Tourism is primarily a human activity that travels from origin to a destination for entertainment or business,Today, the development of Tourism in the Tourism industry is of great importance and has overshadowed various social and economic aspects. With the outbreak of the Corona virus in 2019, the world Tourism industry has been facing an unprecedented recession for more than two years. The development of virtual Tourism is one of the most important tools for success in e-commerce in the Corona era. The purpose of this study is to design a model for the development of virtual Tourism in the Iranian Tourism industry. The number of samples in this study was 8, which was done using 2 non-probability targeted methods (judgmental) and snowball method. This basis is the explanation of the virtual Tourism development model in the Iranian Tourism industry. In this regard, using the data theorizing of the foundation, the final model including 11 categories and 31 concepts has been obtained.

This study aimed to validate a structural model of smart Tourism by examining the impact of multiple technological, behavioral, and managerial constructs on the development of smart Tourism in Kish Island, Iran. The research employed a quantitative design using a descriptive-correlational strategy and structural equation modeling (SEM) to evaluate the proposed model. A two-stage sampling method was applied: first, cluster sampling was used to randomly select 30 hotels from 51 active establishments in Kish Island,second, simple random sampling was used to select tourists from these hotels. Out of 311 distributed questionnaires, 273 were deemed valid and analyzed. A 45-item smart Tourism scale developed by the researchers was used for data collection, with its content validity confirmed by experts (CVI = 0. 82). Cronbach’s alpha, composite reliability (CR), average variance extracted (AVE), and discriminant validity tests were conducted to ensure measurement reliability and validity. Data were analyzed using SPSS-24 and SmartPLS-3. All eight independent variables—perceived value, economic development, smart technology, tourist behavior, complementary activities, destination capability, information management, and smartification—had statistically significant effects on smart Tourism. Smart technology (β = 0. 269, p < 0. 001) and economic development (β = 0. 199, p < 0. 001) showed the strongest influences. model fit indices, including AVE (>0. 50), CR (>0. 70), and goodness-of-fit (GOF = 0. 725), confirmed the model’s validity and predictive power. Discriminant validity was also established using the Fornell-Larcker criterion. The validated smart Tourism model demonstrates that technological infrastructure, managerial readiness, and tourist-centered strategies are essential for developing smart Tourism destinations. These findings offer both theoretical insight and practical guidance for enhancing Tourism innovation, competitiveness, and sustainability in similar regional contexts.