Mapping conditional scenarios for knowledge structuring in (tail) dependence elicitation

References

• Ackermann, F., & Eden, C. (2006). Using causal mapping: Individual and group; traditional and new. In M. Pidd (Ed.), Systems modelling: Theory and practice (pp. 127–145). Chichester: Wiley.
   Google Scholar
• Ackermann, F., Eden, C., Williams, T., & Howick, S. (2007). Systemic risk assessment: A case study. Journal of the Operational Research Society, 58(1), 39–51. doi:10.1057/palgrave.jors.2602105
   Web of Science ®Google Scholar
• Ackermann, F., Howick, S., Quigley, J., Walls, L., & Houghton, T. (2014). Systemic risk elicitation: Using causal maps to engage stakeholders and build a comprehensive view of risks. European Journal of Operational Research, 238(1), 290–299. doi:10.1016/j.ejor.2014.03.035
   Web of Science ®Google Scholar
• Ale, B. J. M., Bellamy, L. J., Cooke, R. M., Goossens, L. H. J., Hale, A. R., Roelen, A. L. C., & Smith, E. (2006). Towards a causal model for air transport safety-an ongoing research project. Safety Science, 44(8), 657–673. doi:10.1016/j.ssci.2006.02.002
   Web of Science ®Google Scholar
• Altbach, P. G., & Knight, J. (2007). The internationalization of higher education: Motivations and realities. Journal of Studies in International Education, 11(3–4), 290–305. doi:10.1177/1028315307303542
   Google Scholar
• Anderson, J. L. (1993). Horizon mission methodology – A tool for the study of technology innovation and new paradigms (NASA Working Paper AIAA Paper 93-1134). Washington: NASA.
   Google Scholar
• Bechlivanidis, C., & Lagnado, D. A. (2013). Does the why tell us the when? Psychological Science, 24(8), 1563–1572. doi:10.1177/0956797613476046
   PubMed Web of Science ®Google Scholar
• Bedford, T., & Cooke, R. M. (2001). Probabilistic risk analysis: Foundations and methods. Cambridge: Cambridge University Press.
   Google Scholar
• Bishop, P., Hines, A., & Collins, T. (2007). The current state of scenario development: An overview of techniques. Foresight, 9(1), 5–25. doi:10.1108/14636680710727516
   Google Scholar
• Bradfield, R., Wright, G., Burt, G., Cairns, G., & Van Der Heijden, K. (2005). The origins and evolution of scenario techniques in long range business planning. Futures, 37(8), 795–812. doi:10.1016/j.futures.2005.01.003
   Web of Science ®Google Scholar
• Bunn, D. W., & Salo, A. A. (1993). Forecasting with scenarios. European Journal of Operational Research, 68(3), 291–303. doi:10.1016/0377-2217(93)90186-Q
   Web of Science ®Google Scholar
• Checkland, P., & Poulter, J. (2010). Soft systems methodology. In M. Reynolds & S. Holwell (Eds.), Systems approaches to managing change: A practical guide (pp. 191–242). London: Springer.
   Google Scholar
• Chelst, K., & Bodily, S. E. (2000). Structured risk management: Filling a gap in decision analysis education. The Journal of the Operational Research Society, 51(12), 1420–1432. doi:10.2307/254039
   Web of Science ®Google Scholar
• Churchman, C. W. (1970). Operations research as a profession. Management Science, 17(2), B-37. doi:10.1287/mnsc.17.2.B37
   Web of Science ®Google Scholar
• Cooke, R. M. (1991). Experts in uncertainty: Opinion and subjective probability in science. New York: Oxford University Press.
   Google Scholar
• Cooke, R. M., & Goossens, L. J. H. (1999). Procedures guide for structured expert judgment (Project Report to the European Commission 18820).
   Google Scholar
• Cooke, R. M., & Goossens, L. H. J. (2004). Expert judgement elicitation for risk assessments of critical infrastructures. Journal of Risk Research, 7(6), 643–656. doi:10.1080/1366987042000192237
   Web of Science ®Google Scholar
• Crawley, F., & Tyler, B. (2015). HAZOP: Guide to best practice. Amsterdam: Elsevier.
   Google Scholar
• Crook, J., & Moreira, F. (2011). Checking for asymmetric default dependence in a credit card portfolio: A copula approach. Journal of Empirical Finance, 18(4), 728–742. doi:10.1016/j.jempfin.2011.05.005
   Web of Science ®Google Scholar
• Cunha, A. A. R., & Morais, D. C. (2016). Analysing the use of cognitive maps in an experiment on a group decision process. Journal of the Operational Research Society, 67(12), 1459–1468. doi:10.1057/jors.2016.19
   Web of Science ®Google Scholar
• Dawes, R. M. (1988). Rational choice in an uncertain world: The psychology of judgement and decision making. Thousand Oaks: SAGE Publications.
   Google Scholar
• De Witte, K., & López-Torres, L. (2017). Efficiency in education: A review of literature and a way forward. Journal of the Operational Research Society, 68(4), 339–363. doi:10.1057/jors.2015.92
   Web of Science ®Google Scholar
• Dias, L., Morton, A., & Quigley, J. (2018). Elicitation: The science and art of structuring judgement. Springer international series in operations research and management science (Vol. 261). Cham: Springer.
   Google Scholar
• Ducot, G., & Lubben, G. J. (1980). A typology for scenarios. Futures, 12(1), 51–57. doi:10.1016/S0016-3287(80)80007-3
   Web of Science ®Google Scholar
• Eden, C., & Ackermann, F. (1999). The role of GDSS in scenario development and strategy making. In String Processing and Information Retrieval Symposium and International Workshop on Groupware (pp. 234–242). IEEE.
   Google Scholar
• EFSA. (2014). Guidance on expert knowledge elicitation in food and feed safety risk assessment. EFSA Journal, 12(6), 3734.
   Google Scholar
• Einhorn, H. J., & Hogarth, R. M. (1986). Judging probable cause. Psychological Bulletin, 99(1), 3–19. doi:10.1037/0033-2909.99.1.3
   Web of Science ®Google Scholar
• Ericson, C. A. (2015). Hazard analysis techniques for system safety. Hoboken: Wiley.
   Google Scholar
• Franco, L. A. (2006). Forms of conversation and problem structuring methods: A conceptual development. Journal of the Operational Research Society, 57(7), 813–821. doi:10.1057/palgrave.jors.2602169
   Web of Science ®Google Scholar
• French, S. (1995). Uncertainty and imprecision: Modelling and analysis. Journal of the Operational Research Society, 46(1), 70–79. doi:10.1057/jors.1995.8
   Web of Science ®Google Scholar
• French, S. (2015). Cynefin: Uncertainty, small worlds and scenarios. Journal of the Operational Research Society, 66(10), 1635–1645. doi:10.1057/jors.2015.21
   Web of Science ®Google Scholar
• French, S., & Rios Insua, D. (2000). Statistical decision theory. New York: Wiley.
   Google Scholar
• Haimes, Y. Y. (2006). On the definition of vulnerabilities in measuring risks to infrastructures. Risk Analysis, 26(2), 293–296. doi:10.1111/j.1539-6924.2006.00755.x
   PubMed Web of Science ®Google Scholar
• Haimes, Y. Y. (2009). On the complex definition of risk: A systems-based approach. Risk Analysis, 29(12), 1647–1654. doi:10.1111/j.1539-6924.2009.01310.x
   PubMed Web of Science ®Google Scholar
• Hanea, A. M., Burgman, M., & Hemming, V. (2018). Idea for uncertainty quantification. In L. C. Dias, A. Morton, & J. Quigley (Eds.), Elicitation: The science and art of structuring judgement. Springer international series in operations research and management science (Vol. 261, Chapter 5, pp. 95–117). Cham: Springer.
   Google Scholar
• Hanea, A. M., McBride, M. F., Burgman, M. A., Wintle, B. C., Fidler, F., Flander, L., … Mascaro, S. (2017). Investigate Discuss Estimate Aggregate for structured expert judgement. International Journal of Forecasting, 33(1), 267–279. doi:10.1016/j.ijforecast.2016.02.008
   Web of Science ®Google Scholar
• Hastie, R., & Dawes, R. M. (2001). Rational choice in an uncertain world: The psychology of judgement and decision making. Thousand Oaks: SAGE Publications.
   Google Scholar
• HEFCE. (2001). Risk management: A guide to good practice for higher education institutions (Technical report). UK: Higher Education Funding Council for England.
   Google Scholar
• HEFCE. (2005). Risk management in higher education: A guide to good practice (Technical report). UK: Higher Education Funding Council for England.
   Google Scholar
• Howard, R. A. (1989). Knowledge maps. Management Science, 35(8), 903–922. doi:10.1287/mnsc.35.8.903
   Web of Science ®Google Scholar
• Howard, R. A., & Matheson, J. E. (2005). Influence diagrams. Decision Analysis, 2(3), 127–143. doi:10.1287/deca.1050.0020
   Google Scholar
• Joe, H. (2014). Dependence modeling with copulas. New York: CRC.
   Google Scholar
• Johnes, J. (2015). Operational research in education. European Journal of Operational Research, 243(3), 683–696. doi:10.1016/j.ejor.2014.10.043
   Web of Science ®Google Scholar
• Kahn, H., & Wiener, A. J. (1967). The year 2000: A framework for speculation on the next thirty three years. New York: MacMillan.
   Google Scholar
• Kahneman, D., & Frederick, S. (2002). Representativeness revisited: Attribute substitution in intuitive judgment. In T. Gilovich, D. Griffin, & D. Kahneman (Eds.), Heuristics and Biases: The Psychology of Intuitive Judgment, p. 49–81. Cambridge University Press.
   Google Scholar
• Kaplan, S. (1997). The words of risk analysis. Risk Analysis, 17(4), 407–417. doi:10.1111/j.1539-6924.1997.tb00881.x
   Web of Science ®Google Scholar
• Kaplan, S., & Garrick, B. J. (1981). On the quantitative definition of risk. Risk Analysis, 1(1), 11–27. doi:10.1111/j.1539-6924.1981.tb01350.x
   Google Scholar
• Ladyman, J., Lambert, J., & Wiesner, K. (2013). What is a complex system? European Journal for Philosophy of Science, 3(1), 33–67. doi:10.1007/s13194-012-0056-8
   Web of Science ®Google Scholar
• Lane, D. C. (2000). Diagramming conventions in system dynamics. Journal of the Operational Research Society, 51(2), 241–245. doi:10.1057/palgrave.jors.2600864
   Web of Science ®Google Scholar
• Lowe, D., Martingale, L., & Yearworth, M. (2016). Guiding interventions in a multi-organisational context: Combining the viable system model and hierarchical process modelling for use as a problem structuring method. Journal of the Operational Research Society, 67(12), 1481–1495. doi:10.1057/jors.2016.6
   Web of Science ®Google Scholar
• MacKenzie, D., & Spears, T. (2014). The formula that killed wall street: The Gaussian copula and modelling practices in investment banking. Social Studies of Science, 44(3), 393–417. doi:10.1177/0306312713517157
   PubMed Web of Science ®Google Scholar
• Mayston, D. J. (2003). Measuring and managing educational performance. Journal of the Operational Research Society, 54(7), 679–691. doi:10.1057/palgrave.jors.2601576
   Web of Science ®Google Scholar
• McNeil, A. J., Frey, R., & Embrechts, P. (2015). Quantitative risk management: Concepts, techniques and tools. New Jersey: Princeton University Press.
   Google Scholar
• Midgley, G. (1992). The sacred and profane in critical systems thinking. Systems Practice, 5(1), 5–16. doi:10.1007/BF01060044
   Web of Science ®Google Scholar
• Mingers, J., & Rosenhead, J. (2004). Problem structuring methods in action. European Journal of Operational Research, 152(3), 530–554. doi:10.1016/S0377-2217(03)00056-0
   Web of Science ®Google Scholar
• Montibeller, G., & Belton, V. (2006). Causal maps and the evaluation of decision options—A review. Journal of the Operational Research Society, 57(7), 779–791. doi:10.1057/palgrave.jors.2602214
   Web of Science ®Google Scholar
• Morecroft, J. (2010). System dynamics. In M. Reynolds & S. Holwell (Eds.), Systems approaches to managing change: A practical guide (pp. 25–85). London: Springer.
   Google Scholar
• O’Hagan, A., Buck, C. E., Daneshkhah, A., Eiser, J. R., Garthwaite, P. H., Jenkinson, D. J., … Rakow, T. (2006). Uncertain judgements: Eliciting experts’ probabilities. Chichester: Wiley.
   Google Scholar
• Paté-Cornell, E. (2012). On ‘black swans’ and ‘perfect storms’: Risk analysis and management when statistics are not enough. Risk Analysis, 32(11), 1823–1833. doi:10.1111/j.1539-6924.2011.01787.x
   PubMed Web of Science ®Google Scholar
• Pearl, J. (1988). Probabilistic reasoning in intelligent systems: Networks of plausible inference. San Francisco: Morgan Kaufmann.
   Google Scholar
• Phillips, L. D. (1984). A theory of requisite decision models. Acta Psychologica, 56(1–3), 29–48. doi:10.1016/0001-6918(84)90005-2
   Web of Science ®Google Scholar
• Poplawska, J., Labib, A., & Reed, D. M. (2017). From vicious to virtuous circles: Problem structuring for quantified decision making in operationalization of corporate social responsibility. Journal of the Operational Research Society, 68(3), 291–307. doi:10.1057/s41274-016-0028-z
   Web of Science ®Google Scholar
• Quigley, J., Colson, A., Aspinall, W., & Cooke, R. M. (2018). Elicitation in the classical model. In L. C. Dias, A. Morton, & J. Quigley (Eds.), Elicitation: The science and art of structuring judgement. Springer international series in operations research and management science (Vol. 261, chapter 2, pp. 15–36). Cham: Springer.
   Google Scholar
• Raiffa, H. (2002). Decision analysis: A personal account of how it got started and evolved. Operations Research, 50(1), 179–185. doi:10.1287/opre.50.1.179.17797
   Web of Science ®Google Scholar
• Renn, O., Burns, W. J., Kasperson, J. X., Kasperson, R. E., & Slovic, P. (1992). The social amplification of risk: Theoretical foundations and empirical applications. Journal of Social Issues, 48(4), 137–160. doi:10.1111/j.1540-4560.1992.tb01949.x
   Web of Science ®Google Scholar
• Rosenhead, J. (2006). Past, present and future of problem structuring methods. Journal of the Operational Research Society, 57(7), 759–765. doi:10.1057/palgrave.jors.2602206
   Web of Science ®Google Scholar
• Rowe, G., & Wright, G. (2001). Expert opinions in forecasting: The role of the Delphi technique. In J. S. Armstrong (Ed.), Principles of forecasting (pp. 125–144). London: Springer.
   Google Scholar
• Salmon, F. (2009). The formula that killed wall street. Significance, 3, 16–20. doi:10.1111/j.1740-9713.2012.00538.x
   Google Scholar
• Savage, L. J. (1954). The foundations of statistics. New York: Wiley.
   Google Scholar
• Shachter, R. D. (1988). Probabilistic inference and in uence diagrams. Operations Research, 36(4), 589–604. doi:10.1287/opre.36.4.589
   Web of Science ®Google Scholar
• Sloman, S., Barbey, A. K., & Hotaling, J. M. (2009). A causal model theory of the meaning of cause, enable, and prevent. Cognitive Science, 33(1), 21–50. doi:10.1111/j.1551-6709.2008.01002.x
   PubMed Web of Science ®Google Scholar
• Stamatis, D. H. (2003). Failure mode and effect analysis: FMEA from theory to execution. Milwaukee: ASQ Quality Press.
   Google Scholar
• Stewart, T. J., French, S., & Rios, J. (2013). Integrating multicriteria decision analysis and scenario planning—Review and extension. Omega, 41(4), 679–688. doi:10.1016/j.omega.2012.09.003
   Web of Science ®Google Scholar
• Tosoni, E., Salo, A., Govaerts, J., & Zio, E. (2019). Comprehensiveness of scenarios in the safety assessment of nuclear waste repositories. Reliability Engineering & System Safety, 188, 561–573. doi:10.1016/j.ress.2019.04.012
   Web of Science ®Google Scholar
• Tosoni, E., Salo, A., & Zio, E. (2018). Scenario analysis for the safety assessment of nuclear waste repositories: A critical review. Risk Analysis, 38(4), 755–776. doi:10.1111/risa.12889
   PubMed Web of Science ®Google Scholar
• Ulrich, W. (2003). Beyond methodology choice: Critical systems thinking as critically systemic discourse. Journal of the Operational Research Society, 54(4), 325–342. doi:10.1057/palgrave.jors.2601518
   Web of Science ®Google Scholar
• Van der Heijden, K. (2011). Scenarios: The art of strategic conversation. Chichester: Wiley.
   Google Scholar
• Vesely, W. E., Goldberg, F. F., Roberts, N. H., & Haasl, D. F. (1981). Fault tree handbook (NUREG-0492). Washington, DC: Nuclear Regulatory Commission.
   Google Scholar
• Werner, C. (2017). Report and R-tool manual: Conditional scenario mapping and dependence elicitation in higher education risk assessment (Technical report). UK: University of Strathclyde.
   Google Scholar
• Werner, C., Bedford, T., Cooke, R. M., Hanea, A. M., & Morales-Nápoles, O. (2017). Expert judgement for dependence in probabilistic modelling: A systematic literature review and future research directions. European Journal of Operational Research, 258(3), 801–819. doi:10.1016/j.ejor.2016.10.018
   Web of Science ®Google Scholar
• Werner, C., Bedford, T., & Quigley, J. (2018). Sequential refined partitioning for probabilistic dependence assessment. Risk Analysis, 38(12), 2683–2702. doi:10.1111/risa.13162
   PubMed Web of Science ®Google Scholar
• Werner, C., Hanea, A. M., & Morales-Náapoles, O. (2018). Eliciting multivariate uncertainty from experts: Considerations and approaches along the expert judgement process. In L. C. Dias, A. Morton, & J. Quigley (Eds.), Elicitation: The science and art of structuring judgement. Springer international series in operations research and management science (Vol. 261, chapter 8, pp. 171–210). Cham: Springer.
   Google Scholar
• White, D. (1995). Application of systems thinking to risk management: A review of the literature. Management Decision, 33(10), 35–45. doi:10.1108/EUM0000000003918
   Google Scholar
• Williams, T., Ackermann, F., Eden, C., & Howick, S. (1997). Project risk: Systemicity, cause mapping and a scenario approach. In K. A. Artto, & K. Kahkonen (Eds.), Managing risks in projects (pp. 343–352). New York: Taylor & Francis.
   Google Scholar
• Wilson, P. F. (1993). Root cause analysis: A tool for total quality management. Milwaukee: ASQ Quality Press.
   Google Scholar
• Wintle, B. C., Fidler, F., Vesk, P. A., & Moore, J. (2013). Improving visual estimation through active feedback. Methods in Ecology and Evolution, 4(1), 53–62. doi:10.1111/j.2041-210x.2012.00254.x
   Web of Science ®Google Scholar
• Wright, G., & Goodwin, P. (2009). Decision making and planning under low levels of predictability: Enhancing the scenario method. International Journal of Forecasting, 25(4), 813–825. doi:10.1016/j.ijforecast.2009.05.019
   Web of Science ®Google Scholar
• Yaniv, I., & Choshen-Hillel, S. (2012). Exploiting the wisdom of others to make better decisions: Suspending judgment reduces egocentrism and increases accuracy. Journal of Behavioral Decision Making, 25(5), 427–434. doi:10.1002/bdm.740
   Web of Science ®Google Scholar