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What is the future of human-generated systematic literature reviews in an age of artificial intelligence?

Author

Listed:
  • Joern Block

    (University of Trier)

  • Andreas Kuckertz

    (University of Trier
    University of Hohenheim)

Abstract

Recent advancements in artificial intelligence (AI) enable the rapid collection and organization of academic research with the push of a button, prompting a reevaluation of the role and value of human-generated systematic literature reviews (SLRs). In this editorial, we explore the value of the human element in producing SLRs, a method originally designed to reduce human bias in literature synthesis. Throughout the three stages of an SLR—design, study collection and selection, and interpretation and communication—we argue that the human element is not just a potential source of bias but also an essential contributor of value. The value of human-generated SLRs lies in (1) formulating the right questions, (2) strategic inefficiency in literature search and selection, and (3) individualized problematizing and theorizing. To better leverage the human element in SLRs, we call for new forms of hybrid SLRs that combine traditional systematic review methods with empirical fieldwork.

Suggested Citation

  • Joern Block & Andreas Kuckertz, 2024. "What is the future of human-generated systematic literature reviews in an age of artificial intelligence?," Management Review Quarterly, Springer, vol. 74(4), pages 1975-1980, December.
  • Handle: RePEc:spr:manrev:v:74:y:2024:i:4:d:10.1007_s11301-024-00471-8
    DOI: 10.1007/s11301-024-00471-8
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    References listed on IDEAS

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    1. Andreas Kuckertz & Joern Block, 2021. "Reviewing systematic literature reviews: ten key questions and criteria for reviewers," Management Review Quarterly, Springer, vol. 71(3), pages 519-524, July.
    2. Christian Fisch & Joern Block, 2018. "Six tips for your (systematic) literature review in business and management research," Management Review Quarterly, Springer, vol. 68(2), pages 103-106, April.
    3. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
    4. Alessandro Liberati & Douglas G Altman & Jennifer Tetzlaff & Cynthia Mulrow & Peter C Gøtzsche & John P A Ioannidis & Mike Clarke & P J Devereaux & Jos Kleijnen & David Moher, 2009. "The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-28, July.
    5. Mats Alvesson & Jörgen Sandberg, 2020. "The Problematizing Review: A Counterpoint to Elsbach and Van Knippenberg’s Argument for Integrative Reviews," Journal of Management Studies, Wiley Blackwell, vol. 57(6), pages 1290-1304, September.
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    More about this item

    Keywords

    Systematic literature review; Artificial intelligence; Human factor;
    All these keywords.

    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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