  This paper analyzes pedestrians' behavioral patterns in the pedestrianized
shopping environment in the historical center of Barcelona, Spain. We employ a
Bluetooth detection technique to capture a large-scale dataset of pedestrians'
behavior over a one-month period, including during a key sales period. We
focused on comparing particular behaviors before, during, and after the
discount sales by analyzing this large-scale dataset, which is different but
complementary to the conventionally used small-scale samples. Our results
uncover pedestrians actively exploring a wider area of the district during a
discount period compared to weekdays, giving rise to strong underlying mobility
patterns.
