| Forecasting: theory and practice F Petropoulos, D Apiletti, V Assimakopoulos, MZ Babai, DK Barrow, ... International Journal of Forecasting 38 (3), 705-871, 2022 | 626 | 2022 |
| Demand forecasting by temporal aggregation B Rostami‐Tabar, MZ Babai, A Syntetos, Y Ducq Naval Research Logistics (NRL) 60 (6), 479-498, 2013 | 97 | 2013 |
| Demand forecasting by temporal aggregation: Using optimal or multiple aggregation levels? N Kourentzes, B Rostami-Tabar, DK Barrow Journal of Business Research 78, 1-9, 2017 | 65 | 2017 |
| Forecasting COVID-19 daily cases using phone call data B Rostami-Tabar, JF Rendon-Sanchez Applied soft computing 100, 106932, 2021 | 49 | 2021 |
| Neural network approach to lumpy demand forecasting for spare parts in process industries MR Amin-Naseri, BR Tabar 2008 International Conference on Computer and Communication Engineering …, 2008 | 47 | 2008 |
| Non-stationary demand forecasting by cross-sectional aggregation B Rostami-Tabar, MZ Babai, Y Ducq, A Syntetos International Journal of Production Economics 170, 297-309, 2015 | 44 | 2015 |
| A novel ranking procedure for forecasting approaches using Data Envelopment Analysis A Emrouznejad, B Rostami-Tabar, K Petridis Technological Forecasting and Social Change 111, 235-243, 2016 | 41 | 2016 |
| Demand forecasting in supply chains: a review of aggregation and hierarchical approaches MZ Babai, JE Boylan, B Rostami-Tabar International Journal of Production Research 60 (1), 324-348, 2022 | 37 | 2022 |
| A hybrid neural network and traditional approach for forecasting lumpy demand A Nasiri Pour, B Rostami-Tabar, A Rahimzadeh Proceedings of the World Academy of Science, Engineering and Technology 2 (4), 2008 | 37 | 2008 |
| Forecasting hierarchical time series in supply chains: an empirical investigation D Mircetic, B Rostami-Tabar, S Nikolicic, M Maslaric International Journal of Production Research 60 (8), 2514-2533, 2022 | 36 | 2022 |
| A note on the forecast performance of temporal aggregation ASYD Bahman Rostami-Tabar, Mohamed Zied Babai Naval Research Logistics (NRL), 2014 | 29 | 2014 |
| The impact of temporal aggregation on supply chains with ARMA (1, 1) demand processes B Rostami-Tabar, MZ Babai, M Ali, JE Boylan European Journal of Operational Research 273 (3), 920-932, 2019 | 23 | 2019 |
| Anticipating special events in emergency department forecasting B Rostami-Tabar, F Ziel International Journal of Forecasting 38 (3), 1197-1213, 2022 | 20 | 2022 |
| Probabilistic forecasting of hourly emergency department arrivals B Rostami-Tabar, J Browell, I Svetunkov Health Systems 13 (2), 133-149, 2024 | 9 | 2024 |
| Integrated demand forecasting and planning model for repairable spare part: an empirical investigation V Babaveisi, E Teimoury, MR Gholamian, B Rostami-Tabar International Journal of Production Research 61 (20), 6791-6807, 2023 | 9 | 2023 |
| Forecasting for social good B Rostami-Tabar, MM Ali, T Hong, RJ Hyndman, MD Porter, A Syntetos International Journal of Forecasting 38 (3), 1245-1257, 2022 | 9 | 2022 |
| To aggregate or not to aggregate: Forecasting of finite autocorrelated demand B Rostami-Tabar, MZ Babai, A Syntetos Journal of the Operational Research Society 74 (8), 1840-1859, 2023 | 7 | 2023 |
| ARIMA demand forecasting by aggregation BR Tabar Bordeaux 1, 2013 | 7 | 2013 |
| Demand forecasting for executives and professionals S Kolassa, B Rostami-Tabar, E Siemsen CRC Press, 2023 | 6 | 2023 |
| The value of point of sales information in upstream supply chain forecasting: an empirical investigation M Abolghasemi, B Rostami-Tabar, A Syntetos International Journal of Production Research 61 (7), 2162-2177, 2023 | 5 | 2023 |
