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• W4386195344 abstract "Purpose The recent pandemic disrupted the way in which businesses transact with each other. In response to maintaining cleanliness in business-to-business (B2B) settings, artificial intelligence (AI)-enabled robots have been adopted as substitutes for cleaning personnel, yet their implications remain largely underexamined. This study aims to examine B2B buyer responses to cleaning information notices (human vs AI-enabled agent) placed at either the entry to the premises or the sales counter, thereby adding to the nascent literature in this line of inquiry. Design/methodology/approach Three field experiments were conducted across diverse B2B businesses (wholesalers in Studies 1–2 and a commercial business in Study 3). To achieve greater empirical rigor and generalizability, this research used diverse stimuli across different B2B settings. In addition, the results ruled out alternate explanations and shed light upon political ideology as a boundary condition. Finally, a single-paper meta-analysis confirmed H1 , consolidating the established effect. Findings Featuring over 1,000 B2B buyers, the results show that politically liberal B2B buyers express greater preference for human over AI-performed cleaning while labor-orientated buyers are indifferent. Importantly, this effect is driven by greater relaxation associated with humans, which in turn, increases their future patronage and referral intent. Originality/value The results enrich the collective knowledge of the adoption of AI-enabled robots, reinforcing for marketing practitioners and businesses that the reliance on human-based outcomes remains a preferred touchpoint in B2B settings, particularly for liberals." @default.
• W4386195344 created "2023-08-27" @default.
• W4386195344 creator A5030170320 @default.
• W4386195344 date "2023-08-29" @default.
• W4386195344 modified "2023-09-25" @default.
• W4386195344 title "Disruptive AI: the response depends on the buyer’s political ideology" @default.
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• W4386195344 doi "https://doi.org/10.1108/jbim-03-2023-0126" @default.
• W4386195344 hasPublicationYear "2023" @default.
• W4386195344 type Work @default.
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