Abstract
This paper describes the design of an Intelligent Simulation Model of Online Consumer Behavior (ISMOCB) that incorporates a knowledge base using some form of the Artificial Intelligence methods such as Naïve Bayes Classifier and Artificial Neural Networks. This study investigates modeling online consumer behavior by using demographic characteristics such as age, gender, marital status, educational status, monthly income and number of people in the family. This will provide producing more synthetic data and creating an “Artificial Database” which includes the demographics of online consumers and their purchase transactions. The model is built for online shopping based on empirical data gathered in Turkey via an online survey. Two different inference systems are used for which product group is chosen by whom has which demographic characteristics. The quality of the data, gathered exclusively for this project, allows a fine validation of the simulation results.
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Çağil, G., Erdem, M.B. An intelligent simulation model of online consumer behavior. J Intell Manuf 23, 1015–1022 (2012). https://doi.org/10.1007/s10845-010-0439-7
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DOI: https://doi.org/10.1007/s10845-010-0439-7