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master's thesis
Metode prognoze potražnje u lancu opskrbe
Zagreb: University of Zagreb, Faculty of Transport and Traffic Sciences, 2019. urn:nbn:hr:119:302085
Jazbec, Mirna Sofie
University of Zagreb
Faculty of Transport and Traffic Sciences
Division of Intelligent Transport Systems and Logistics
Department of Transport Logistics

Institutional repository: Faculty of Transport and Traffic Sciences

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Jazbec, M. S. (2019). Metode prognoze potražnje u lancu opskrbe (Master's thesis). Zagreb: University of Zagreb, Faculty of Transport and Traffic Sciences. Retrieved from https://urn.nsk.hr/urn:nbn:hr:119:302085

Jazbec, Mirna Sofie. "Metode prognoze potražnje u lancu opskrbe." Master's thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, 2019. https://urn.nsk.hr/urn:nbn:hr:119:302085

Jazbec, Mirna Sofie. "Metode prognoze potražnje u lancu opskrbe." Master's thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, 2019. https://urn.nsk.hr/urn:nbn:hr:119:302085

Jazbec, M. S. (2019). 'Metode prognoze potražnje u lancu opskrbe', Master's thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, accessed 25 August 2024, https://urn.nsk.hr/urn:nbn:hr:119:302085

Jazbec MS. Metode prognoze potražnje u lancu opskrbe [Master's thesis]. Zagreb: University of Zagreb, Faculty of Transport and Traffic Sciences; 2019 [cited 2024 August 25] Available at: https://urn.nsk.hr/urn:nbn:hr:119:302085

M. S. Jazbec, "Metode prognoze potražnje u lancu opskrbe", Master's thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:119:302085

Metadata
TitleMetode prognoze potražnje u lancu opskrbe
Title (english)Demand Forecasting in Supply Chain
AuthorMirna Sofie Jazbec
MentorKristijan Rogić (mentor)
Committee memberRatko Stanković (predsjednik povjerenstva)
Committee memberDarko Babić (član povjerenstva)
Committee memberMario Šafran (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Transport and Traffic Sciences
(Division of Intelligent Transport Systems and Logistics)
(Department of Transport Logistics)
Zagreb
Defense date and country2019-09-25, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Traffic and Transport Technology
Intelligent Transport Systems and Logistics
Abstract
Prognoza potražnje jedan je od elemenata upravljanja lancem opskrbe. Prognoze potražnje definiraju koji će proizvodi biti traženi, u kojoj količini i u kojem vremenskom razdoblju. Postoji nekoliko metoda prognoziranja, a to su: kvalitativne, uzročne, vremenske, prognoze istraživanjem tržišta i simulacijske. U ovom radu za izračun buduće potražnje koristit će vremenske metode prognoziranja. Vremenske metode su najčešći način prognoziranja jer se baziraju na empirijskim podacima. Što je količina empirijskih podataka veća i tržište relativno stabilno, vremenske metode su pouzdanije. Dakako, različite metode, bez obzira na količinu podataka, daju rezultate s različitim razinama točnosti, što je predmet istraživanja ovog rada. Dakle, izračun će se raditi prema unaprijed dobivenim povijesnim podacima, za različite grupe proizvoda, da se vidi kako vrsta proizvoda, sezonalnost, trendovi i ostali faktori utječu na točnost prognoze.
Abstract (english)
Demand forecast is one of elements of the supply chain management. Demand forecasts define which products will be in demand, in which quantity and in which period of time. There are several forecasting methods, which are as follows: qualitative, causal, time series, market research forecasting and simulation forecasting. In this paper, time series forecasting methods will be used in order to calculate the future demand. Time series forecasting methods are the most common forecasting methods because they are based on empirical data. The greater the quantity of empirical data, the more reliable time series forecasting methods, providing that the market is relatively stable. Of course, regardless of the quantity of data, various methods give results with various levels of accuracy, which is the subject of research of this paper. Hence, the calculation will be conducted according to historical data obtained in advance, for various groups of products, in order to demonstrate how the product type, seasonality, trends and other factors affect the accuracy of the forecast.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:119:302085
Study programmeTitle: Intelligent Transport Systems and Logistics
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka prometa (magistar/magistra inženjer/inženjerka prometa)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2020-01-27 11:07:32