Articles
INVESTIGATION OF ASSOCIATION MODELS TO DESCRIBE CONSUMER PURCHASE PATTERNS
Article number
566_19
Pages
167 – 173
Language
English
Abstract
Maximising returns to all supply chain participants requires presentation of an appropriate range of products and qualities to the consumer.
Understanding and modeling consumer response and purchase behaviour assists in the management of product quality, product display and specialing by retailers.
This paper explores the use of certain data mining techniques, in particular association rule learning, to describe consumer buying patterns in a supermarket.
The primary case study involved analysis of meat purchases, to identify relationships between differing quality meats.
We discuss the strengths of the approach and have identified avenues where there is potential to enhance such models for perishable produce.
Understanding and modeling consumer response and purchase behaviour assists in the management of product quality, product display and specialing by retailers.
This paper explores the use of certain data mining techniques, in particular association rule learning, to describe consumer buying patterns in a supermarket.
The primary case study involved analysis of meat purchases, to identify relationships between differing quality meats.
We discuss the strengths of the approach and have identified avenues where there is potential to enhance such models for perishable produce.
Authors
M. Hall, N.J. Kusabs, D. Gillgren, G. Holmes, A.F. Bollen
Keywords
data mining, association rules, supermarket, meat, Apriori algorithm
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