John Quigley
John Quigley
Department of Management Science, University of Strathclyde
Verified email at - Homepage
Cited by
Cited by
Project Complexity and Risk Management (ProCRiM): Towards modelling project complexity driven risk paths in construction projects
A Qazi, J Quigley, A Dickson, K Kirytopoulos
International journal of project management 34 (7), 1183-1198, 2016
Supply chain risk network management: A Bayesian belief network and expected utility based approach for managing supply chain risks
A Qazi, A Dickson, J Quigley, B Gaudenzi
International Journal of Production Economics 196, 24-42, 2018
Bayesian belief nets for managing expert judgement and modelling reliability
JH Sigurdsson, LA Walls, JL Quigley
Quality and reliability engineering international 17 (3), 181-190, 2001
Systemic risk elicitation: Using causal maps to engage stakeholders and build a comprehensive view of risks
F Ackermann, S Howick, J Quigley, L Walls, T Houghton
European Journal of Operational Research 238 (1), 290-299, 2014
Building prior distributions to support Bayesian reliability growth modelling using expert judgement
L Walls, J Quigley
Reliability Engineering & System Safety 74 (2), 117-128, 2001
Modelling the reliability of search and rescue operations with Bayesian Belief Networks
L Norrington, J Quigley, A Russell, R Van der Meer
Reliability Engineering & System Safety 93 (7), 940-949, 2008
Exploring dependency based probabilistic supply chain risk measures for prioritising interdependent risks and strategies
A Qazi, J Quigley, A Dickson, ŞÖ Ekici
European Journal of Operational Research 259 (1), 189-204, 2017
Expert elicitation for reliable system design
T Bedford, J Quigley, L Walls
Statistical Science, 428-450, 2006
LC Dias, A Morton, J Quigley
Springer International Publishing. MR3700912. doi: https://doi. org/10.1007 …, 2018
Risk analysis of damaged ships–a data-driven Bayesian approach
S Kelangath, PK Das, J Quigley, SE Hirdaris
Ships and Offshore Structures 7 (3), 333-347, 2012
Supplier quality improvement: The value of information under uncertainty
J Quigley, L Walls, G Demirel, BL MacCarthy, M Parsa
European journal of operational research 264 (3), 932-947, 2018
Estimating rate of occurrence of rare events with empirical bayes: A railway application
J Quigley, T Bedford, L Walls
Reliability Engineering & System Safety 92 (5), 619-627, 2007
Elicitation in the classical model
J Quigley, A Colson, W Aspinall, RM Cooke
Elicitation: The science and art of structuring judgement, 15-36, 2018
Trading reliability targets within a supply chain using Shapley's value
J Quigley, L Walls
Reliability Engineering & System Safety 92 (10), 1448-1457, 2007
Eliciting engineering knowledge about reliability during design‐lessons learnt from implementation
R Hodge, M Evans, J Marshall, J Quigley, L Walls
Quality and reliability engineering international 17 (3), 169-179, 2001
Mixing methodologies to enhance the implementation of healthcare operational research
R Sachdeva, T Williams, J Quigley
Journal of the Operational Research Society 58 (2), 159-167, 2007
Supply Chain Risk Management: Systematic literature review and a conceptual framework for capturing interdependencies between risks
A Qazi, J Quigley, A Dickson
2015 International Conference on Industrial Engineering and Operations …, 2015
Estimating the probability of rare events: addressing zero failure data
J Quigley, M Revie
Risk Analysis: An International Journal 31 (7), 1120-1132, 2011
Expert judgement combination using moment methods
B Wisse, T Bedford, J Quigley
Reliability Engineering & System Safety 93 (5), 675-686, 2008
Confidence intervals for reliability-growth models with small sample-sizes
J Quigley, L Walls
IEEE Transactions on Reliability 52 (2), 257-262, 2003
The system can't perform the operation now. Try again later.
Articles 1–20