This paper deals with the problem why the contribution to knowledge gained through researches not sufficiently transferred into practical results. Given a contribution it will only be possible to apply it generally to practical problems if it is actually "staged" .Staging here does not only mean to produce and to present but requires the active spectator as the recipient .With "active"the demand for the learning ability of the practitioners is meant: successful practical application of modern research requires knowledge of its methodological foundation. With the aid of a case study the development and implementation of a marketing model for advertising media research possible trouble spots are examined which could lead in a typical way to a failure of the presentation.
This paper deals with the problem why the contribution to knowledge gained through researches not sufficiently transferred into practical results. Given a contribution it will only be possible to apply it generally to practical problems if it is actually "staged". Staging here does not only mean to produce and to present but requires the active spectator as the recipient. With "active" the demand for the learning ability of the practitioners is meant: successful practical application of modern research requires knowledge of its methodological foundation. With the aid of a case study the development and implementation of a marketing model for advertising media research possible trouble spots are examined which could lead in a typical way to a failure of the presentation.
In this report a new multivariant model is presented. In the first section a use-oriented systematic is developed. Within this systematic the multivariant technique, at present in vogue in practical research, is arranged. The new technique: Partial Typology, is identified as lying within the field of Cluster Analysis models. The systematic approach of the method identifies the differences in principle between this technique and other multivariant techniques. In contrast to other techniques two interdependent fields of variables are used to build the clusters. In the second section of the report the method of Partial Typology is presented in detail by using a case study from the field of regional research. The relationship between population mobility and community structure is investigated over six periods. The results of the investigation show the particular advantages and knowledge to be obtained from using Partial Typology. In section three the procedural realization and suitable criteria for optimization are described.
In this report a new multivariant model is presented. In the first section a use-oriented systematic is developed. Within this systematic the multivariant technique, at present in vogue in practical research, is arranged. The new technique: Partial Typology, is identified as lying within the field of Cluster Analysis models. The systematic approach of the method identifies the differences in principle between this technique and other multivariant techniques. In contrast to other techniques two interdependent fields of variables are used to build the clusters. In the second section of the report the method of Partial Typology is presented in detail by using a case study from the field of regional research. The relationship between population mobility and community structure is investigated over six periods. The results of the investigation show the particular advantages and knowledge to be obtained from using Partial Typology. In section three the procedural realization and suitable criteria for optimization are described.
The method being introduced here was developed by Infratest, Munich. The first section is devoted to the requisites of applications with which marketing models have to comply if they are to meet the requirements of the user. The second and third sections deal with the development of the model approach. The model is strictly speaking a dynamic and open one. Both environmental influences and the competitive conditions are simultaneously taken into account. The market is essentially described by three moduli of elasticity. Whereas the alpha values describe the competitive conditions, the beta values measure the success of the marketing strategy. Finally, the factor of inertia describes the sensitivity of the market to marketing within a lapse of time. The fourth section is devoted to a case study taken from the consumer market. In addition to a brief interpretation of the results, forecasts and possibilities for simulation are presented with the aid of the model. The reliability of the model parameter was tested here. Moreover, the findings were not computed for all of the eight periods investigated, but only for a shorter period of time. The marketing criterion of the periods not included was then "forecast" on the basis of the Model 369 parameter. The values forecast could now be compared with the values actually measured. When the Model 369 runs, including six periods, and the two periods were forecast, the result was throughout one of a high degree of reliability. On the basis of the forecasted values, it was also possible to compute various simulations for different marketing strategies and to examine their effects on the marketing success of all products.
The method being introduced here was developed by Infratest, Munich. The first section is devoted to the requisites of applications with which marketing models have to comply if they are to meet the requirements of the user. The second and third sections deal with the development of the model approach. The model is strictly speaking a dynamic and open one. Both environmental influences and the competitive conditions are simultaneously taken into account. The market is essentially described by three moduli of elasticity. Whereas the alpha values describe the competitive conditions, the beta values measure the success of the marketing strategy. Finally, the factor of inertia describes the sensitivity of the market to marketing within a lapse of time. The fourth section is devoted to a case study taken from the consumer market. In addition to a brief interpretation of the results, forecasts and possibilities for simulation are presented with the aid of the model. The reliability of the model parameter was tested here. Moreover, the findings were not computed for all of the eight periods investigated, but only for a shorter period of time. The marketing criterion of the periods not included was then "forecast" on the basis of the Model 369 parameter. The values forecast could now be compared with the values actually measured. When the Model 369 runs, including six periods, and the two periods were forecast, the result was throughout one of a high degree of reliability. On the basis of the forecasted values, it was also possible to compute various simulations for different marketing strategies and to examine their effects on the marketing success of all products.