scholarly journals Applying Object-Oriented Bayesian Networks for Smart Diagnosis and Health Monitoring at both Component and Factory Level

2017 ◽  
pp. 132-141 ◽  
Author(s):  
Anders L. Madsen ◽  
Nicolaj Søndberg-Jeppesen ◽  
Mohamed S. Sayed ◽  
Michael Peschl ◽  
Niels Lohse
Keyword(s):  
Bayesian Networks ◽  
Health Monitoring ◽  
Object Oriented

Systems Health Monitoring: Integrating FMEA into Bayesian Networks

2021 ◽  
Author(s):  
Chetan S. Kulkarni ◽  
Matteo Corbetta ◽  
Elinirina I. Robinson
Keyword(s):  
Bayesian Networks ◽  
Health Monitoring

Object-oriented Bayesian networks for complex quality management problems

2013 ◽  
Vol 49 (1) ◽  
pp. 115-133 ◽  
Author(s):  
Flaminia Musella ◽  
Paola Vicard
Keyword(s):  
Quality Management ◽  
Bayesian Networks ◽  
Object Oriented ◽  
Management Problems

Reconciling internal and external satisfaction through probabilistic graphical models

2017 ◽  
Vol 9 (3/4) ◽  
pp. 347-370 ◽  
Author(s):  
Flaminia Musella ◽  
Roberta Guglielmetti Mugion ◽  
Hendry Raharjo ◽  
Laura Di Pietro
Keyword(s):  
Customer Satisfaction ◽  
Bayesian Networks ◽  
Graphical Models ◽  
Object Oriented ◽  
Holistic Approach ◽  
Probabilistic Graphical Models ◽  
Model Parameters ◽  
Holistic View ◽  
Content Type ◽  
External Customer

Purpose This paper aims to holistically reconcile internal and external customer satisfaction using probabilistic graphical models. The models are useful not only in the identification of the most sensitive factors for the creation of both internal and external customer satisfaction but also in the generation of improvement scenarios in a probabilistic way. Design/methodology/approach Standard Bayesian networks and object-oriented Bayesian networks are used to build probabilistic graphical models for internal and external customers. For each ward, the model is used to evaluate satisfaction drivers by category, and scenarios for the improvement of overall satisfaction variables are developed. A global model that is based on an object-oriented network is modularly built to provide a holistic view of internal and external satisfaction. The linkage is created by building a global index of internal and external satisfaction based on a linear combination. The model parameters are derived from survey data from an Italian hospital. Findings The results that were achieved with the Bayesian networks are consistent with the results of previous research, and they were obtained by using a partial least squares path modelling tool. The variable ‘Experience’ is the most relevant internal factor for the improvement of overall patient satisfaction. To improve overall employee satisfaction, the variable ‘Product/service results’ is the most important. Finally, for a given target of overall internal and external satisfaction, external satisfaction is more sensitive to improvement than internal satisfaction. Originality/value The novelty of the paper lies in the efforts to link internal and external satisfaction based on a probabilistic expert system that can generate improvement scenarios. From an academic viewpoint, this study moves the service profit chain theory (Heskett et al., 1994) forward by delivering operational guidelines for jointly managing the factors that affect internal and external customer satisfaction in service organizations using a holistic approach.

Sign in / Sign up

Export Citation Format

Share Document