@inproceedings{5e7fd66224ac47e2b7d0ba2541d808b3,
title = "Customer defection prediction in online bookstores",
abstract = "Since the cost of retaining an existing customer is lower than that of developing a new one, exploring potential customer defection becomes an important issue in the fiercely competitive environment of electronic commerce. Accordingly, this study used artificial neural networks (ANNs) to predict customers' repurchase intentions and thus avoid defection based on a set of criteria of quality attributes satisfaction and three beliefs in theory of planned behavior (TPB). The predicted repurchase intentions found by utilizing ANNs was compared with traditional analytic tools such as multiple discriminant analysis (MDA). Finally, via T-test analysis indicated that predicted accuracy of ANNs is better in both training and testing phases.",
keywords = "Artificial neural network (ANNs), Electronic commerce, Online shopping, Repurchase intention, Theory of planned behavior (TPB)",
author = "Shih, {Ya Yueh} and Kwoting Fang and Duen-Ren Liu",
year = "2003",
month = apr,
language = "English",
series = "ICEIS 2003 - Proceedings of the 5th International Conference on Enterprise Information Systems",
publisher = "Escola Superior de Tecnologia do Instituto Politecnico de Setubal",
pages = "352--358",
editor = "Slimane Hammoudi and Joaquim Filipe and Olivier Camp and Mario Piattini",
booktitle = "ICEIS 2003 - Proceedings of the 5th International Conference on Enterprise Information Systems",
note = "5th International Conference on Enterprise Information Systems, ICEIS 2003 ; Conference date: 23-04-2003 Through 26-04-2003",
}