Modeling Customer KM Using Neural Networks

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Massoud Moballegh, Nasser Safaei


The purpose of this study is to model customer knowledge using artificial neural network. In terms of purpose, this research is an application that has been keyed by using a sample of 60 out of 70 organizations based on information technology in Tehran. Inputs were used for the parameters of organizational structure and process, human resources, communication and interaction, knowledge, customer, management, technology and infrastructure of information technology and organizational strategy, 36 neurons in the middle layer and one neuron in the output layer for the parameter of customer knowledge. The output of the neural network showed that the customer's knowledge was very accurately predicted by the neural network. Predicted values ​​for customer knowledge had a mean square error of MSE = 0.015 compared to experimental values ​​and in the test phase, the degree of conformity of the results obtained from the model with their actual value had a high correlation (R = 0.90512). This indicates the fact that the model produced through artificial neural network has the ability to predict the effectiveness of customer knowledge management in the organization, based on how to implement the effective factors in customer knowledge management.

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