Quarterly Publication

Document Type : Original Article

Authors

1 Associate Professor, Department of Business Management, Faculty of Management, Central Tehran Branch of Islamic Azad University, Tehran, Iran.

2 Ph.D. Candidate, Department of Business Management, Faculty of Management, Central Tehran Branch of Islamic Azad University, Tehran, Iran.

3 Professor, Department of Business Management, Faculty of Management, Central Tehran Branch of Islamic Azad University, Tehran, Iran.

Abstract

This study aims to design and explain the online advertising model with an image-based marketing approach. In this regard, while reviewing the concepts of online advertising, image-based marketing (GIF marketing), and tourism using confirmatory factor analysis and structural equation modeling, we designed and explained the online advertising model with the GIF marketing approach in Iran’s oil and gas industrial tourism hubs. The research strategy includes a combined qualitative study of the content analysis, grounded theory, and Delphi analysis, and a quantitative study in the survey. The study population in the qualitative part includes experts in advertising focusing on the tourism industry, and in the quantitative part, all tourists are in Iran’s oil and gas industrial tourism hubs. Regular test and confirmatory factor analysis and structural equation modeling tests confirmed the components and model. The results showed that the components (causal factors, contexts, and outputs) of an online advertising model with GIF marketing approach in oil and gas industrial tourism hubs are in order of priority: 1- message acceptance, 2- international tourism growth, 3- motivation for acceptance, 4- Information technology, 5- advertising website design, 6- GIF attractiveness, 7- online shopping intention, 8- competitive environment, 9- attitude and perception, 10- GIF content and value, and 11- social networks. In order to conduct open interviews and coding, we finally extracted 62 indicators. The results of model validation and model overall fit index (GOF), which has a value of 0.794, showed that the overall fit of the model is desirable, and as a result, the overall model is valid and approved. Further, in the Q2 index, positive numbers showed more than 0.35, which showed the high predictive power of the model.

Keywords

Main Subjects

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