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Data‐driven allocation of development aid towards Sustainable Development Goals: Evidence from HIV/AIDS

Jakubik, Johannes ORCID iD icon 1,2; Feuerriegel, Stefan
1 Karlsruhe Service Research Institute (KSRI), Karlsruher Institut für Technologie (KIT)
2 Institut für Wirtschaftsinformatik und Marketing (IISM), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

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.


Verlagsausgabe §
DOI: 10.5445/IR/1000144275
Veröffentlicht am 21.10.2022
Originalveröffentlichung
DOI: 10.1111/poms.13714
Scopus
Zitationen: 2
Web of Science
Zitationen: 3
Dimensions
Zitationen: 4
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Wirtschaftsinformatik und Marketing (IISM)
Karlsruhe Service Research Institute (KSRI)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2022
Sprache Englisch
Identifikator ISSN: 1059-1478, 1937-5956
KITopen-ID: 1000144275
Erschienen in Production and Operations Management
Verlag John Wiley and Sons
Band 31
Heft 6
Seiten 2739-2756
Vorab online veröffentlicht am 19.03.2022
Externe Relationen Abstract/Volltext
Nachgewiesen in Scopus
Dimensions
Web of Science
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