engleski

Bayesian and Neural Networks for Customer Satisfaction Optimization

The economic environment in the last years has dramatically modified, and the way of interaction with customers has changed also, because in the actual conditions customer stability is no longer guaranteed. Measuring perceptions of customers can be a major problem for decision makers. Much of the problem is to determine which attributes carry most weight in the customer satisfaction. This study explores potential importance of visitor types and elements of festivals` offer as factors of influencing overall customer satisfaction based on main and interaction effects. Paper suggests application of intelligent system consisting of Bayesian networks and neural networks used to determine the attributes that influence overall satisfaction. Data used in the analysis was collected by questionnaire which was distributed to visitors of Spancirfest, festival in the Varazdin, medieval city in northwest of Croatia. Proposed techniques are shown to be superior to statistical techniques which were previously used in these purposes. Such findings of this study suggest usage of artificial intelligent techniques for gaining a full understanding of the determinants of festival participants’ satisfaction.

Intelligent system; Data mining; Artificial intelligence; Bayesian network; Neural network; Customer satisfaction.

nije evidentirano