Big data analytics and artificial intelligence technologies based collaborative platform empowering absorptive capacity in health care supply chain: An empirical study

Surajit Bag, Pavitra Dhamija, Rajesh Kumar Singh, Muhammad Sabbir Rahman and V. Raja Sreedharan

Journal of Business Research, 2023, vol. 154, issue C

Abstract: The healthcare supply chain involves the manufacturing and delivery of medicines at the right time, at the right place, and in the correct quantity. In the world of uncertainties, especially deadly pandemics, the digitalization of the healthcare supply chain has emerged as one of the urgent phenomena to implement, for which organizations are focussing on the omnichannel healthcare approach. This paper explores (a) the antecedents of big data analytics and artificial intelligence (BDA-AI) technology-based collaborative platform for empowering absorptive capacity in omnichannel health care processes; (b) the effect of BDA-AI collaborative platform powered absorptive capacity in omnichannel health care processes and organization performance. The data is collected using a structured questionnaire from healthcare supply chain executives working in South Africa. The findings indicate that the involvement of managerial factors will improve the capacity of health care organizations to develop a BDA-AI technology-driven collaborative platform to assimilate, transfer and exploit critical information from large data sets. It will capacitate healthcare supply chains to deliver innovative performance to healthcare businesses. This work is the first of its kind to examine big data-based knowledge gained in the context of the omnichannel supply chain.

Keywords: Omnichannel; Healthcare business; Artificial intelligence; Big data analytics; Collaborative platform; Healthcare supply chain; Developing countries (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:154:y:2023:i:c:s0148296322007706

DOI: 10.1016/j.jbusres.2022.113315

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