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Título: | Towards semi-automatic human performance evaluation: The case study of a contact center |
Fecha de publicación: | 27-jun-2018 |
Editorial: | IOS Press |
Cita bibliográfica: | Intelligent Data Analysis, vol. 22, no. 4, pp. 867-880, 2018 |
ISSN: | ISSN 1088-467X ISSN 1571-4128 |
Materias relacionadas: | CDU::6 - Ciencias aplicadas::68 - Industrias, oficios y comercio de artículos acabados. Tecnología cibernética y automática |
Palabras clave: | Feature Selection Quality evaluation Contact Center |
Resumen: | Evaluating in a correct, fair, systematic and reliable way the quality of the work is a central problem in modern business. Both from the psychological and the social point of view, this problem is very far away from being solved, let alone from being managed by a (semi-) automatic decision support system. In this paper we consider the case study of evaluating the operators’ work quality in a medium-sized contact center, and, in particular, the problem of selecting the correct variables to be used in such an evaluation. Starting from a data set representative of the company’s range and size of activities, that allowed no usable predictive model for evaluating the skills of the agents, we were able to devise a reproducible methodology, along with an a posteriori optimization process, to select the essential variables that should be used to objectively evaluate the quality of the agents’ work. These results may be used in a support system helping the supervisors in evaluating the agents’ performances. Moreover, we believe that our methodology may be extrapolated and reused in other comparable contexts characterized by the measurability of the human operators’ performance. |
Autor/es principal/es: | Brunello, Andrea Jiménez, Fernando Marzano, Enrico Palma, José Sánchez, Gracia Sciavicco, Guido |
Facultad/Departamentos/Servicios: | Facultades, Departamentos, Servicios y Escuelas::Departamentos de la UMU::Ingeniería de la Información y las Comunicaciones Department of Mathematics, Physics, and Computer Science, University of Udine, Udine, Italy R&D Department, Gap Srlu, Trieste, Italy Department of Mathematics and Computer Science, University of Ferrara, Ferrara, Italy |
Versión del editor: | https://content.iospress.com/articles/intelligent-data-analysis/ida173586 |
URI: | http://hdl.handle.net/10201/123905 |
DOI: | https://www.doi.org/10.3233/IDA-173586 |
Tipo de documento: | info:eu-repo/semantics/article |
Número páginas / Extensión: | 14 |
Derechos: | info:eu-repo/semantics/openAccess Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
Descripción: | ©<2018>. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This document is the, Accepted version of a Published Work that appeared in final form in [Intelligent Data Analysis]. To access the final edited and published work see[https://www.doi.org/10.3233/IDA-173586] |
Aparece en las colecciones: | Artículos: Ingeniería de la Información y las Comunicaciones |
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