Leveraging Artificial Intelligence (AI) in Competitive Intelligence (CI) Research

Joseph F. Hair; Misty  Sabol

doi:10.24883/eagleSustainable.v15i.469

Autores

Joseph F. Hair University of South Alabama, Alabama https://orcid.org/0000-0002-9226-9693
Misty Sabol Mitchell College of Business, United States https://orcid.org/0000-0002-0259-918X

DOI:

https://doi.org/10.24883/eagleSustainable.v15i.469

Palavras-chave:

Artificial Intelligence (AI), Large Language Models (LLMs), Scholarly Research, Competitive Intelligence (CI), GPT Models

Resumo

Objective: The rapid advancement of artificial intelligence (AI) has significantly influenced research and academic practices, prompting universities to create guidelines for student use of large language models (LLMs). However, there is ongoing debate among academic journals and conferences regarding the necessity of reporting AI assistance in manuscript development. This paper aims to explore diverse perspectives on the use of LLMs in scholarly research, particularly within the context of competitive intelligence (CI), and to offer guidelines for CI researchers on how to effectively leverage AI tools like GPT models.

Method: The study conducts a comprehensive review of existing literature on the integration of AI in academic research, focusing specifically on the capabilities of generative AI models such as ChatGPT-4, Scholar GPT, and Consensus GPT. These models, developed by OpenAI, are evaluated for their utility in various stages of the research process, including literature review, qualitative analysis, and data analysis. The analysis emphasizes how the quality of AI-generated outputs depends on the specificity of the user's input.

Results: While LLMs have demonstrated significant potential in enhancing literature reviews, qualitative research, and data analysis, the study finds that their full capabilities in academic research remain underexplored. The research highlights both the concerns about potential "contamination" of scholarly work through AI use and the benefits these models offer, especially when used strategically.

Conclusions: The article presents a structured guide for business researchers, with particular emphasis on those engaged in competitive intelligence, to integrate AI language models effectively throughout the research process. The findings underline the importance of input specificity and provide practical recommendations for leveraging LLMs to enhance research efficiency and output quality.

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Biografia do Autor

Joseph F. Hair, University of South Alabama, Alabama

Dr. Joseph F. Hair is an American author, consultant, and professor. He currently serves as a Distinguished Professor of Marketing, holds the Cleverdon Chair of Business, and is the Director of the PhD program at the Mitchell College of Business, University of South Alabama. Previously, he held the positions of Senior Scholar for the DBA program at the Michael J. Coles College of Business at Kennesaw State University, and the Copeland Endowed Chair of Entrepreneurship at the Ourso College of Business Administration, Louisiana State University.

Dr. Hair has authored over 100 editions of his books, including Multivariate Data Analysis (8th edition, 2019), which has been cited over 201,000 times, Essentials of Business Research Methods (5th edition, 2023), A Primer on Partial Least Squares Structural Equation Modeling – PLS (3rd edition, 2022), Essentials of Marketing Research (6th edition, 2024), and MKTG (14th edition, 2024). He is renowned for his contributions to marketing research and multivariate data analysis.

From 2018 to 2024, Clarivate Analytics recognized Dr. Hair as part of the top 1% of all Business and Economics professors worldwide for his impactful research and contributions to the field.

Misty Sabol, Mitchell College of Business, United States

Dr. Misty Sabol is an experienced instructor specializing in Marketing, Supply Chain Management, and Analytics. Her research focuses on diverse areas such as statistics and methodologies, innovation, creativity, and ecosystems. Dr. Sabol holds a Doctor of Business Administration from the University of Dallas, a Master’s in Management from the University of Alabama, and a Bachelor’s in Business Administration from the University of New Orleans.

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