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- W4312872375 abstract "AI has attracted extant literature devoted to different subjects, including healthcare. However, AI studies within healthcare have focused extensively on medical diagnosis, operations, and prescription, to the neglect of healthcare supply chain. To bridge this knowledge gap, we draw on innovation and knowledge transfer theories and an in-depth semi-structured interview to explain how AI-enabled medical drones in healthcare supply chain are transferred to developing countries to solve political, socioeconomics and environmental challenges. Data are collated from gatekeepers' knowledge and innovation transfers of the world's largest medical drone program in Ghana. Our evidence shows that despite the developing economy's peculiarities, a systematic knowledge transfer process was adopted and with the support of enabling factors such as political will, skilled personnel, and institutional cooperation contributed to the transfer of the AI-enabled medical drones. This ensures that there is fluidity in the application of the technology, resulting in political, socio-economic, and environmental benefits." @default.
- W4312872375 created "2023-01-05" @default.
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- W4312872375 date "2022-01-01" @default.
- W4312872375 modified "2023-09-30" @default.
- W4312872375 title "Transferring AI technology in medical supply chain: a disruptive approach at addressing political, socioeconomic, and environmental dilemma in developing economies" @default.
- W4312872375 doi "https://doi.org/10.1504/ijtpm.2022.126139" @default.
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