This paper was presented and seen as two parts: a broad and intriguing first part followed by a highly specific sub-model. The group was not concerned to make spontaneous suggestions as to the treatment of the open ended topics in the first part but devoted its attention to the 'Linear Programming Model of Profit'.
Our fundamental aim was to develop a new and more refined technique of image research which would be so simple to apply that the test persons to be questioned would not have to undergo too much strain, yet the results obtained from the interviews should lead directly to new avenues of approach and hence towards more effective marketing and product policies. Our test series finally and after long and thorough experimenting produced a new brand image test method, the so-called MRK Test. This new test method relies on the mathematical concept of multiple regression and correlation. The abbreviation name of the test "MRK" consists of the first letters of "multiple regressions and correlations". What the multiple regression approach is basically trying to achieve is this: we are seeking to find out to which degree we are able to predict the actual buying behaviour from variables that are within our reach, and then seek to determine which weight these variables have in the ultimate buying decision of consumers.
In this paper I want to outline two applications of a mathematical model for consumer purchasing data. Apart from their own direct interest, these applications may serve to illustrate how a mathematical model can he useful for two somewhat different purposes, namely: A. To provide insight into a situation previously not understood - in this case the effect of particular patterns of purchasing on sampling errors; B. To allow the prediction of certain quantities instead of having to observe them directly - here the prediction of the market penetration in a longer period of time than has actually been observed. The model which will be used involves the so-called Negative Binomial distribution. Earlier work on the fit of this distribution to consumer purchasing data has already been described, but it may be helpful to summarize it briefly here before outlining the more recent developments.
With very few exceptions, empirical social research methods are being used primarily for purposes of predicting future events or behaviour. Sociological and economic analyses, even where on their face they appear to be nothing but fact finding or studies in methodology, generally intend to establish links between past and future developments. Obviously it cannot be the purpose of this paper to cover a general area, of this scope.This paper deals with the much narrower, question to what extend survey methods can be helpful in predicting future economic behaviour, in particulars how survey methods can be applied in forecasting future, sales volumes.
With very few exceptions, empirical social research methods are being used primarily for purposes of predicting future events or behaviour. Sociological and economic analyses, even where on their face they appear to be nothing but fact finding or studies in methodology, generally intend to establish links between past and future developments. Obviously it cannot be the purpose of this paper to cover a general area, of this scope.This paper deals with the much narrower, question to what extend survey methods can be helpful in predicting future economic behaviour, in particulars how survey methods can be applied in forecasting future, sales volumes.
With very few exceptions, empirical social research methods are being used primarily for purposes of predicting future events or behaviour. Sociological and economic analyses, even where on their face they appear to be nothing but fact finding or studies in methodology, generally intend to establish links between past and future developments. Obviously it cannot be the purpose of this paper to cover a general area, of this scope.This paper deals with the much narrower, question to what extend survey methods can be helpful in predicting future economic behaviour, in particulars how survey methods can be applied in forecasting future, sales volumes.
This paper describes a technique for the matching of population samples. The matching is achieved through prediction and the method turns-upon the combining of empirically developed predictors to give the best available predictive (or matching) composite. The development of this composite is through the principle used in-simple biological classification, which is to be sharply distinguished from the principle inherent in multiple correlation. The mathematical bases of the method are very simple and appear to be superior to the usual maximising formulas. Empirical matching is to be contrasted with matching by custom or hunch.
This paper describes a technique for the matching of population samples. The matching is achieved through prediction and the method turns-upon the combining of empirically developed predictors to give the best available predictive (or matching) composite. The development of this composite is through the principle used in-simple biological classification, which is to be sharply distinguished from the principle inherent in multiple correlation. The mathematical bases of the method are very simple and appear to be superior to the usual maximising formulas. Empirical matching is to be contrasted with matching by custom or hunch.
What is usually named motivation research is the application of the methods of psychology and sociology to commercial problems and is therefore nothing hut a certain type of research in the field of distribution. Its special aim is to understand and to explain the behaviour of the retailer in order to foresee and to influence eventually his future reactions. Another type of research aims essentially to register and to describe directly measurable facts that does not permit to explain those facts and therefore does not foresee the evolution.