The purpose of this study is to develop a methodology for the identification, categorization and prioritization of operational government-supported healthcare supply chain barriers (GHSCBs).
This study develops a theoretical background for identifying and segregating relevant GHSCBs and proposes a 5W2H (a Toyota production system) with fuzzy DEcision MAking Trial and Evaluation Laboratory (DEMATEL) embedded approach to quantify the causal–effect relationships among the identified operational GHSCBs.
Seven GHSCBs (i.e. uncertainty of demand management, lack of continuous improvement and learning, lack of deadline management, lack of social audit, warehousing equipment unavailability, human resource shortage and inadequate top level monitoring) were identified as significant cause group where the government, top management and decision-makers of government-supported healthcare supply chain (GHSC) have to put efforts.
The results obtained are specific to the GHSC of Indian perspective, which could be extended to global context. However, the proposed approach can be a base and provide a platform to understand and analyze the interactions among GHSCBs.
The proposed methodology will show the appropriate areas for allocating efforts and resources to mitigate the impact of GHSCBs for successful implementation of healthcare supply chain.
According to best of the authors' knowledge, this is the first study of operational barrier for GHSC in India in specific. The use of 5W2H embedded fuzzy DEMATEL approach for the development and analysis of the theoretical framework of Indian GHSCBs is unique in barrier literature.
This work is supported by the Department of Science and Technology- Rajasthan funded through the project No. P.7 (3) Vpro/R&D/2016/5957 entitled “Design of Healthcare Supply Chain for Enhancing Availability and Reducing Wastage of Generic Medicines for Rural Areas in Rajasthan”.
Dixit, A., Routroy, S. and Dubey, S.K. (2021), "Analyzing the operational barriers of government-supported healthcare supply chain", International Journal of Productivity and Performance Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJPPM-09-2020-0493
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