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dc.contributor.authorAlmaktoom, Abdulaziz
dc.contributor.authorBajafar, Lama
dc.contributor.authorBeran, Tasnim
dc.contributor.authorShafaamri, Asmaa
dc.date.accessioned2023-05-07T07:40:55Z
dc.date.available2023-05-07T07:40:55Z
dc.date.issued2022-12-29
dc.identifier.urihttp://hdl.handle.net/20.500.14131/780
dc.description.abstractThis study aims to show how the oil industry may affects the Saudi oil exports. The oil price has been uneven in recent years. In this paper, several forecasting methods been evaluated to help augmenting oil export prediction accuracy. In this paper, several forecasting methods were applied to the data collected and errors been measured. As a result, based on Mean Forecast Error (BIAS), the linear regression method was the best because it has the lowest error value. This indicates that there will be variation in the demand which means the accurate prediction will help on oil production demand planning. The data used was collected from Aramco's annual report, the Saudi General Authority for Statistics, and online newspapers.en_US
dc.description.sponsorshipDepartment of Operations and Supply Chain Managementen_US
dc.description.sponsorshipEffat Universityen_US
dc.publisherProceedings of the International Conference on Management and Social Sciences (ICMSS-2022), Bangkok, Thailand, December 28-29, 2022.en_US
dc.subjectForecastingen_US
dc.titleSaudi Oil Export Forecastingen_US
dc.contributor.researcherDepartment Collaborationen_US
dc.contributor.ugstudentLama Bajafar, Tasnim Beran, Asmaa Shafaamrien_US
dc.title.projectSaudi Oil Export Forecastingen_US
dc.contributor.departmentSupply Chain Managementen_US
dc.contributor.firstauthorBajafar, Lama


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