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Customer satisfaction prediction in the shipping industry with hybrid meta-heuristic approaches

Bekiros, Stelios, Loukeris Nikolaos, Matsatsinis Nikolaos, Bezzina, Frank

Πλήρης Εγγραφή


URI: http://purl.tuc.gr/dl/dias/64C9C9B2-7B3D-4CCD-B96E-DF5A28348FAB
Έτος 2019
Τύπος Δημοσίευση σε Περιοδικό με Κριτές
Άδεια Χρήσης
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Βιβλιογραφική Αναφορά S. Bekiros, N. Loukeris, N. Matsatsinis and F. Bezzina, "Customer satisfaction prediction in the shipping industry with hybrid meta-heuristic approaches," Comput. Econ., vol. 54, no. 2, pp. 647-667, Aug. 2019. doi: 10.1007/s10614-018-9842-5 https://doi.org/10.1007/s10614-018-9842-5
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Περίληψη

Optimization and prediction of customer satisfaction in the shipping industry impacts immensely upon strategic planning and consequently on the targeted market share of a corporation. In shipping industry, accurate measures of customer satisfaction are usually very cumbersome to elaborate. In this work we aim to reveal the most effective optimization methods, employing artificial intelligence approaches such as rough sets, neural networks, advanced classification methods as well as multi-criteria analysis under a comparative framework vis-à-vis their forecasting performance.

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