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Author Valle, M.A.; Ruz, G.A.; Masias, V.H. pdf  doi
  Title Using self-organizing maps to model turnover of sales agents in a call center Type
  Year 2017 Publication Applied Soft Computing Abbreviated Journal Appl. Soft. Comput.  
  Volume (down) 60 Issue Pages 763-774  
  Keywords Self organizing map; Fused network; Classifier; Employee turnover; Call center; Personality traits  
  Abstract This paper proposes an approach for modeling employee turnover in a call center using the versatility of supervised self-organizing maps. Two main distinct problems exist for the modeling employee turnover: first, to predict the employee turnover at a given point in the sales agent's trial period, and second to analyze the turnover behavior under different performance scenarios by using psychometric information about the sales agents. Identifying subjects susceptible to not performing well early on, or identifying personality traits in an individual that does not fit with the work style is essential to the call center industry, particularly when this industry suffers from high employee turnover rates. Self-organizing maps can model non-linear relations between different attributes and ultimately find conditions between an individual's performance and personality attributes that make him more predisposed to not remain long in an organization. Unlike other models that only consider performance attributes, this work successfully uses psychometric information that describes a sales agent's personality, which enables a better performance in predicting turnover and analyzing potential personality profiles that can identify agents with better prospects of a successful career in a call center. The application of our model is illustrated and real data are analyzed from an outbound call center. (C) 2017 Elsevier B.V. All rights reserved.  
  Address [Valle, Mauricio A.] Univ Finis Terrae, Fac Econ & Negocios, Santiago, Chile, Email: mvalle@uft.cL  
  Corporate Author Thesis  
  Publisher Elsevier Science Bv Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1568-4946 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000414072200057 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 795  
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