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The perks and perils of artificial intelligence use in lateral exchange markets

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  • Satornino, Cinthia B.
  • Grewal, Dhruv
  • Guha, Abhijit
  • Schweiger, Elisa B.
  • Goodstein, Ronald C.

Abstract

Artificial intelligence (AI) clearly can benefit standard business models, in which firms sell products to buyers. But the outcomes of greater reliance on AI in peer-to-peer marketplaces, also known as lateral exchange markets (LEMs), might differ. Deploying AI likely improves outcomes for buyers and sellers (separately), as well as the effectiveness of their matching. In contrast, contingencies related to the power of the LEM and the presence and interaction of buyers and sellers (consociality) may evoke a dark side of AI. Guided by literature on LEMs, AI, and agency theory, the current work establishes buy- and sell-side tensions that arise when LEMs deploy AI. With a unique focus on buyers and sellers (cf. platforms) in LEMs and careful attention to the dark side, as well as the bright side, of AI, this article offers novel perspectives and implications for research and practice.

Suggested Citation

  • Satornino, Cinthia B. & Grewal, Dhruv & Guha, Abhijit & Schweiger, Elisa B. & Goodstein, Ronald C., 2023. "The perks and perils of artificial intelligence use in lateral exchange markets," Journal of Business Research, Elsevier, vol. 158(C).
    • Handle: RePEc:eee:jbrese:v:158:y:2023:i:c:s0148296322010451
    DOI: 10.1016/j.jbusres.2022.113580
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    1. Kevin J. Boudreau & Andrei Hagiu, 2009. "Platform Rules: Multi-Sided Platforms as Regulators," Chapters, in: Annabelle Gawer (ed.), Platforms, Markets and Innovation, chapter 7, Edward Elgar Publishing.
    2. Guha, Abhijit & Grewal, Dhruv & Kopalle, Praveen K. & Haenlein, Michael & Schneider, Matthew J. & Jung, Hyunseok & Moustafa, Rida & Hegde, Dinesh R. & Hawkins, Gary, 2021. "How artificial intelligence will affect the future of retailing," Journal of Retailing, Elsevier, vol. 97(1), pages 28-41.
    3. Benoit, Sabine & Baker, Thomas L. & Bolton, Ruth N. & Gruber, Thorsten & Kandampully, Jay, 2017. "A triadic framework for collaborative consumption (CC): Motives, activities and resources & capabilities of actors," Journal of Business Research, Elsevier, vol. 79(C), pages 219-227.
    4. Jin, Byoungho Ellie & Shin, Daeun Chloe, 2020. "Changing the game to compete: Innovations in the fashion retail industry from the disruptive business model," Business Horizons, Elsevier, vol. 63(3), pages 301-311.
    5. Arun Rai, 2020. "Explainable AI: from black box to glass box," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 137-141, January.
    6. Fleura Bardhi & Giana M. Eckhardt, 2012. "Access-Based Consumption: The Case of Car Sharing," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 39(4), pages 881-898.
    7. Dwivedi, Yogesh K. & Hughes, Laurie & Ismagilova, Elvira & Aarts, Gert & Coombs, Crispin & Crick, Tom & Duan, Yanqing & Dwivedi, Rohita & Edwards, John & Eirug, Aled & Galanos, Vassilis & Ilavarasan, , 2021. "Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy," International Journal of Information Management, Elsevier, vol. 57(C).
    8. Grewal, Dhruv & Guha, Abhijit & Satornino, Cinthia B. & Schweiger, Elisa B., 2021. "Artificial intelligence: The light and the darkness," Journal of Business Research, Elsevier, vol. 136(C), pages 229-236.
    9. Grewal, Dhruv & Herhausen, Dennis & Ludwig, Stephan & Villarroel Ordenes, Francisco, 2022. "The Future of Digital Communication Research: Considering Dynamics and Multimodality," Journal of Retailing, Elsevier, vol. 98(2), pages 224-240.
    10. Carliss Y. Baldwin & C. Jason Woodard, 2009. "The Architecture of Platforms: A Unified View," Chapters, in: Annabelle Gawer (ed.), Platforms, Markets and Innovation, chapter 2, Edward Elgar Publishing.
    11. Thomas Davenport & Abhijit Guha & Dhruv Grewal & Timna Bressgott, 2020. "How artificial intelligence will change the future of marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 24-42, January.
    12. Verónica H. Villena & Christopher W. Craighead, 2017. "On the Same Page? How Asymmetric Buyer–Supplier Relationships Affect Opportunism and Performance," Production and Operations Management, Production and Operations Management Society, vol. 26(3), pages 491-508, March.
    13. Aguirre, Elizabeth & Mahr, Dominik & Grewal, Dhruv & de Ruyter, Ko & Wetzels, Martin, 2015. "Unraveling the Personalization Paradox: The Effect of Information Collection and Trust-Building Strategies on Online Advertisement Effectiveness," Journal of Retailing, Elsevier, vol. 91(1), pages 34-49.
    14. repec:elg:eechap:15612_26 is not listed on IDEAS
    15. Nisreen Ameen & Ali Tarhini & Alexander Reppel & Amitabh Anand, 2021. "Customer experiences in the age of artificial intelligence," Post-Print halshs-03045430, HAL.
    16. Steven Tadelis, 2016. "Reputation and Feedback Systems in Online Platform Markets," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 321-340, October.
    17. Ming-Hui Huang & Roland T. Rust, 2021. "A strategic framework for artificial intelligence in marketing," Journal of the Academy of Marketing Science, Springer, vol. 49(1), pages 30-50, January.
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