 Bargaining with algorithms: How consumers respond to offers proposed by algorithms versus humansZhengyu Shen and Liyin Jin Journal of Retailing, 2024, vol. 100, issue 3, 345-361 Abstract: The rapid integration of artificial intelligence (AI) into negotiations has catalyzed a transformative change in the retail industry. This study analyzes consumer responses to AI negotiators—a scenario becoming more common as retailers employ sophisticated algorithms in negotiation practices. Through five studies spanning B2C, B2B, and C2C negotiations, the findings reveal that consumers tend to make fewer adjustments to their counteroffers when bargaining with algorithms, persuaded of algorithms’ decision-making precision and comprehensive market intelligence. Notably, this confidence in algorithmic accuracy has a disproportionate effect on individuals from lower socioeconomic backgrounds, which can be mitigated by casting doubt on AI's infallibility. These insights do not merely provide retailers with a tactical advantage in utilizing AI for negotiations but also highlight the necessity for a more profound and ethical interaction with technology. Understanding the dynamics of human‒algorithm interaction in negotiation contexts allows retailers and brands to navigate this new terrain with greater efficacy and mindfulness. Keywords: Algorithms; Negotiation; Human–algorithm interaction; Algorithm perception (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jouret:v:100:y:2024:i:3:p:345-361 DOI: 10.1016/j.jretai.2024.05.001 Access Statistics for this article Journal of Retailing is currently edited by A. Roggeveen More articles in Journal of Retailing from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.