Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Using association rules for product assortment decisions: a case study
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
A data mining approach to product assortment and shelf space allocation
Expert Systems with Applications: An International Journal
ICACTE '08 Proceedings of the 2008 International Conference on Advanced Computer Theory and Engineering
Hi-index | 12.05 |
Marketing research has suggested that the in-store stimuli such as shelf-space allocation and product assortment have great influence on customer buying behaviour and may induce sales by maximizing impulse buying and cross-selling. The previous studies, however, have ignored the effect of product price in shelf-space arrangement. That is, they study the relationship between products and their simultaneous sales in a static fashion, disregarding the dynamic changes of their prices. The changes in product price may change the association between products such as complementarity and substitutability relationships. Consequently, it would affect the applied strategies of shelf allocation. In this paper a new approach is developed to optimally select and price the products and allocate them to shelf space with consideration of their prices. This paper takes advantage of data mining techniques, association rules, to find relationships between products regarding to their prices. Finally, to show the efficiency and effectiveness of the proposed approach, the experiment on real world data is executed.