Abstract: The aim of this research is to explain the role of artificiality in designing a winning model for commercial platforms for the purpose of development between Iran and Russia.
Research method: This research has examined the subject with a combination of (qualitative and quantitative). In the qualitative phase, data were collected through semi-structured interviews with 12 experts and upon reaching theoretical saturation. Qualitative data analysis was performed using theorizing and open, axial and selective coding methods. In this stage, causal, axial conditions, contexts and intervening factors, strategies and messages resulting from the implementation of the platform were identified and a paradigmatic research model was designed. The theoretical model resulting from the qualitative phase, the design of a quantitative questionnaire, the views of experts were measured and the relationships between changes were validated. The questionnaire consisted of 69 questions with Likert analysis, which assessed the level of use, including the opposition of the responses to the statements measuring the effectiveness of artificial intelligence on international relations of the model. The validity and reliability of the questionnaire were confirmed in preliminary studies. The statistical population of the research was active experts in the digital economy of Iran, who were purposefully sampled due to access to the complete list. In total, the questionnaire was distributed to 221 experts active in the digital economy. The sample size was calculated based on the Cohen method. The data obtained were analyzed using structural equation statistical analysis and PLS software. The reliability and validity of the research construct were assessed using variance value and Cronbach's alpha.
Research findings: The results of the qualitative phase showed that components such as understanding audience behavior, branding, modifying and updating business rules, pricing policy, protecting copyright, and developing user account infrastructures and new payments play the greatest role. A quantitative analysis examined the positive and negative relationship between investment in AI and increased platform competitiveness. On the other hand, weak legal regulations and privacy gaps were identified as significant challenges. The platform economy model based on AI can pave the way for attracting trust and investors in this ecosystem.
Conclusion:The results show that user experience management and behavioral analysis with the help of advanced AI algorithms not only reduce the challenges arising from rapid market changes and customer expectations, but also play an important role in policy formulation and regulatory reform. On the other hand, limitations such as the lack of independent and credible legal authority and shortcomings in privacy and copyright laws have created conditions that directly affect the development of commercial platforms and highlight the need for policymaking tailored to local realities. Innovations such as dynamic pricing based on machine learning and the use of data-based competitive and supportive strategies lead to increased user attraction, strengthened brand position, and sustainable economic growth. Overall, assessing and prioritizing key criteria, developing a strategic roadmap, and intelligently controlling obstacles provide a reliable platform for improving operational efficiency and developing a competitive platform economy between Iran and Russia.