Development of S-ARIMA Model for Forecasting Demand in a Beverage Supply Chain
Demand forecasting is one of the key activities in planning the freight flows in supply chains, and accordingly it is essential for planning and scheduling of logistic activities within observed supply chain. Accurate demand forecasting models directly influence the decrease of logistics costs, sinc...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2016-11-01
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| Series: | Open Engineering |
| Subjects: | |
| Online Access: | http://www.degruyter.com/view/j/eng.2016.6.issue-1/eng-2016-0056/eng-2016-0056.xml?format=INT |
| _version_ | 1828395752816115712 |
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| author | Mircetic Dejan Nikolicic Svetlana Maslaric Marinko Ralevic Nebojsa Debelic Borna |
| author_facet | Mircetic Dejan Nikolicic Svetlana Maslaric Marinko Ralevic Nebojsa Debelic Borna |
| author_sort | Mircetic Dejan |
| collection | DOAJ |
| description | Demand forecasting is one of the key activities
in planning the freight flows in supply chains, and
accordingly it is essential for planning and scheduling
of logistic activities within observed supply chain. Accurate
demand forecasting models directly influence the decrease
of logistics costs, since they provide an assessment
of customer demand. Customer demand is a key component
for planning all logistic processes in supply chain,
and therefore determining levels of customer demand is
of great interest for supply chain managers. In this paper
we deal with exactly this kind of problem, and we develop
the seasonal Autoregressive IntegratedMoving Average (SARIMA)
model for forecasting demand patterns of a major
product of an observed beverage company. The model is
easy to understand, flexible to use and appropriate for assisting
the expert in decision making process about consumer
demand in particular periods. |
| first_indexed | 2024-12-10T08:18:21Z |
| format | Article |
| id | doaj.art-dcebe25745674999b66bdf579ae13062 |
| institution | Directory Open Access Journal |
| issn | 2391-5439 |
| language | English |
| last_indexed | 2024-12-10T08:18:21Z |
| publishDate | 2016-11-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Open Engineering |
| spelling | doaj.art-dcebe25745674999b66bdf579ae130622022-12-22T01:56:24ZengDe GruyterOpen Engineering2391-54392016-11-016110.1515/eng-2016-0056eng-2016-0056Development of S-ARIMA Model for Forecasting Demand in a Beverage Supply ChainMircetic Dejan0Nikolicic Svetlana1Maslaric Marinko2Ralevic Nebojsa3Debelic Borna4University of Novi Sad, Faculty of Technical Science/ Traffic Department, Novi Sad, SerbiaUniversity of Novi Sad, Faculty of Technical Science/ Traffic Department, Novi Sad, SerbiaUniversity of Novi Sad, Faculty of Technical Science/ Traffic Department, Novi Sad, SerbiaUniversity of Novi Sad, Faculty of Technical Science/ Traffic Department, Novi Sad, SerbiaUniversity of Rijeka, Faculty of Maritime Studies, Rijeka, CroatiaDemand forecasting is one of the key activities in planning the freight flows in supply chains, and accordingly it is essential for planning and scheduling of logistic activities within observed supply chain. Accurate demand forecasting models directly influence the decrease of logistics costs, since they provide an assessment of customer demand. Customer demand is a key component for planning all logistic processes in supply chain, and therefore determining levels of customer demand is of great interest for supply chain managers. In this paper we deal with exactly this kind of problem, and we develop the seasonal Autoregressive IntegratedMoving Average (SARIMA) model for forecasting demand patterns of a major product of an observed beverage company. The model is easy to understand, flexible to use and appropriate for assisting the expert in decision making process about consumer demand in particular periods.http://www.degruyter.com/view/j/eng.2016.6.issue-1/eng-2016-0056/eng-2016-0056.xml?format=INTconsumer demand time series S-ARIMA |
| spellingShingle | Mircetic Dejan Nikolicic Svetlana Maslaric Marinko Ralevic Nebojsa Debelic Borna Development of S-ARIMA Model for Forecasting Demand in a Beverage Supply Chain Open Engineering consumer demand time series S-ARIMA |
| title | Development of S-ARIMA Model for Forecasting
Demand in a Beverage Supply Chain |
| title_full | Development of S-ARIMA Model for Forecasting
Demand in a Beverage Supply Chain |
| title_fullStr | Development of S-ARIMA Model for Forecasting
Demand in a Beverage Supply Chain |
| title_full_unstemmed | Development of S-ARIMA Model for Forecasting
Demand in a Beverage Supply Chain |
| title_short | Development of S-ARIMA Model for Forecasting
Demand in a Beverage Supply Chain |
| title_sort | development of s arima model for forecasting demand in a beverage supply chain |
| topic | consumer demand time series S-ARIMA |
| url | http://www.degruyter.com/view/j/eng.2016.6.issue-1/eng-2016-0056/eng-2016-0056.xml?format=INT |
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