Analytics-driven complaint prioritisation via deep learning and multicriteria decision-making
| dc.coverage | DOI: 10.1016/j.ejor.2023.08.027 | |
| dc.creator | Vairetti, Carla | |
| dc.creator | Aránguiz, Ignacio | |
| dc.creator | Maldonado, Sebastián | |
| dc.creator | Karmy, Juan Pablo | |
| dc.creator | Leal, Alonso | |
| dc.date | 2024 | |
| dc.date.accessioned | 2026-01-05T21:14:06Z | |
| dc.date.available | 2026-01-05T21:14:06Z | |
| dc.description | <p>Complaint analysis is an essential business analytics application because complaints have a strong influence on customer satisfaction (CSAT). However, the process of categorising and prioritising complaints manually can be extremely time consuming for large companies. In this paper, we propose a framework for automatic complaint labelling and prioritisation using text analytics and operational research techniques. The labelling step of the training set is performed using a simple weighting approach from the multiple-criteria decision-making (MCDM) literature, while transformer-based deep learning (DL) techniques are used for text classification. We define two priority classes, namely, urgent complaints and other claims, and develop a system for automatic complaint categorisation. Our experimental results show that excellent predictive performance can be achieved with state-of-the-art text classification models. In particular, BETO, a bidirectional encoder representations from transformers (BERT) model trained on a large Spanish corpus, reaches an accuracy (ACCU) and area under the curve (AUC) of 92.1% and 0.9785, respectively. This positive result translates into a successful complaint prioritisation scheme, which improves CSAT and reduces the churn rate.</p> | eng |
| dc.identifier | https://investigadores.uandes.cl/en/publications/315c204f-29a3-456a-9078-bfbf0a71dc5d | |
| dc.identifier.uri | https://repositorio.uandes.cl/handle/uandes/65952 | |
| dc.language | eng | |
| dc.rights | info:eu-repo/semantics/restrictedAccess | |
| dc.source | vol.312 (2024) date: 2024-02-01 nr.3 p.1108-1118 | |
| dc.subject | Analytics | |
| dc.subject | BERT | |
| dc.subject | Complaint management | |
| dc.subject | Deep learning | |
| dc.subject | Text analytics | |
| dc.title | Analytics-driven complaint prioritisation via deep learning and multicriteria decision-making | eng |
| dc.type | Article | eng |
| dc.type | Artículo | spa |