1999 · 364 citations · 24 references
BusinessBusiness EconomicsDecision SciencesDecision AnalysisMicroeconomicsRetail AnalyticsAssortment StrategyBasket AnalysisFrequent Pattern MiningProduct Assortment ManagementAssortment Decision Support SystemsAssortment Profitability AnalysisConvenience Store EconomicsFrequent Itemset MiningProduct Assortment Analysis
It has been claimed that the discovery of association rules is well-suited for applications of market basket analysis to reveal regularities in the purchase behaviour of customers. Moreover, recent work indicates that the discovery of interesting rules can in fact only be addressed within a microeconomic framework. This study integrates the discovery of frequent itemsets with a (microeconomic) model for product selection (PROFSET). The model enables the integration of both quantitative and qualitative (domain knowledge) criteria. Sales transaction data from a fullyautomated convenience store is used to demonstrate the effectiveness of the model against a heuristic for product selection based on product-specific profitability. We show that with the use of frequent itemsets we are able to identify the cross-sales potential of product items and use this information for better product selection. Furthermore, we demonstrate that the impact of product assortment decisions on overall assortment profitability can easily be evaluated by means of sensitivity analysis.
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Mining association rules between sets of items in large databases
Rakesh Agrawal, Tomasz Imieliński, Arun Swami · 1993 · 14.8K citations · Full text
Fast algorithms for mining association rules
Rakesh Agrawal, Ramakrishnan Srikant · 1998 · 10.8K citations
Fast discovery of association rules
Rakesh Agrawal, Heikki Mannila, Ramakrishnan Srikant et al. · Knowledge Discovery and Data Mining · 1996 · 2.3K citations