Publication Date


Document Type


First Advisor

Grokë, Paul O.||Nelson, J. H. (Professor of business)

Degree Name

M.S. (Master of Science)


Department of Marketing


Marketing||Sales||Linear programming||Selling


It has been the contention of many marketing people that one of the most important control devices used by marketing management is the equitable establishment of sales quotas or goals. Although this is an important function, many marketing managers have been setting these goals on an intuitive, subjective basis. This subjectivity has created many problems, in that the published goals may not accurately reflect market potentials or dynamics. The resultant quotas could not be objectively supported. This study has been undertaken to investigate the use of linear programming in reducing this subjectivity by econometrically establishing sales goals for the various regional areas of a marketer of industrial products. It was believed that the mathematical processes of linear programming would remove the subjectivity from this critical function. In order to accomplish this, the mathematical technique would have to select specific economic indicators from among a group of such indicators, weight them in relationship to their affect upon sales achievement, present these weightings in a form which could be incorporated into forecasting formulae which would forecast estimated dollar sales. These estimated sales, when compared with actual sales achievement, would result in a correlation coefficient in excess of .8000 for each regional area. In pursuit of these goals, the study first undertook the investigation of the various linear programming approaches available. From this group, the simplex method of linear programming was selected as having the greatest probability of meeting the analytical requirements of the study. Because the simplex method involves significant mathematical manipulation, it was determined that it would be desirable to use an electronic computer to do the actual data analysis. It then became necessary to either write a computer program or to find an existing program which used the simplex method. In this phase of the study, it was determined that many programs of this type are available both from the computer manufacturers or academic sources. A program was chosen to fit the equipment available and modified to use the programming language available. The data used in this analysis were the actual sales history of a cooperating marketing firm of industrial products and employment data for specific industry groups. The latter group of data was extracted from the County Business Patterns published on a continuing basis by the Department of Commerce and the Department of Health, Education, and Welfare of the United States Government. These data are measures of employment by industry group within county areas for the entire United States. They were compiled to cover an area which was coextensive with each of the regional areas for the marketing firm. These collected and compiled data were presented to the selected computer program. The program related the changes in employment levels by industry to the changes in total sales achievement for each region. The results of these analyses were inserted into forecasting formulae and extended. The results of these extensions met the requirements of this study, in that, three out of four of the regions established a correlation level in excess of .8000. The correlation values achieved were: .9972, .9047, .8289, and .7130. (This final value was for a region which had experienced significant changes in both economic and sales activity over the period of the study.) It has been the conclusion of this study that linear programming analysis is a usable tool for a marketing manager of industrial products in establishing sales goals for the regional divisions of his marketing activities. It has also been recommended that, because of the successful conclusion of this study, further investigation be made into the application of linear programming analysis to other industrial marketing activities which require resource allocation or mathematical evaluation of voluminous data.


Includes bibliographical references.||Includes illustrations.


vi, 120 pages




Northern Illinois University

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