Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/185051 
Year of Publication: 
2016
Citation: 
[Journal:] Decision Analytics [ISSN:] 2193-8636 [Volume:] 3 [Issue:] 1 [Publisher:] Springer [Place:] Heidelberg [Year:] 2016 [Pages:] 1-24
Publisher: 
Springer, Heidelberg
Abstract: 
We formalise and present an innovative general approach for developing complex system models from survey data by applying Bayesian Networks. The challenges and approaches to converting survey data into usable probability forms are explained and a general approach for integrating expert knowledge (judgements) into Bayesian complex system models is presented. The structural complexities of the Bayesian complex system modelling process, based on various decision contexts, are also explained along with a solution. A novel application of Bayesian complex system models as a management tool for decision making is demonstrated using a railway transport case study. Customer satisfaction, which is a Key Performance Indicator in public transport management, is modelled using data from customer surveys conducted by Queensland Rail, Australia.
Subjects: 
Decision making
Bayesian modelling
Management tools
Customer satisfaction
Transportation
Persistent Identifier of the first edition: 
Creative Commons License: 
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Document Type: 
Article
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