Enabling effective and fast decision-making in organisations: forecasting with the Theta Method [REF2021]
Impact Summary for the General Public
Nikolopoulos’ research focuses on Predictive Analytics employing the Theta forecasting method he initially developed. His empirical research at Bangor University has led to significant efficiency savings and enhanced decision-making for multinational companies by improving forecasts. Nikolopoulos’ forecasting models have proven accuracy and superior computational speed in international competitions. Uber has applied Nikolopoulos’ Theta models worldwide since 2017 for their financial forecasts with an efficiency saving of over approximately USD750,000,000 (04-2020) per annum. BOSCH and Amazon Web Services use Theta for forecasting product demands and sales. The wider use of Nikolopoulos’ Theta Method within commerce is highlighted by over 6,500,000 downloads of the implementation of the Theta Method within the freeware R package.
Category of impact
- Economic
Research outputs (5)
- Published
Forecasting with the Theta Method
Research output: Chapter in Book/Report/Conference proceeding › Entry for encyclopedia/dictionary › peer-review
- Published
On the M4.0 forecasting competition: Can you tell a 4.0 earthquake from a 3.0?
Research output: Contribution to journal › Article › peer-review
- Published
Forecasting with a hybrid method utilizing data smoothing, a variation of the Theta method and shrinkage of seasonal factors
Research output: Contribution to journal › Article › peer-review