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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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