Saudi Oil Export Forecasting
dc.contributor.author | Almaktoom, Abdulaziz | |
dc.contributor.author | Bajafar, Lama | |
dc.contributor.author | Beran, Tasnim | |
dc.contributor.author | Shafaamri, Asmaa | |
dc.date.accessioned | 2023-05-07T07:40:55Z | |
dc.date.available | 2023-05-07T07:40:55Z | |
dc.date.issued | 2022-12-29 | |
dc.identifier.uri | http://hdl.handle.net/20.500.14131/780 | |
dc.description.abstract | This 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.sponsorship | Department of Operations and Supply Chain Management | en_US |
dc.description.sponsorship | Effat University | en_US |
dc.publisher | Proceedings of the International Conference on Management and Social Sciences (ICMSS-2022), Bangkok, Thailand, December 28-29, 2022. | en_US |
dc.subject | Forecasting | en_US |
dc.title | Saudi Oil Export Forecasting | en_US |
dc.contributor.researcher | Department Collaboration | en_US |
dc.contributor.ugstudent | Lama Bajafar, Tasnim Beran, Asmaa Shafaamri | en_US |
dc.title.project | Saudi Oil Export Forecasting | en_US |
dc.contributor.department | Supply Chain Management | en_US |
dc.contributor.firstauthor | Bajafar, Lama |