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Author (up) Ruz, G.A.; Varas, S.; Villena, M. pdf  doi
  Title Policy making for broadband adoption and usage in Chile through machine learning Type
  Year 2013 Publication Expert Systems With Applications Abbreviated Journal Expert Syst. Appl.  
  Volume 40 Issue 17 Pages 6728-6734  
  Keywords Broadband penetration; Policy making; Clustering analysis; Bayesian networks  
  Abstract For developing countries, such as Chile, we study the influential factors for adoption and usage of broadband services. In particular, subsidies on the broadband price are analyzed to see if this initiative has a significant effect in the broadband penetration. To carry out this study, machine learning techniques are used to identify different household profiles using the data obtained from a survey on access, use, and users of broadband Internet from Chile. Different policies are proposed for each group found, which were then evaluated empirically through Bayesian networks. Results show that an unconditional subsidy for the Internet price does not seem to be very appropriate for everyone since it is only significant for some households groups. The evaluation using Bayesian networks showed that other polices should be considered as well such as the incorporation of computers, Internet applications development, and digital literacy training. (C) 2013 Elsevier Ltd. All rights reserved.  
  Address [Ruz, Gonzalo A.; Varas, Samuel; Villena, Marcelo] Univ Adolfo Ibanez, Fac Ingn & Ciencias, Santiago, Chile, Email:  
  Corporate Author Thesis  
  Publisher Pergamon-Elsevier Science Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0957-4174 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000326214700006 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 326  
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