Analyzing Supermarket Shopping Paths from Indirect Observation and Simulation Study

This paper proposes a revised customer behavioral model for Agent-Based In-Store Simulator (ABISS). ABISS is able to carry out a virtual experiment of customers´ purchasing and walking behavior in the supermarket. To enhance the performance of ABISS, however, we must observe real customer behaviors and determine their behavioral parameters. In this paper, we describe a new indirect measurement method: First, we utilize a general purpose RFID tag system equipped with both in market carts and shopping places, Second, purchased items are collected with the point of sales information gathered at the cashing register places, and Third, the gathered shopping paths with purchase information are compared with intensive simulation results by ABISS. The both field study and simulation experimental results have suggested that the proposed model explains well on customer behaviors.