The Role of Artificial Intelligence Capabilities in Enhancing the Effect of B2B Marketing on Export Performance: A Study in the Petrochemical Industry
Keywords:
Artificial Intelligence Capabilities, Export Performance,Abstract
The present study aimed to investigate the role of artificial intelligence capabilities in strengthening the effect of B2B marketing on export performance in petrochemical companies and to explain the mechanisms through which these capabilities influence information management, marketing planning, and marketing execution. This study was applied in terms of purpose and descriptive-survey in terms of methodology, employing the structural equation modeling approach. The statistical population consisted of managers and experts in marketing, export sales, and planning departments of petrochemical companies operating in international markets. Convenience sampling was used, and the sample size was determined as 105 participants using G*Power software. Data were collected through a standardized questionnaire based on a five-point Likert scale. Construct validity was confirmed through Average Variance Extracted (AVE) and the Fornell–Larcker criterion, while reliability was assessed using Cronbach’s alpha and composite reliability. Data analysis was performed using SmartPLS software and the partial least squares approach. The findings indicated that artificial intelligence capabilities had a positive and significant effect on information management, marketing planning, and marketing execution. The strongest direct effect was observed on marketing execution, highlighting the critical role of intelligent technologies in improving the efficiency of industrial marketing activities. Furthermore, all three dimensions of B2B marketing had direct and positive effects on export performance, with information management emerging as the strongest predictor of export performance. Indirect effect analysis also demonstrated that artificial intelligence enhanced export performance through improving information management and marketing planning. The coefficient of determination for export performance was 0.731, indicating the strong explanatory power of the proposed model. The results demonstrated that artificial intelligence capabilities, as a strategic organizational resource, can enhance competitive advantage and export performance by strengthening key B2B marketing processes. The integration of intelligent technologies into data analysis, demand forecasting, marketing planning, and customer relationship management can improve the effectiveness of export decision-making and facilitate sustainable international market development for petrochemical companies.
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References
Agrawal, S., Gupta, R., & Singh, P. (2024). Operational Performance and AI Integration in Industrial Sectors. Journal of Business Research, 78(4), 210-230.
Alizadeh, H., M, K., Saberian, H., & Keramati, M. (2024). Qualitative Study to Propose Digital Marketing Based on Customer Experience: Considering Grounded Theory (GT). Business, Marketing, and Finance Open, 1(6), 86-98. https://doi.org/10.61838/bmfopen.1.6.8
Alizadeh, H., & Nazarpour Kashani, H. (2024). The Impact of Perceived Experience with ChatGPT on Online Consumers' Information Searching Behavior: An Empirical Study of Iranian College Students. Asia Pacific Journal of Marketing and Logistics. https://doi.org/10.1108/APJML-02-2024-0140
Bag, S., Pretorius, J. H. C., Gupta, S., & Dwivedi, Y. K. (2021). Role of Institutional Pressures and Resources in the Adoption of Big Data Analytics Powered Artificial Intelligence, Sustainable Manufacturing Practices and Circular Economy Capabilities. Technological Forecasting and Social Change, 163, 120420. https://doi.org/10.1016/j.techfore.2020.120420
Chen, Y., Zhang, L., & Kumar, S. (2023). The Impact of Artificial Intelligence on Marketing Strategies: Evidence from Multinational Companies. Journal of Marketing Research, 60(2), 123-145.
Ersoy, A. B. (2024). Artificial Intelligence Applications Used in Online Retail in China and Their Relationship to Customer Satisfaction and Loyalty. International Journal of Business and Applied Social Science, 8-17. https://doi.org/10.33642/ijbass.v10n3p2
Herhausen, D., Miocevic, D., Morgan, R. E., & Kleijnen, M. H. (2020). The Digital Marketing Capabilities Gap. Industrial Marketing Management, 90, 276-290.
McKinsey, & Company. (2025). AI in the Workplace: A Report for 2025.
Mehrani, H., Alizadeh, M., & Rasouli, A. (2022). Evaluation of the Role of Artificial Intelligence Tools in the Development of Financial Services and Marketing. Journal of Technology in Entrepreneurship and Strategic Management, 1(1), 71-82. https://www.journaltesm.com/index.php/journaltesm/article/view/278
Mikalef, P., Conboy, K., & Krogstie, J. (2021). Artificial Intelligence as an Enabler of B2B Marketing: A Dynamic Capabilities Micro-Foundations Approach. Industrial Marketing Management, 98, 80-92.
Mikalef, P., Lemmer, K., Schaefer, C., Ylinen, M., Fjortoft, S. O., Torvatn, H. Y., & Niehaves, B. (2023). Examining How AI Capabilities Can Foster Organizational Performance in Public Organizations. Government Information Quarterly, 40(2), 101797.
Paschen, J., Pitt, C., & Kietzmann, J. (2020). Artificial Intelligence: Building Blocks and an Innovation Typology. Business Horizons, 63(2), 147-155.
Peltier, J. W., Dahl, A. J., & Schibrowsky, J. A. (2024). Artificial Intelligence in Interactive Marketing: A Conceptual Framework and Research Agenda. Journal of Research in Interactive Marketing, 18(1), 54-90. https://doi.org/10.1108/JRIM-01-2023-0030
Phan, T. N., Nguyen, T. T., & Vu, M. T. (2023). From AI Capability to Enhanced Organizational Performance: The Path Through Organizational Creativity. Journal of Business Research, 158, 113-123. https://doi.org/10.1016/j.jbusres.2022.113123
Talha, M. (2025). Optimizing Digital Marketing Campaigns Using Artificial Intelligence (AI) and Social Media Analytics: A Comparative Study of Machine Learning Algorithms. International Journal of Scientific Research in Engineering and Management, 9(3), 1-9. https://doi.org/10.55041/ijsrem42691
Teng, H. Y., Li, M. W., & Chen, C. Y. (2025). Does Smart Technology, Artificial Intelligence, Robotics, and Algorithm (STARA) Awareness Have a Double-Edged-Sword Influence on Proactive Customer Service Performance? Effects of Work Engagement and Employee Resilience. Journal of Hospitality Marketing & Management, 1-24. https://doi.org/10.1080/19368623.2025.2449853
Torabi, M. A., Dehghan Anari, M., Jalalian, N., & Shahsavand, A. H. (2024). Neuromorphic Design in the Intelligent Organization: Reconstructing AI Decision-Making Processes Inspired by the Octopus Brain. Intelligent Marketing Management, 5(4), 11-23. https://en.civilica.com/doc/2098235/
Wu, Y. (2023). AI-Based Compliance Automation in Commercial Bank: How the Silicon Valley Bank Provided a Cautionary Tale for Future Integration. International Research in Economics and Finance, 7(1). https://doi.org/10.20849/iref.v7i1.1356
Yoo, J. W., Park, J., & Park, H. (2024). The Impact of AI-Enabled CRM Systems on Organizational Competitive Advantage: A Mixed-Method Approach Using BERTopic and PLS-SEM. Heliyon, 10(16). https://doi.org/10.1016/j.heliyon.2024.e36392
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Copyright (c) 2025 Hamid Alizadeh; Mobina Damavandi Nejad, Abbas Behradfar (Author)

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