 Data‐driven allocation of development aid toward sustainable development goals: Evidence from HIV/AIDSJohannes Jakubik and Stefan Feuerriegel Production and Operations Management, 2022, vol. 31, issue 6, 2739-2756 Abstract: Ending the HIV/AIDS epidemic is an important target of the United Nations Sustainable Development Goals (SDGs). To achieve it, countries worldwide donate large amounts of development aid (USD 15.18 billion annually). However, current practice in allocating development aid is largely based on decision heuristics and thus subject to inefficiencies. To address this problem, we aim to support managers of funding bodies in identifying cost‐effective allocations of development aid and thus develop a new decision model. We combine data analytics with mathematical optimization, whereby the former estimates the country‐specific effectiveness of aid, and the latter suggests an allocation under budget constraints. We evaluate our decision model using aid data obtained from the SDG Financing Lab of the OECD, demonstrating that our decision model could reduce the infection rate over current practice. Our work directly benefits managers of funding bodies tasked with financing development activities and helps them achieve cost‐effective progress toward ending the HIV/AIDS epidemic. Date: 2022 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bla:popmgt:v:31:y:2022:i:6:p:2739-2756 Ordering information: This journal article can be ordered from Access Statistics for this article Production and Operations Management is currently edited by Kalyan Singhal More articles in Production and Operations Management from Production and Operations Management Society |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.