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Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/17809| Title: | Forecasting SMEs’ credit risk in supply chain finance with an enhanced hybrid ensemble machine learning approach |
| Authors: | Zhu, Y Zhou, L Xie, C Wang, G-J Nguyen, TV |
| Keywords: | Supply chain finance;Small and medium-sized enterprises;Credit risk forecasting;Machine learning;RS-MultiBoosting;Partial dependency plot |
| Issue Date: | 2019 |
| Publisher: | Elsevier |
| Citation: | Zhu, Y., Zhou, L., Xie, C., Wang, G.-J. and Nguyen, T.V. (2019). Forecasting SMEs’ credit risk in supply chain finance with an enhanced hybrid ensemble machine learning approach. International Journal of Production Economics, 211, pp.22–33. doi: 10.1016/j.ijpe.2019.01.032 |
| URI: | http://bura.brunel.ac.uk/handle/2438/17809 |
| DOI: | http://dx.doi.org/10.1016/j.ijpe.2019.01.032 |
| ISSN: | 0925-5273 |
| Appears in Collections: | Brunel Business School Research Papers |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | Embargoed until 28 Jan 2020 | 1.49 MB | Adobe PDF | View/Open |
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