The Complexity of Shelflisting

TL;DR

This paper investigates the computational complexity of optimal shelflisting, considering different consumer decision models and how preference structures and product arrangement directions influence the problem.

Contribution

It provides new complexity results for product arrangement problems under various consumer behavior models and preference structures.

Findings

Complexity depends on the size of consumers' top cycle.

Preference direction impacts the computational difficulty.

Different consumer decision models lead to varying complexity results.

Abstract

Optimal shelflisting invites profit maximization to become sensitive to the ways in which purchasing decisions are order-dependent. We study the computational complexity of the corresponding product arrangement problem when consumers are either rational maximizers, use a satisficing procedure, or apply successive choice. The complexity results we report are shown to crucially depend on the size of the top cycle in consumers' preferences over products and on the direction in which alternatives on the shelf are encountered.