By Philippe A. Naert, Peter S.H. Leeflang
The commentary that many versions are outfitted yet few are used has nearly develop into a average within the administration technology and operations examine literature. however, the assertion is still to a wide volume actual this present day, additionally and maybe even extra so the place advertising and marketing types are involved. This led Philippe Naert, now approximately 4 years in the past, to jot down an idea textual content of some hundred pages with reference to how one can construct imple males desk advertising versions, that's, types which may and should be used. one of many readers of that early manuscript used to be Peter Leefiang. He made feedback resulting in a extra constant ordering of the cloth and professional posed the addition of a few issues and the growth of others to make the ebook extra self-contained. This led to a co-authorship and a revised model, which used to be written via Peter Leefiang and consisted of a reshuffling and a diffusion of the unique fabric by means of approximately fifty in keeping with cent. numerous conferences among the co-authors produced additional refinements within the textual content and the series of chapters and sections, and then Philippe Naert back completely transformed the total textual content. This ended in a brand new enlargement, back by way of fifty in keeping with cent, of the second one new release. The 3rd generation additionally required the inclusion of loads of new literature indicating that the sphere is making speedy development and that implementation has develop into an important problem to advertising version builders.
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MARKETING DECISION MODELS 23 So we may conclude this section by repeating that the 'direction' of the solution can often be found by a non-quantitative analysis. A more quantitative treatment of the problem, however, can be instrumental in finding the 'approximate length' of the solution. We will, however, not always be able to find the optimal 'length' or solution and a quantitative treatment can only give information about 'the direction' Because in these cases the outcomes do not correspond with a priori ideas of decision makers about 'directions', quantitative treatments are still very valuable.
In other situations, as has been observed previously, a descriptive model may be all that one is looking for. In still other cases, one may stop at the predictive stage, although optimization is analytically or numerically possible. Examples are models developed by Little (l975a, 1975b) and Urban (1969a). There are several reasons for this. First of all, one wants to avoid a 'push-button' approach, where the computer tells the manager what he should do. Such an approach requires little thinking on the part of the manager, and pretty soon he would lose touch with how his market works, and he would not know how to handle discrepancies between predicted and actual results.
For example, one may describe a market by the structure of brand loyalty (the percentage of people buying product i in period t + 1, who bought the same brand on the last purchase occasion), and brand switching (percentage of people changing from brand i to brand J)' That is, the market is described by a stochastic brand choice model. 1. Under the heading of predictive models we mean models aiming at forecasting or predicting future events. In the context of decision models, this will generally mean the prediction of the effect of alternative actions.
Building Implementable Marketing Models by Philippe A. Naert, Peter S.H. Leeflang