Document Type : Original Article
Authors
1
Department of Business Management, Sar.C., Islamic Azad University, Sari, Iran.
2
Department of Business Management, Nar.C., Islamic Azad University, Naragh, Iran.
3
Department of Business Management, NT.C., Islamic Azad University, Tehran, Iran.
4
Department of Business Administration, To.C., Islamic Azad University, Tonekabon, Iran.
10.22034/oajre.2026.582043.1218
Abstract
Chabahar Free Zone, endowed with unique natural capacities and a strategic geographical position, possesses substantial potential to emerge as a national and international tourism hub. However, realizing this objective necessitates the precise identification and systematic ranking of key marketing factors that effectively influence travelers' decision-making processes. The primary aim of this research was to test the tourism marketing model of Chabahar and to rank the marketing factors affecting tourist attraction. In terms of purpose, the present study is applied in nature, while adopting a quantitative methodological approach. A survey strategy was employed for the quantitative component, and the research design was descriptive-survey with respect to data collection procedures. The statistical population comprised all investors in the tourism sector, from which a sample of 242 participants was selected through simple random sampling based on Cochran's formula. Data analysis was conducted using structural equation modeling, and model validation was performed utilizing SmartPLS4 software. The findings revealed that consequences, with a mean rank of 2.63, occupied the highest priority. Intervening factors, with a mean rank of 2.55, ranked second. The central phenomenon, with a mean rank of 2.43, ranked third. Contextual factors, with a mean rank of 2.40, ranked fourth. Strategies, with a mean rank of 2.39, ranked fifth. Finally, causal conditions, with a mean rank of 2.38, occupied the lowest priority. Furthermore, model validation indicated that the Goodness-of-Fit index yielded a value of 0.546, representing a robust indicator that confirms the overall high quality and adequate fit of the proposed model.
Keywords