Application of Quantitative Forecasting Models in a Manufacturing Industry
| dc.contributor.author | Akeem Olanrewaju Salami Kyrian Kelechi Okpara Rahman Oladimeji Mustapha | |
| dc.date.accessioned | 2023-07-24T11:07:15Z | |
| dc.date.available | 2023-07-24T11:07:15Z | |
| dc.date.issued | 2017-07-23 | |
| dc.description.abstract | Time series forecasting analysis has become a major tool in different applications for the Manufacturing Company. Among the most effective approaches for analyzing time series data is ARIMA (Autoregressive Integrated Moving Average). In this study we used Box-Jenkins methodology to build ARIMA model for annual sales forecast for 7up Bottling Company Plc for the period from January 2010 to December 2015, given the available monthly sales data. After the model specification; the best model for production was ARIMA (1, 1, 1) and for utilization was ARIMA (0, 1, 1). A 12 months forecast have also been made to determine the expected amount of sales revenue in year 2016. The time plot reveals seasonal variation. It thus concludes that that there is increase in sales revenue of Company with time, hence these models can be adopted for sales, production, utilization and demand forecasting in Nigeria | |
| dc.identifier.issn | 2222-2839 | |
| dc.identifier.uri | https://kwasuspace.kwasu.edu.ng/handle/123456789/711 | |
| dc.language.iso | en | |
| dc.publisher | European Journal of Business and Management | |
| dc.title | Application of Quantitative Forecasting Models in a Manufacturing Industry | |
| dc.type | Article |