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https://www.um.edu.mt/library/oar/handle/123456789/92572| Title: | Customer satisfaction prediction in the shipping industry with hybrid meta-heuristic approaches |
| Authors: | Bekiros, Stelios Loukeris, Nikolaos Matsatsinis, Nikolaos Bezzina, Frank |
| Keywords: | Consumer satisfaction Neural networks (Computer science) Decision support systems Decision making -- Data processing Data mining |
| Issue Date: | 2018 |
| Publisher: | Springer |
| Citation: | Bekiros, S., Loukeris, N., Matsatsinis, N., & Bezzina, F. (2018). Customer satisfaction prediction in the shipping industry with hybrid meta-heuristic approaches. Computational Economics, 54(2), 647-667. |
| 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. |
| URI: | https://www.um.edu.mt/library/oar/handle/123456789/92572 |
| Appears in Collections: | Scholarly Works - FacEMAMAn |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Customer satisfaction prediction in the shipping industry with hybrid meta-heuristic approaches.pdf Restricted Access | 525.95 kB | Adobe PDF | View/Open Request a copy |
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