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The Red Queen Effect (RQE) on Business and the Role of Generative AI in Industry 5.0

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  • Saurav Kumar

Abstract

Purpose: The aims of this research paper are bifold firstly, it attempts to identify the contributions of the RQE theory and secondly, to enable corporates to evade the Red Queen Effect by using generative artificial intelligence to be prepared for Industry 5.0. Design/Methodology/Approach: The red queen effect is a metaphor used in the business world to describe the unsuccessful efforts of a company to get ahead of its competition. The red queen effect is the need to continually adapt and evolve to maintain relevance in an ever-changing environment. Companies must constantly innovate and find new ways to stay ahead of the competition to ensure their survival and success. Companies typically research or study the competition and then implement strategies to help boost their company sales and profits. This is an effective and practical method of outmaneuvering the competition. Findings: The use of SD enables GAI to expand CP beyond short-term adjustments and actions, empowering businesses to foresee and create content that takes into account projected future customer preferences and behaviours which seeks to solve the requirement of so-called sustainable consumption patterns by providing the answer in the form of customers mass customization which can be used by the companies to avoid red queen effect currently prevailing in their respective industries thus getting ahead in race of competition and preparing them for future industry 5.0. Practical Implications: While this technique works in theory, companies might not achieve their goals because the competition engages in the same business practice. Despite a company's efforts to surpass the competition, the company does not move forward or grow. Originality/Value: The research is only of its kind solution to Red queen effect faced by companies in current Industry 4.0.

Suggested Citation

  • Saurav Kumar, 2025. "The Red Queen Effect (RQE) on Business and the Role of Generative AI in Industry 5.0," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 15(2), pages 40-53.
  • Handle: RePEc:ers:ijfirm:v:15:y:2025:i:2:p:40-53
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    References listed on IDEAS

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    1. William P. Barnett & Elizabeth G. Pontikes, 2008. "The Red Queen, Success Bias, and Organizational Inertia," Management Science, INFORMS, vol. 54(7), pages 1237-1251, July.
    2. Ashlee Humphreys & Rebecca Jen-Hui Wang & Eileen FischerEditor & Linda PriceAssociate Editor, 2018. "Automated Text Analysis for Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 44(6), pages 1274-1306.
    3. Arturas Kaklauskas & Natalija Lepkova & Saulius Raslanas & Ingrida Vetloviene & Virgis Milevicius & Jevgenij Sepliakov, 2021. "COVID-19 and Green Housing: A Review of Relevant Literature," Energies, MDPI, vol. 14(8), pages 1-38, April.
    4. Pallant, Jessica & Sands, Sean & Karpen, Ingo, 2020. "Product customization: A profile of consumer demand," Journal of Retailing and Consumer Services, Elsevier, vol. 54(C).
    5. Alicia Orea-Giner & Laura Fuentes-Moraleda & Teresa Villacé-Molinero & Ana Muñoz-Mazón & Jorge Calero-Sanz, 2022. "Does the Implementation of Robots in Hotels Influence the Overall TripAdvisor Rating? A Text Mining Analysis from the Industry 5.0 Approach," Post-Print hal-04039195, HAL.
    6. Govindarajan, Vijay & Gupta, Anil K., 2001. "Strategic innovation: a conceptual road map," Business Horizons, Elsevier, vol. 44(4), pages 3-12.
    7. William P. Barnett & Olav Sorenson, 2002. "The Red Queen in organizational creation and development," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 11(2), pages 289-325.
    8. Sebastian Saniuk & Sandra Grabowska & Bożena Gajdzik, 2020. "Social Expectations and Market Changes in the Context of Developing the Industry 4.0 Concept," Sustainability, MDPI, vol. 12(4), pages 1-21, February.
    9. Levinthal, Daniel & March, James G., 1981. "A model of adaptive organizational search," Journal of Economic Behavior & Organization, Elsevier, vol. 2(4), pages 307-333, December.
    10. Sebastian Saniuk & Sandra Grabowska & Martin Straka, 2022. "Identification of Social and Economic Expectations: Contextual Reasons for the Transformation Process of Industry 4.0 into the Industry 5.0 Concept," Sustainability, MDPI, vol. 14(3), pages 1-20, January.
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    Keywords

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    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • L21 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Business Objectives of the Firm
    • M20 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - General

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