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

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 w...

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Bibliographic Details
Published in:Computational economics 2019-08, Vol.54 (2), p.647-667
Main Authors: Bekiros, Stelios, Loukeris, Nikolaos, Matsatsinis, Nikolaos, Bezzina, Frank
Format: Article
Language:English
Subjects:
Artificial intelligence
Behavioral/Experimental Economics
Classification
Computer Appl. in Social and Behavioral Sciences
Customer satisfaction
Economic Theory/Quantitative Economics/Mathematical Methods
Economics
Economics and Finance
Forecasting
Heuristic methods
Market shares
Math Applications in Computer Science
Multiple criterion
Neural networks
Operations Research/Decision Theory
Optimization
Shipping
Shipping industry
Strategic planning
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Summary: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.
ISSN:0927-7099
1572-9974
DOI:10.1007/s10614-018-9842-5