Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Smart Mobs: The Next Social Revolution
Smart Mobs: The Next Social Revolution
Forecasting Sales Using Neural Networks
Proceedings of the International Conference on Computational Intelligence, Theory and Applications
Why people buy things they don't need: understanding and predicting consumer behavior
Why people buy things they don't need: understanding and predicting consumer behavior
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This work proposes Swarm-Moves -- a supermarket optimization simulation model based on swarm intelligence to identify parameters and their values that can influence customers to buy more on impulse in real-time. The model simulates the process of customers' shopping behavior in real-time, and pass products' information and promotions to the customers in exchange of their distinctive shopping pattern. The simulation can be tailored to incorporate any given model of customers' behavior in a particular supermarket, settings, events or promotions. The results, although preliminary, shows that impulse shopping can be increased by 29% using customers' feedback in real-time by informing other customers about common shopping pattern. The work advocates the use of RFID technology for marketing products in supermarkets, and provide several dimensions to look for influencing customers via feedback, real-time marketing, target advertisement and on-demand promotions.