Abstract
This research aims to assess the predictive capabilities between the Digital Marketing Model Innovation (DMMI), based on the Oslo Manual 4th ed., and the Consumer Decision-Making Style (CDMS) model. The methodology involved an artificial neural network based on SPSS software to analyze data collected from 400 young Mexican students (Generation Z) belonging to ten local Guadalajara city universities from January to June 2019. The above mentioned are essential for several organizations interested in recognizing how to collect and measure innovation data of DMMI related to different CDMS internet behavior to increase competitiveness. The results suggest improvements on each one of the strategic relationships at the DMMI-CDMS model. Such improvements involving a high prediction level based on Multilayer Perceptron (MLP) as a predictive neural network on different variables compared with a Binary Logistic Regression (BLR) to assess and explain the scope of such predictions of the DMMI-CDMS model.
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