Document Type : Research Paper

Author

Ph.D. International Marketing Management, Semnan University, Iran

Abstract

Benevolence and helping the poor have always been ingrained in the spirit of heroic sports. The present study aimed at analyzing the motivations of heroic sport activists to participate in benevolent marketing using a mixed approach. In the first step, 50 codes were extracted qualitatively (content analysis) as motivations to participate in benevolent marketing and categorized to 10 factors according to semantic similarities. Based on these factors, a questionnaire was designed. In the second step, quantitative approaches in data-mining (explanatory and predictive) were used to evaluate the statistical population. 393 heroic sport activists were classified into two separate clusters using the Davies–Bouldin index. Moreover, artificial neural networks were used to design a model which predicted the motivations of heroic sport activists for benevolence. Results showed that reciprocation, desire for entertainment and pleasure, and emotional importance in the first cluster, and religious teachings, need for helping others, and desire for social participation in the second cluster received the most cluster centers. The use of neural networks indicated that the independent variables had high predictive potentials and can predict the changes in the dependent variable with the accuracy of 0.958. Moreover, the results of the sensitivity analysis confirmed the importance of demographic, symbolic, and religious teaching variables in the participation of heroic sport activists in benevolence.

Keywords

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