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Title:Napovedovanje prihoda ameriških turistov v Slovenijo
Authors:ID Babić, Irena (Author)
ID Dragan, Dejan (Mentor) More about this mentor... New window
Files:.pdf UN_Babic_Irena_2019.pdf (2,23 MB)
MD5: 289CA4051FACF56AAE5C2FADDBB31F9C
PID: 20.500.12556/dkum/56e46c15-016c-414f-98e1-1750940a37db
 
Language:Slovenian
Work type:Bachelor thesis/paper
Organization:FL - Faculty of Logistic
Abstract:Napovedovanje je v poslovnem okolju ključnega pomena za pravilno sprejemanje poslovnih odločitev in zmanjšanje tveganj le teh ter za uspešno in učinkovito poslovanje, kar velja tudi za turistični sektor. Pri tem je natančno napovedovanje bodočih turističnih trendov še posebej pomembno za pravilno planiranje bodočih investicij v turistično infrastrukturo, saj napačne investicije na osnovi napačnih napovedi lahko vodijo v velike izgube. V okviru načrtovanja modelov za napovedovanje je izrednega pomena ustrezen izbor matematičnih in statističnih metod, na osnovi katerih bo prediktivni model zagotavljal dobre napovedi. V turističnih oskrbovalnih verigah se napovedi turističnega povpraševanja prav tako uporabljajo za zmanjšanje tveganj odločitev in stroškov, da ne bi prišlo do napačnih poslovnih potez in investicij v turistične objekte. V naši diplomski nalogi smo testirali in primerjali dve metodi, in sicer metodo Holt-Winters (HW) in Multiplo linearno regresijo (MLR). Pri metodi HW smo uporabili zgodovinske podatke o prihodu ameriških turistov v Slovenijo. Pri MLR pa smo poleg podatkov o prihodu ameriških turistov, torej časovne vrste, ki jo napovedujemo, uporabili tudi eksogene makroekonomske kazalnike gospodarstva ZDA kot vhodne regresorske časovne vrste. Rezultati so pokazali, da se model MLR nekoliko bolje prilega dejanskim podatkom v primerjavi z modelom HW. Torej dodatne informacije, ki jih nosijo eksogeni kazalniki, pripomorejo k boljšemu opisu dinamike gibanja prihodov ameriških turistov. Poleg same analize dinamike gibanja prihodov turistov nas je zanimalo tudi napovedovanje, kjer smo uporabili model HW, s katerim smo izračunali napovedi prihodnjih prihodov turistov za štiri četrtletja.
Keywords:napovedovanje, Holt-Winters metoda, multipla linearna regresija, makroekonomski kazalniki, ameriški turisti
Place of publishing:Celje
Publisher:[I. Babić]
Year of publishing:2019
PID:20.500.12556/DKUM-73022 New window
UDC:519.2
COBISS.SI-ID:512980797 New window
NUK URN:URN:SI:UM:DK:ZXULE5NS
Publication date in DKUM:04.04.2019
Views:1491
Downloads:111
Metadata:XML DC-XML DC-RDF
Categories:FL
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Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:21.01.2019

Secondary language

Language:English
Title:Forecasting of American tourists' arrival to Slovenia
Abstract:Predictions are key for making right business decisions in the business world and reducing risks of these decisions as well as successful and efficient business; this is also true for the tourist sector. Accurate predictions of future tourist trends are especially important for planning future investments into tourist infrastructure, because incorrect investments based on incorrect predictions can lead to great losses. When planning models for predictions, it is crucial to produce an appropriate selection of mathematical and statistical methods based on which the prediction model will ensure good predictions. In tourist supply chains, the predictions of tourist demand can also be used to minimise the risk of decisions and costs so as to avoid incorrect business decisions and investments in tourist infrastructure. The graduation thesis tests and compares two methods the Holt-Winters (HW) and the Multiple Linear Regression (MLR) method. The HW method uses historical data about American tourists visiting Slovenia. In MLR, the data about American tourists in Slovenia, i. e. temporal category we are predicting, was complemented with exogenous macro-economic indexes for the American economy as regression temporal categories. Results show the MLR model fits the real data a bit better compared to the HW model. Thus, additional information carried by the exogenous indexes help describe the dynamics of the trend of American tourists visiting Slovenia. Beside the analysis of the dynamics of the trend of American tourists visiting Slovenia the graduation thesis also explores predictions made with the help of the HW model which was used to calculate the predictions of future tourist visits for 4 quarters.
Keywords:predictions, the Holt-Winters method, multiple linear regression, macro-economic indexes, American tourists


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