Multinomial Logistic Regression model to measure the customer preferences respect to the pharmaceutical sector: case Ambato, Ecuador - Edison R. Valencia; Álvaro J. Bonifaz (GarVal Editorial Ltda., 2018)
Context: The investigation includes the Ecuadorian pharmaceutical market from the business competitive point of view, focusing on the service offered by the Farmacias Cruz Azul and Farmacias Económicas franchises. Aims: To determine the main variables that influence the consumer's choice, in the pharmaceutical sector, and generate a predictive model of competitive analysis. Methods: Through the Multinomial Logistic Regression Model was obtained the significant variables that helped to predict the customer's pharmacy choice. The study was conducted in the zone number 3, center of the country, whose sample was calculated based on the infinite population formula. A total of 393 clients were surveyed in the main public and private health centers. Results: After establishing the dependent variable "Choice of Pharmacy"; Of the eight variables under study, the relevant independent variables were: Reason for choice, Fidelity and Low prices with a level of significance of 0.003, 0.001 and 0.000, respectively. Final variables and introduced to the regression model; which resulted, a probability of 16.82% that customers go to Farmacias Cruz Azul, 77.12% to choose Farmacias Económicas, and only 0.63% to go to another pharmacy, including independent. Conclusions: The Multinomial Logistic Regression Model was useful to predict the probability of choice of pharmacy, which a client has according to variables that represent service; allowing also to perform key simulations for the continuous improvement of the sector, planning and competitive analysis.