Advisor 1 a Descriptive Model of Advertising Budgeting for Industrial Products

Cover Advisor 1 a Descriptive Model of Advertising Budgeting for Industrial Products
Advisor 1 a Descriptive Model of Advertising Budgeting for Industrial Products
Gary L Lilien
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125, etc. This form of model was tried, both as in (1) and in a multiplicative form with consis- tently poor results as follows: -28- (1) The models did not fit well, particularly at the extremes.
(2) The effects of several variables were in the, wrong logical direction.
(3) Small changes in the model form (adding or deleting variables) changed the coefficients significantly.
The reasons for the poor fit seemed to be the following: (1) The data have wide ranges and some distributions are highly
... skewed.
(2) More than one budgeting process may be represented in the sample.
(3) Actual budgeting processes may use much less well-defined data.
Resolving the issues implied in (1) and (2) is a difficult job. To- gether they imply that a variety of submodels should be developed for vari- ous ranges of the Independent variables. But in what ranges? And how many submodels?
An insight relative to point (3) may go a long way toward satisfying points (1) and (2), During unstructured Interviews with ad managers, the reasons for budgeting high for advertising were such statements as " large number of customers, " " early in life cycle"; much unused plant capacity...


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