Artificial Intelligence in Academic Research: Contributor, Constructivist or Cheat?
Date
Authors
Scott-Kennel, Joanna
Zhang, Rongmei
Scott, Jonathan
Supervisor
Item type
Journal Article
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
Taylor and Francis Group
Abstract
The role of generative AI (Gen-AI) in the academic research process remains underexplored. This paper examines how Chatbots might be integrated into academic research, distinguishing this application from traditional uses of machine learning in marketing research and data analysis. Using Constructivist Learning Theory (CLT) as a framework, we experiment with queries at different stages of the research process, including the literature review, research gap identification, theory alignment, and method selection. The study contributes to understanding how AI can support academic research in marketing. Responses from ChatGPT, Gemini, Perplexity and Claude are compared and potential benefits and limitations for marketing scholars discussed.Description
Keywords
35 Commerce, Management, Tourism and Services, 3506 Marketing, Machine Learning and Artificial Intelligence, Networking and Information Technology R&D (NITRD), Generic health relevance, 1505 Marketing, Marketing
Source
Journal of Marketing Theory and Practice, ISSN: 1069-6679 (Print); 1944-7175 (Online), Taylor and Francis Group, 34(3), 501-522. doi: 10.1080/10696679.2025.2457672
Publisher's version
Rights statement
© 2025 The Author(s). Published with license by Taylor & Francis Group, LLC. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.