Post-scrip-retail forecasting : research and practice
Year of publication: |
2022
|
---|---|
Authors: | Fildes, Robert ; Kolassa, Stephan ; Ma, Shaohui |
Published in: |
International journal of forecasting. - Amsterdam [u.a.] : Elsevier, ISSN 0169-2070, ZDB-ID 283943-X. - Vol. 38.2022, 4, p. 1319-1324
|
Subject: | COVID-19 | Disruption | Instability | Machine learning | Omni-retailing | Online retail | Structural change | Künstliche Intelligenz | Artificial intelligence | Coronavirus | Online-Handel | Online retailing | Strukturwandel | Prognoseverfahren | Forecasting model |
-
Powering retailers' digitization through analytics and automation
Simchi-Levi, David, (2018)
-
Salari, Nooshin, (2022)
-
A computational model to predict consumer behaviour during COVID-19 pandemic
Safara, Fatemeh, (2022)
- More ...
-
Retail forecasting: research and practice
Fildes, Robert, (2019)
-
Retail forecasting : research and practice
Fildes, Robert, (2022)
-
The performance of the global bottom-up approach in the M5 accuracy competition : a robustness check
Ma, Shaohui, (2022)
- More ...