Traffic
Study programme typeuniversity
Study levelgraduate
Study programmeTraffic and Transport; specializations in: Road Traffic and Transport, Railway Traffic and Transport, Water Traffic and Transport, Air Traffic and Transport, Postal Traffic, Information and Communication Traffic, Urban Traffic and Transport
Study specializationAir Traffic and Transport
Academic title abbreviationmag. ing. traff.
Genremaster's thesis
Language Croatian
Defense date2016-09-27
Parallel abstract (English)
Forecasting future demand for air transport is a domain where there's a high possibility of mistake and great uncertainty. There's no optimal or unique method of forecasting demand for air transportation, it's about combinations and variations of very complex methods with a goal to have a more realistic prediction. Forecasting future demand, based on data demand on realized flights in the past, usually do not represent actual demand. As a matter of fact, when it reaches the reservation limit the number of refusals is not recorded, but these data are essential in order to obtain the estimated actual demand. The effectiveness of some forecasting method is usually determined by the criteria of accuracy, and rating the suitability of the selected method of forecasting future demand is based on the observation of the difference between actual and predicted values demand. The goal is to describe elements of Airline Revenue Management and their role in the allocation of seats in individual classes of transport, analyze and compare the methods for evaluating the actual demand for air services in air traffic.
Parallel keywords (Croatian)prognoziranje potražnje upravljanje kapacitetima zrakoplova cenzuriranje podataka metode nadogradnje statističke metode
Resource typetext
Access conditionOpen access
Terms of usehttp://rightsstatements.org/vocab/InC/1.0/
URN:NBNhttps://urn.nsk.hr/urn:nbn:hr:119:690658
CommitterMojca Brenko-Puzak