Generative Artificial Intelligence in Applied Business Contexts: A Systematic Review, Lexical Analysis, and Research Framework
DOI:
https://doi.org/10.33423/jabe.v26i2.7040Keywords:
business, economics, generative artificial intelligence, systematic review, lexical analysis, applied business researchAbstract
Generative Artificial Intelligence (GenAI) is transforming business practices with potential applications in customer service, code generation, risk analysis, and HR functions. GenAI may simultaneously create or exacerbate ethical, legal, and security concerns in the business context despite its promise. Thus, researchers should be interested in its role and impact, especially in the applied business context. This multi-method systematic review examines GenAI literature in applied business research, revealing dominant themes like ChatGPT and language models but noting a scarcity of business-based studies. Analysis of GenAI research features in applied business studies identifies a limited focus on theoretical frameworks, data collection methods, and data analysis processes. We suggest frameworks for future research to assess GenAI’s impact on system and information quality, user satisfaction, and organizational outcomes based on our findings. This review provides a vital foundation for understanding and advancing GenAI in applied business research contexts.
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