This paper presents results on experimental analysis on customers’ behaviors in a supermarket. The experiments are conducted in two ways. The one is to observe real behaviors of customers measured by Radio Frequency Identification (RFID) tags equipped with baskets for purchased items. We set RFID tags and antennas in a supermarket to obtain these data. The other is simulated data gathered by Agent-Based In-Store Simulator (ABISS), which modeled the same supermarket and customers with purchase decision and pedestrian behaviors. The objectives of ABISS is to investigate customer walking flows and purchasing behaviors in a supermarket. So far, such investigations have cost very much to examine in real situations. The simulator enables us to carry out “virtual experiments” through changing various parameters of retail businesses and store operations. Intensive comparisons with these real and virtual data have suggested the improvement of customer agents’ rules in ABISS.
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