Digging deep: futuristic building blocks of omni-channel healthcare supply chain resiliency using a machine learning approach
Kumar, Anil and Naz, Farheen and Luthra, Sunil and Vashistha, Rajat and Kumar, Vikas and Garza-Reyes, Jose Arturo and Chhabra, Deepak (2023) Digging deep: futuristic building blocks of omni-channel healthcare supply chain resiliency using a machine learning approach. Journal of Business Research, 162. ISSN 0148-2963
|
Text
1-s2.0-S0148296323002618-main.pdf - Published Version Available under License Creative Commons Attribution. Download (2MB) |
Abstract
There is a lack of studies which have explored the factors of omni-channel healthcare supply chain resiliency (OHSCR). Thus, the current study explores the resiliency factors of healthcare supply chains (HSCs) and the development of futuristic blocks of OHSCR. In the first phase of the study, the resiliency factors of HSCs were identified through an extensive literature review and expert interviews. In the second phase, a machine learning approach, i.e., K-means clustering, was used to develop the futuristic blocks of OHSCR. Lastly, in the third phase, implications and future research propositions were discussed. The findings of this study suggest that the healthcare sector evaluating OHSCR should focus on six key building blocks: data-driven management and transformative technological adoption, flexible and transparent organisational management system, robust and diversified supply chain system, responsible and customer-centric supply chain, information sharing and knowledge management, and strategic alignment and network ecosystem. A conceptual research framework is also proposed to support future research.
| Item Type: | Article | ||||||
|---|---|---|---|---|---|---|---|
| Identification Number: | https://doi.org/10.1016/j.jbusres.2023.113903 | ||||||
| Dates: |
|
||||||
| Uncontrolled Keywords: | Healthcare supply chains, Omni-channel, Resilience, Omni-channel Healthcare Supply Chains Resiliency, Machine learning | ||||||
| Subjects: | CAH11 - computing > CAH11-01 - computing > CAH11-01-05 - artificial intelligence CAH11 - computing > CAH11-01 - computing > CAH11-01-07 - business computing CAH17 - business and management > CAH17-01 - business and management > CAH17-01-02 - business studies CAH17 - business and management > CAH17-01 - business and management > CAH17-01-04 - management studies |
||||||
| Divisions: | Faculty of Business, Law and Social Sciences > Birmingham City Business School | ||||||
| Depositing User: | Vikas Kumar | ||||||
| Date Deposited: | 27 Mar 2023 13:56 | ||||||
| Last Modified: | 18 Apr 2023 09:28 | ||||||
| URI: | https://www.open-access.bcu.ac.uk/id/eprint/14283 |
Actions (login required)
 |
View Item |
Tools
Tools