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Intensidad exportadora e interacción entre fortalezas del marketing mix: Un análisis basado en redes neuronales artificiales

Authors

GUTIÉRREZ VILLAR, MARÍA BELÉN, MONTERO SIMÓ, MARÍA JOSÉ, ARAQUE PADILLA, RAFAEL, CASTRO GONZÁLEZ, PILAR

External publication

No

Means

Rev. Metodos Cuantitativos Econ. Empresa

Scope

Article

Nature

Científica

JCR Quartile

SJR Quartile

SJR Impact

0.137

Publication date

01/01/2014

Scopus Id

2-s2.0-84920983382

Abstract

Among the determining factors in export activity, many studies have high-lighted the relevance of the marketing mix. Generally, the majority of them use a variables analysis to focus on specific strategies, in particular, standardized-adaptations. This paper analyzes if there is an interactive effect of strength generated in different variables of the marketing mix that can be associated with different export profiles. The Extreme Learning Machine (ELM) algorithm has been used within the Multilayer Perceptron (MLP) of Artificial Neural Networks (ANN). In addition, the analyses combine a novel approach for sensitivity analysis developed ad hoc for this paper to determine the individual and interactive effects of predictable variables on the dependent variable in classification problems of a dichotomous nature. The results obtained allow us to confirm the existence of the postulated interactive effects, simultaneously revealing the usefulness of ANN and of the sensitivity analysis proposed for research in the area of marketing and, specifically, in firms' internationalization studies.

Keywords

Artificial neural networks; Extreme learning machine; Internationalization; Marketing mix; Sensitivity analysis