Modeling the values of private sector agents in multi-echelon humanitarian supply chains

Corinne Carland, Jarrod Goentzel, Gilberto Montibeller*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

Humanitarian organizations (HOs) increasingly look to engage private sector supply chains in achieving outcomes. The right engagement approach may require knowledge of agents’ preferences across multi-echelon supply chains to align private sector value creation with humanitarian outcomes. We propose a multi-attribute value analysis (MAVA) framework to elucidate such preferences. We formalize this approach and apply it in collaboration with a HO pilot aiming to facilitate better private sector availability of malaria rapid diagnostic tests in Uganda. We demonstrate how HOs could use criteria weights and value functions from MAVA for project evaluation; in the process, we reveal business model insights for importers, distributors, and retailers in the pilot. We also show how MAVA facilitates the impact assessment of hypothetical options (i.e., combinations of products, services, and subsidies) to guide HO resource deployment. This paper offers the first attempt, to our knowledge, to develop quantitative measures for economic and non-economic objectives involving all agents in a multi-echelon supply chain, either humanitarian or commercial. We hope that this initial step stimulates further research to validate results and develop the framework proposed.

Original languageEnglish
Pages (from-to)532-543
Number of pages12
JournalEuropean Journal of Operational Research
Volume269
Issue number2
DOIs
StatePublished - 1 Sep 2018
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2018 Elsevier B.V.

Keywords

  • Global health
  • Humanitarian logistics
  • Humanitarian supply chains
  • Multi-criteria decision analysis
  • OR in societal problems

ASJC Scopus subject areas

  • General Computer Science
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

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