JOURNAL ARTICLE
Site Reassignment for Mobile Outreach Teams: Investigating the Effectiveness of Decentralized Decision Making.
Published In: Manufacturing & Service Operations Management (M&SOM) (INFORMS), 2024, v. 26, n. 6. P. 2336 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: van Rijn, Lisanne; de Vries, Harwin; Van Wassenhove, Luk N. 3 of 3
Abstract
This article focuses on optimizing the assignment of outreach healthcare sites to mobile outreach teams to improve service effectiveness in rural and underserved areas, addressing challenges aligned with United Nations Sustainable Development Goal (SDG) 3.8 for universal health coverage by 2030. It proposes a decentralized decision-making approach where subsets of teams collaborate in meetings to reassign sites, contrasting with traditional centralized planning that may not fit contexts granting teams autonomy. Using empirical data from the nongovernmental organization MSI Reproductive Choices' outreach programs in six countries, including a detailed case study in Uganda, the study finds that decentralized approaches—especially simple decision rules based on site takeovers—perform close to centralized optimization and can outperform it when central data are inaccurate. Key moderators influencing effectiveness include the number of teams collaborating, iterations of meetings, site reassignment methods, team grouping strategies, and the accuracy of central estimates. The findings suggest that decentralized site reassignment is a feasible and effective alternative for humanitarian organizations, supporting flexible, locally informed decision making while maintaining near-optimal client service volumes.
Additional Information
- Source:Manufacturing & Service Operations Management (M&SOM) (INFORMS). 2024/11, Vol. 26, Issue 6, p2336
- Document Type:Article
- Subject Area:Social Sciences and Humanities
- Publication Date:2024
- ISSN:1523-4614
- DOI:10.1287/msom.2021.0437
- Accession Number:180921130
- Copyright Statement:Copyright of Manufacturing & Service Operations Management (M&SOM) (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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