Journal
PRODUCTION AND OPERATIONS MANAGEMENT
Volume 30, Issue 9, Pages 3116-3142Publisher
WILEY
DOI: 10.1111/poms.13420
Keywords
public health supply chains; commodity stock‐ outs; developing countries; empirical methods
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Public health supply chains in developing countries face resource constraints leading to stock-outs. The study found that expanding commodity range increases the risk of stock-outs, while urban facilities can significantly reduce stock-out likelihood by updating LMIS records daily.
Public health supply chains are channels through which health commodities are distributed among end clients. In developing countries, significant resource constraints hamper the effective and efficient delivery of health commodities, leading to supply chain failures such as stock-outs. While the prevalence of commodity stock-outs is well-acknowledged, there is little by way of systematic and rigorous empirical research that sheds light on the factors that drive such stock-outs in developing countries. The study documented in this article is anchored in the logistics cycle framework that is well-accepted and widely adopted by organizations involved in managing public health supply chains. Using this framework, we empirically investigate how commodity range and a health facility's logistics management information system (LMIS) practices impact the likelihood of stock-outs. We estimate our models using a novel field dataset spanning 4000 health facilities across five developing countries. Our results indicate that the likelihood of stock-outs increases with an expansion in the range of health commodities offered through the public health supply chain. However, the detrimental impact of offering a wider range of health commodities is more severe in resource-constrained rural facilities relative to their urban counterparts. Further, we find that urban facilities can significantly reduce the likelihood of stock-outs by updating their LMIS records on a daily basis. However, in rural facilities, daily LMIS updating is beneficial only when used in conjunction with an electronic LMIS. Our findings have implications for resource allocation to reduce the risk of health commodity stock-outs in developing countries.
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