Modeling Viral Marketing to Strengthen the Online Purchasing Channel: A Mixed Approach with the SWARA Technique Based on Genetic Algorithms

Document Type : Research Paper

Author

Department of Managementand accounting, To.c., Islamic Azad University, Tonekabon, Iran

Abstract

The aim of the present research is to model and prioritize components to provide optimal viral marketing rules in online businesses. It is a mixed-methods applied research study. In the qualitative section of this research, 15 individuals were selected through purposeful sampling by the researcher to ensure their relevance and expertise regarding the research topic, and the quantitative part includes 460 customers of online businesses using a stratified random sampling method. The data collection tools in the qualitative section used the projection technique and in-depth interviews. Using the MAXQDA software, the interviews were analyzed and summarized, through which six components were identified. Then, in the quantitative section, 12 experts determined the Lavash index, and subsequently, exploratory factor analysis was conducted using the SPSS software. Using the SWARA technique, the identified indicators were ranked based on expert opinions according to their degree of importance, and to identify the most influential component, the genetic metaheuristic algorithm was used, with WEKA and RAPIDMINER software employed in this section. Finally, utilizing the decision tree method and MATLAB software, viral marketing optimization rules were identified. The findings in the qualitative section showed that online persuasion, online trust, online support, online services, and online attractiveness were the components of viral marketing, and in the quantitative section, online persuasion and online trust were determined as the best feature or component.

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Main Subjects

References

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Interdisciplinary Journal of Management Studies
Volume 19, Issue 3
July 2026
Pages 527-543

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