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Object-oriented Bayesian networks for complex quality management problems

Listed author(s):
  • Flaminia Musella

    ()

  • Paola Vicard

    ()

Registered author(s):

    Quality management and customer satisfaction evaluation can be difficult tasks to perform when processes involve multiple production lines or provide multichannel services. As a consequence, the top management needs to analyse the problem from different perspectives, to evaluate possible improvement strategies at several levels and to take appropriate decisions. To this aim, we propose to use object-oriented Bayesian networks by which different quality aspects and evaluations can be integrated in a unique framework allowing to analyse improvement strategies in real time. We show, by an application to an internal-customer satisfaction survey, how to combine the perceived quality of different production areas and how to evaluate the impact on the global quality of improvement actions developed in one or more areas. Copyright Springer Science+Business Media Dordrecht 2015

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    File URL: http://hdl.handle.net/10.1007/s11135-013-9977-3
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    Article provided by Springer in its journal Quality & Quantity.

    Volume (Year): 49 (2015)
    Issue (Month): 1 (January)
    Pages: 115-133

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    Handle: RePEc:spr:qualqt:v:49:y:2015:i:1:p:115-133
    DOI: 10.1007/s11135-013-9977-3
    Contact details of provider: Web page: http://www.springer.com

    Order Information: Web: http://www.springer.com/economics/journal/11135

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    1. Julia Mortera & Paola Vicard & Cecilia Vergari, 2012. "Object-Oriented Bayesian Networks for a Decision Support System," Departmental Working Papers of Economics - University 'Roma Tre' 0144, Department of Economics - University Roma Tre.
    2. Silvia Salini & Ron Kenett, 2009. "Bayesian networks of customer satisfaction survey data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(11), pages 1177-1189.
    3. Claudia Tarantola & Paola Vicard & Ioannis Ntzoufras, 2012. "Monitoring and Improving Greek Banking Services Using Bayesian Networks: an Analysis of Mystery Shopping Data," Quaderni di Dipartimento 160, University of Pavia, Department of Economics and Quantitative Methods.
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