Turning artificial neural networks into a marketing science tool: modeling and forecasting the impact of sales promotions

Qureshi, Ibrahim Zafar, Khammash, Marv and Nikolopoulos, K (2011) Turning artificial neural networks into a marketing science tool: modeling and forecasting the impact of sales promotions. In: 3rd International Conference on Agents and Artificial Intelligence, 28-30 January 2011, Rome, Italy.

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Abstract

In this study we model the effect of promotions in time-series data and we consequently forecast that extraordinary effect via Artificial Neural Networks (ANN) as implemented from the Expert Method of a popular Artificial Intelligence software. We simulate data considering five factors as to determine the actual impact of each individual promotion. We consider additive and multiplicative models, with the later presenting both linear and non-linear relationships between those five factors; in addition, we superimpose either low or high levels of noise. Our empirical findings suggest that, for nonlinear models with high level of noise, ANN outperform all benchmarks. Standard ANN topologies work well for models with up to two factors while the Expert method provided by the software works well for higher number of factors.

Item Type: Conference or Workshop Item (Poster)
Additional Information: Paper No. 385
Schools and Departments: School of Business, Management and Economics > Business and Management
Subjects: H Social Sciences
Depositing User: Janet Snow
Date Deposited: 06 Jul 2012 11:32
Last Modified: 12 Dec 2012 17:07
URI: http://sro.sussex.ac.uk/id/eprint/39963
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