Building AI-driven cross-cultural marketing programs to support international trade in the USA
Globalization has made it much easier for U.S. businesses to reach customers all over the world, but marketing to people from different cultures is still hard. New tools are available to help with these problems thanks to advances in Artificial Intelligence (AI). This study's goal is to create and test a framework for AI-powered cross-cultural marketing programs that help U.S. businesses trade with other countries. We outline a research agenda that looks into how AI technologies, like natural language processing and machine learning, can help us better understand and adapt to cultural markets. We used a mixed-method approach, which included surveys of marketing and trade professionals as well as looking at AI usage data and trade statistics. The main findings show that companies that combine AI with cultural intelligence get more customers and do better in exports. AI-based personalization helps break down language and cultural barriers. The results have real-world implications for marketers, who can use AI to make campaigns more culturally sensitive, and for policymakers, who can encourage the use of AI in export promotion. This research adds to what we know by bringing together the fields of AI, cross-cultural marketing, and international trade. It does this by suggesting a new conceptual model based on Hofstede's cultural dimensions, technology acceptance theory, and the resource-based view. The study finds that AI-driven marketing that is in line with local culture can greatly improve U.S. companies' ability to compete and do business around the world.
Authors
- Monique Mohammed
- Nana Abena Manu (ORCID: https://orcid.org/0000-0003-3957-7686)
- Judith Anita Afriyie
- Tomiwa Gabriel Majekodunmi
- Olasunbo Moradeun Osowo
Publication Details
- Journal
- World Journal of Advanced Engineering Technology and Sciences
- Published
- 2024-11-30
- DOI
- https://doi.org/10.30574/wjaets.2024.13.1.0465
- Primary Topic
- International Business and FDI
- Type
- article
- Field-Weighted Citation Impact
- 0.00