1 Agent-Based Modelling Incorporating Qualitative and Quantitative ...

simulation results and statistical logs from the mall: we aim to assess the macro-behaviour of the
model in terms of that of the empirical system (see part five). Number (3) relies upon the
participation of the stakeholders in an iterative evaluation and redevelopment process. This
involves assessing both the assumptions upon which the model is based, and the micro-behaviour
of simulated agents, in terms of their plausibility, as out lined in (Moss, Downing et al. 2000).
We suggest that this model is well-validated in terms of the nature of the value chain and of the
issues facing the manufacturer, though less in terms of the behaviour, attitudes, and expectations of
customers and distributors. Of the different methods of validation, stakeholder evaluation should be
the most reliable because stakeholders are sensitive to results that ‘do not look right’, i.e. are not
like anything they have observed. However, potential problems with qualitative data are that
respondents may be misinformed in their assertions, or we may misinterpret their degree of
certainty in them. Quantitative data is more reliable but is limited to those concepts we can measure
easily, which is quite restrictive in this type of model. This is why qualitative methods are also
used: a model involving qualitative data requires qualitative methods of validation.
There were two methodological issues encountered during the course of the research which may be
considered unique to the approach taken. Firstly, significant collaboration was required between the
researcher and the stakeholders via frequent e-mail, telephone and face-to-face discussions,
presentations, etc. Consultation was important to develop the partnership, to ensure the stakeholders
fully understood the nature of the project, and were able to contribute to it and benefit from it. It
was necessary that stakeholders were aware of key modelling concepts in order that they could
understand the significance of the simulation experiments and, very importantly, contribute ideas of
their own to the research design. Secondly, qualitative data were used to inform a quantitative
model amenable to the techniques of numerical simulation. Descriptions provided by the fieldwork
respondents needed to be translated into a suitably formal and precise language. However, it was
important to preserve much of the semantic content in order that explanations for behaviour of the
model could be generated to which the stakeholders could relate and therefore more easily identify.
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