业务
路径(计算)
计算机科学
营销
运输工程
工程类
计算机网络
作者
Sagarkumar Hirpara,Pratik Parikh
标识
DOI:10.1016/j.cie.2020.106919
摘要
Abstract The physical design of a retail store is known to influence the attitude and behavior of shoppers, in turn affecting the store’s performance. While literature in retail design has alluded to the impact of changes in department placements on impulse revenue, it has not accounted for the resulting changes in shopper path. Changes in shopper path can alter a department’s visibility to shoppers passing by, which could change a department’s impulse revenue. To address this gap, we propose a model for the retail facility layout problem considering shopper path (RFLP-SP) that optimally places departments in the store in order to maximize a retailer’s expected per shopper impulse revenue. Since estimating shopper paths is difficult to express in closed analytical form, we propose a Simulated Annealing based heuristic to generate up to k alternate shortest paths that a shopper may take for a given planned purchase list. This is then embedded in a Particle Swarm Optimization based solution approach to solve the overall RFLP-SP model. Our results suggest up to 13.71% increase in impulse revenue for a deeper store over a square-shaped store, and up to 9.65% increase in one side-door store over other door combinations. Further, the derived solutions are sensitive to shopper basket size, shape of the store, number and location of doors, and adjacency requirement of the departments. We also illustrate the use of our proposed approach on an existing layout of a leading US retailer’s store.
科研通智能强力驱动
Strongly Powered by AbleSci AI