INVESTIGATION OF ASSOCIATION MODELS TO DESCRIBE CONSUMER PURCHASE PATTERNS

M. Hall, N.J. Kusabs, D. Gillgren, G. Holmes, A.F. Bollen
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.
Hall, M., Kusabs, N.J., Gillgren, D., Holmes, G. and Bollen, A.F. (2001). INVESTIGATION OF ASSOCIATION MODELS TO DESCRIBE CONSUMER PURCHASE PATTERNS. Acta Hortic. 566, 167-173
DOI: 10.17660/ActaHortic.2001.566.19
https://doi.org/10.17660/ActaHortic.2001.566.19
data mining, association rules, supermarket, meat, Apriori algorithm
English

Acta Horticulturae