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

Artikel

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.

Object Details

• Language: Spanisch

References and Relationships

• Bibliographic citation: Journal: Revista de Métodos Cuantitativos para la Economía y la Empresa ; ISSN: 1886-516X ; Volume: 18 ; Year: 2014 ; Pages: 88-111 ; Sevilla: Universidad Pablo de Olavide

Classification and Topics

• Classification: Wirtschaft ; Marketing
• Subject: internationalization ; marketing mix ; Artificial Neural Networks ; Extreme Learning Machine ; sensitivity analysis

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Gutiérrez-Villar, Belén ; Montero-Simó, María José ; Araque-Padilla, Rafael Ángel ; Castro-González, Pilar
• Event: Veröffentlichung
• (who): Universidad Pablo de Olavide
• (where): Sevilla
• (when): 2014

Further information

• Handle: http://hdl.handle.net/10419/113878
• Last update: 10.03.2025, 11:45 AM CET