Impact Of Purchase Dependency On Retail Multi-Item Inventory Management

Abstract

The Research Incorporated In The Thesis Makes An Attempt To Account For Purchase Dependency In Retail Multi-Item Inventory Management With Large Number Of Items. Dependence Of Purchase Of An Item (Or A Number Of Items) On The Purchase Of Another Item (Or A Number Of Items) Has Been Referred As Purchase Dependency In The Thesis. The Present Research Work Suggests Model For Finding Purchase Dependency And Making Use Of Them In Designing Inventory Replenishment In Retail Multi-Item Inventory. According To The Research, Purchase Dependencies In Retail Sale Can Be Extracted Through Data Mining. Purchase Dependency Leads To Lost Sale Of Several Items And Increase In The Holding Cost Of Unsold Inventories. The Research Also Shows That There May Be Unimportant Or Less Important B Or C-Class Items With An Impact On The Purchase Of A-Class Items. To Minimize The Lost Sale Cost Of Such A-Class Items, These B Or C-Class Items (Having An Impact On The Purchase Of A-Class Items) Should Be Treated At Par With The A-Class Items. To Design Inventory Replenishment Policy For Retail Multi-Item Inventory With Large Number Of Items With Purchase Dependencies, Simulation Can Be Used To Compare Different Applicable Inventory Replenishment Policies. A Procedure To Simulate Various Applicable Inventory Replenishment Policies In The Context Of Purchase Dependency Has Been Explained And Illustrated With Examples. Customer Profile-Induced Purchase Dependencies Have Also Been Addressed In The Thesis. Quantitative Association Rules Can Provide More Valuable Input Than Binary Association Rules In Designing Inventory Replenishment Policy In Retail Sale. The Thesis Gives A Technique For Mining Generalized Quantitative Association Rules In The Context Of Retail Sale.