Οικονομετρικές μέθοδοι εφαρμοσμένες στο μάρκετινγκ η περίπτωση της παραγοντικής ανάλυσης
Econometric methods applied in marketing the case of factor analysis
KeywordsΟικονομετρία ; Οικονομετρική έρευνα ; Μάρκετινγκ ; Έρευνα αγοράς ; Πολυμεταβλητές στατιστικές μέθοδοι ; Παραγοντική ανάλυση ; Econometrics ; Econometric research ; Marketing ; Market research ; Factor analysis
Entrepreneurs and Marketing Researchers are daily challenged to make decisions which will lead to a smooth and successful business. Any decision in general, but especially in business, involves a risk, because of the inability to predict the precise reactions of the target market/audiences. Decisions consequently rely on the information that the Marketing Researchers have in hand, yet, this information is not unlimited and/or provide concrete answers, but it acts as their "eyes" in the market. Moreover, according to Peter Drucker “You cannot manage what you cannot control and you cannot control something you cannot measure”. Thus, the science of Marketing recruited Econometrics, and in particular Multivariate Statistical Methods to obtain additional information through researches which carried out in order to better understand the behavior and preferences of consumers. One of the multivariate statistical methods that is widely used in these researches is Factor analysis. In the herewith Thesis, is pointed out the interdependence between the design of the overall research process with statistical methods and especially that of Factor Analysis. Factor analysis was designed to examine the covariance of a set of variables and interpret the correlations between these variables by grouping them into factors. Specifically, it reduces the number of variables into smaller units, and thus facilitates the development of the basic concepts in an area of science, such as that of Marketing. However, the method is subjective to a considerable degree and the researcher must take into account certain conditions that must be followed for the selection of appropriate statistical criteria, as well as, pay attention to several issues that arise during its implementation.