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Concurrent neural network: a model of competition between times series

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https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs10479-021-04253-3;h=repec:spr:annopr:v:313:y:2022:i:2:d:10.1007_s10479-021-04253-3
Time Added
6/20/2022, 12:17:56 PM
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Neural Networks
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Authors
Rémy Garnier Rémy Garnier: Universite de Cergy-Pontoise
Abstract
Abstract Competition between times series often arises in sales prediction when similar products are on sale on a marketplace. This article provides a model of the presence of cannibalization between times series. This model creates a "competitiveness" function that depends on external features such as price and margin. It also provides a theoretical guaranty on the error of the model under some reasonable conditions and implement this model using a neural network to compute this competitiveness function. This implementation outperforms other traditional time series methods and classical neural networks for market share prediction on a real-world data set. Moreover it allows controlling underprediction which plagues traditional forecasts models.
Keywords
High dimensional times series ; Multivariate count times series ; Non-stationnary times series ; Sales forecasting ; Cannibalization ; Competition modeling ; E-commerce data (search for similar items in EconPapers)
Year Published
2022
Series
Annals of Operations Research 2022 vol. 313 issue 2 No 16 945-964
Rank
0.73
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