Quantification of causal models that contain many so-called “soft” variables is often problematic because so few “hard” data are available to calibrate the model. This paper describes a case study in which different techniques were used to qualify a causal model that contained a number of such soft variables, such as “level of expected customer irritation”, or “effort required to reach branch office”. The case study itself concerned the development of a decision-support system to assess branch office viability of a medium-sized bank. The specifics techniques used for quantification are viability for a medium-sized bank. The specific techniques used for quantification are part of the standard “tool set” of the Participative Modelling (PBM) Method, the synergistic blend of system dynamics and group knowledge elicitation techniques developed by the author in a series of six case studies, of which was the fifth.

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Date created

• 1995

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• Document

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• Creative Commons BY-NC-ND Attribution-NonCommercial-NoDerivs 4.0 International

  
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12420ec6bd5f758d2b4dea59aabd75a9

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System Dynamic Society Records

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• This collection is part of the University Archives