An Artificial-Intelligence-Based Omnichannel Blood Supply Chain: A Pathway for Sustainable Development

A.M. Ghouri, H.R. Khan, V. Mani, M.A.U. Haq and Ana Beatriz Lopes de Sousa Jabbour ()
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Ana Beatriz Lopes de Sousa Jabbour: Métis Lab EM Normandie - EM Normandie - École de Management de Normandie = EM Normandie Business School

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Abstract: We formulated and tested an innovative omnichannel blood supply chain (OBSC) model based on artificial intelligence (AI) using inputs raised in semi structured interviews conducted with heath care practitioners in a blood supply chain. The proposed AI-based OBSC model addresses the supply and demand imbalance in crucial situations for blood supply chains. A resource dependence theory bottom-up approach was applied to underpin the OBSC model. This model consists of two parts: (a) helping to find the closest and fastest available blood supply (omnichannel perspective) and (b) raising a blood supply request among university students (with the help of the university's IT system) through SMS messaging in case of emergencies or blood shortages (AI perspective). This OBSC model is significant because it contributes to the United Nations' Sustainable Development Goals, specifically the goal 3 to ``ensure healthy lives and promote well-being for all at all ages.'' \textcopyright 2023 Elsevier Inc.

Keywords: Artificial intelligence; Health care; Omnichannel; Supply chain management; Sustainable development (search for similar items in EconPapers)
Date: 2023
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Published in Journal of Business Research, 2023, 164, ⟨10.1016/j.jbusres.2023.113980⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04276023

DOI: 10.1016/j.jbusres.2023.113980

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