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Cited by 17Meta-analysis and systematic reviewsscientometrics and bibliometrics researchInformation Retrieval and Search Behavior

Are AI tools better than traditional tools in literature searching? Evidence from E-commerce research

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Tomczyk, Przemysław, Brüggemann, Philipp, Mergner, Niklas, Petrescu, Maria·2026·Journal of Librarianship and Information Science
DOI 10.1177/09610006241295802
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Abstract

This article examines the potential implications of Artificial Intelligence (AI) for literature search, comparing AI-based tools to conventional research methods. It also addresses the scarcity of academic literature on specific AI tools for research writing, posing four critical questions regarding accuracy, quality, uniqueness, and qualified uniqueness. Employing Algorithmic Theory and Data Dependency Theory, this project scrutinizes AI performance in algorithms, machine learning models, and data quality. Testing nine e-commerce topics using Scopus, Web of Science, Elicit, and SciSpace, the authors conclude that while conventional methods excel in accuracy and quality, AI tools show promise in uniqueness, complementing literature reviews. The findings also emphasize the judicious integration of AI tools and advocate for further research into new applications and diverse fields. Ultimately, this research offers highly relevant insights into leveraging AI tools to enhance conventional literature search practices in research and professional domains.

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  45. Author biographies Przemyslaw Tomczyk is a PhD in economics in the field of man- agement sciences. He defended his PhD thesis at the Warsaw School of Economics. He is an assistant professor at the Department of Marketing at Kozminski University. He special- izes in the role of artificial intelligence in scientific writing and science automation. He is the author of several dozens of scien- tific publications and the YouTube channel 'dr Przemek Tomczyk AI'. He studies and teaches how to write scientifically faster and better using artificial intelligence.

Authors
Tomczyk, P., Brüggemann, P., Mergner, N., & Petrescu, M.
Affiliations
  • Kozminski University (PL)
  • FernUniversität in Hagen (DE)
  • Embry–Riddle Aeronautical University (US)
Corresponding author
Tomczyk, Przemysław
ORCID
Venue
Journal of Librarianship and Information Science
Publisher
SAGE Publications
Published
2024-11-15
Volume
58
Issue
1
Pages
135-145
ISSN
  • 0022-2232 (ISSN-L)
  • 0961-0006
  • 1741-6477
DOI
10.1177/09610006241295802
OpenAlex
W4404415145
Cited by
17
References
48
Citations by year
2026: 9 · 2025: 8
FWCI
4.77
Type
journal article
Language
en
Open access
Licence
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations
  • Journal of Librarianship and Information Science (publishedVersion)
  • Scholarly Commons (Embry–Riddle Aeronautical University) (submittedVersion, cc-by-nc-nd)
Funders
Academy of Marketing
Topics
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › scientometrics and bibliometrics research
  • Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
Keywords
AI-assisted literature searching, academic writing, search accuracy, search quality, Elicit, SciSpace, Scopus, Web of Science, algorithmic theory

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