Presenting an interactive marketing model based on causal, contextual and intervening variables in the steel industry
The purpose of this research is Presenting an interactive marketing model based on causal, contextual and intervening variables in the steel industry based on the foundational data theory method. In this research, based on interview tools from experts and senior managers of the steel industry, many factors related to content-based marketing, and research variables have been identified and structures related to each variable have been presented using open, central and selective coding methods. In the next step, based on the analysis of the data obtained from the questionnaire, by confirmatory factor analysis method with PLS technique, the factor load and combined reliability for the research variables were calculated above 0.4 and 0.7, respectively, and as a result, the validity of each construct related to the factors And the implications of the research model were confirmed. Then, by the method of structural equations and estimation of the final model, causal factors, contextual factors, and intervening factors have been confirmed in the first to fourth positions of influence on content-based interactive marketing in the final model of the research. Finally, while presenting the research model with optimal overall goodness of fit, paying attention to the effects and consequences of the model including: internal and corporate consequences, competitive advantage, brand experience management, customer and market consequences are suggested.
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Tourism Industry in the Era of the Fourth Industrial Revolution: Personalized Marketing and the Role of Artificial Intelligence
Seyed Yasser Mousavian, *, Farzad Asayesh, Dariyoush Jamshidi
Digital Transformation and Administration Innovation, Winter 2025 -
Presentation of interactive marketing model with approach on customer knowledge management in steel industry
Hossein Vahidi Iry Sofla, Mahmoud Ahmadi Sharif *, Mohammad Nasrolahnia, Peyman Ghafari Ashtiani
Journal of Industrial Management Studies, Autumn 2024