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.

Customer Satisfaction Prediction in the Shipping Industry with Hybrid Meta-heuristic Approaches

Bekiros S.
First
;
2019-01-01

Abstract

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.
2019
54
2
647
667
Data mining; Decision support systems; Multi-criteria decision analysis; Neural networks; Preference models; Rough sets; Shipping
Bekiros S.; Loukeris N.; Matsatsinis N.; Bezzina F.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1915072
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