The rise of human–machine collaboration: Managers' perceptions of leveraging artificial intelligence for enhanced B2B service recovery

Ameen, Nisreen, Pagani, Margherita, Pantano, Eleonora, Cheah, Jun Hwa ORCID: https://orcid.org/0000-0001-8440-9564, Tarba, Shlomo and Xia, Senmao (2024) The rise of human–machine collaboration: Managers' perceptions of leveraging artificial intelligence for enhanced B2B service recovery. British Journal of Management. ISSN 1045-3172

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Abstract

This research analyses managers’ perceptions of the multiple types of artificial intelligence (AI) required at each stage of the business-to-business (B2B) service recovery journey for successful human–AI collaboration in this context. Study 1 is an exploratory study that identifies managers’ perceptions of the main stages of a B2B service recovery journey based on human–AI collaboration and the corresponding roles of the human–AI collaboration at each stage. Study 2 provides an empirical examination of the proposed theoretical framework to identify the specific types of intelligence required by AI to enhance performance in each stage of B2B service recovery, based on managers’ perceptions. Our findings show that the prediction stage benefits from collaborations involving processing-speed and visual-spatial AI. The detection stage requires logic-mathematical, social and processing-speed AI. The recovery stage requires logic-mathematical, social, verbal-linguistic and processing-speed AI. The post-recovery stage calls for logic-mathematical, social, verbal-linguistic and processing-speed AI.

Item Type:	Article
Uncontrolled Keywords:	business, management and accounting(all),strategy and management,management of technology and innovation ,/dk/atira/pure/subjectarea/asjc/1400
Faculty \ School:	Faculty of Social Sciences > Norwich Business School
Depositing User:	LivePure Connector
Date Deposited:	01 Jul 2024 11:33
Last Modified:	01 Nov 2024 12:30
URI:	https://ueaeprints.uea.ac.uk/id/eprint/95721
DOI:	10.1111/1467-8551.12829

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