Impact of Information Exchange on Supplier Forecasting Performance

By Juan Ramón Trapero, Nikolaos Kourentzes, Robert Fildes. 2012

134 citations recorded by the source corpus.

Subfields: Management Information Systems, Management Science and Operations Research

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Information Systems

1. Robert Fildes
2. Stephan Kolassa
3. Shaohui Ma

In Management Science and Operations Research

1. Christoph Bergmeir
2. Kasun Bandara
3. Shaohui Ma
4. Robert Fildes
5. Slawek Smyl
6. Stephan Kolassa
7. Fotios Petropoulos
8. Rob J Hyndman

Citations in the corpus

• Forecasting Across Time Series Databases using Long Short-Term Memory Networks on Groups of Similar Series (2017, background): “ds (Adya and Collopy, 1998; Zhang et al., 1998; Crone et al., 2011). Though some works have shown that NNs can be competitive even in situations where few data is available (Kourentzes et al., 2014a; Trapero et al., 2012), they typically realize their full potential in situations with more data. Fro”
• Retail forecasting: Research and practice (2019, background): “Empirical models analyzing the relationship between POS data and manufacturing forecast accuracy show improvements are possible though not inevitable (Hartzel and Wood, 2017;Trapero, Kourentzes, and Fildes, 2012; Williams, Waller, Ahire, and 18 Ferrier, 2014).”
• Forecasting across time series databases using recurrent neural networks on groups of similar series: A clustering approach (2017, background): “Though some works have shown that NNs can be competitive even in situations where few data is available (Kourentzes et al., 2014a; Trapero et al., 2012), they typically realize their full potential in situations with more data.”