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ABSTRACTIn recent years, decision making based on systematic analysis has been greatly emphasized. Yet, decision analysis is often carried out without analyzing the limitations of certain quantitative techniques. This paper presents the concept, solution method, and application potential of goal programming which eliminates many limitations of conventional linear optimization models.

Robert L. Winkler's paper [1] provides a comprehensive overview of challenging research areas for decision making under uncertainty. Hence, rather than try to extend the list of research areas identified, this note will attempt to embellish some that I feel are particularly important. In these areas, I feel the value of systematic research is particularly high.For convenience, the discussion will be organized under the four research categories identified by Winkler with a couple of sugestions following in an "implementation research" category. The reader will note, however, that many of the suggested topics actually relate to more than one research category.

1. Aim of Factor Analysis -- 2. The Method of Factor Analysis -- 2.1 Normalisation of the variables -- 2.2 Correlation and variance in factor analysis -- 2.3 The model of the factor analysis -- 2.4 Solution of the model -- 2.5 Interpretation of the final aspects -- 3. Application of Factor Analysis to Data from Developing Countries -- 3.1 The variables -- 3.2 Working out the factor analysis -- 3.3 Interpretation of the results according to areas -- 3.4 Interpretation of the results according to final aspects -- Summary -- Appendices.