JOURNAL ARTICLE
Technology-Enabled Agent Choice and Uptake of Social Assistance Programs: Evidence from India's Food Security Program.
Published In: Manufacturing & Service Operations Management (M&SOM) (INFORMS), 2024, v. 26, n. 4. P. 1472 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Allu, Rakesh; Ganesh, Maya; Deo, Sarang; Devalkar, Sripad K. 3 of 3
Abstract
This article examines the impact of technology-enabled agent choice on the uptake of commodities in social assistance programs, focusing on India’s Public Distribution System (PDS), which provides subsidized food grains to low-income households through designated agents. Using a natural experiment comparing two neighboring states—Andhra Pradesh and Telangana—that introduced agent choice at different times, the study finds that enabling beneficiaries to choose their agents increases the quantity of entitlements collected by 6.6%, primarily by encouraging agents to improve compliance with operating guidelines such as keeping shops open more consistently. The effect is significantly stronger in areas with higher agent density, highlighting the importance of accessible alternatives for choice to be effective. These findings suggest that limited forms of choice, where beneficiaries select the place of collection but the product and price remain fixed, can enhance welfare without the operational challenges associated with fully replacing in-kind transfers with cash transfers.
Additional Information
- Source:Manufacturing & Service Operations Management (M&SOM) (INFORMS). 2024/07, Vol. 26, Issue 4, p1472
- Document Type:Article
- Subject Area:Consumer Health
- Publication Date:2024
- ISSN:1523-4614
- DOI:10.1287/msom.2022.0528
- Accession Number:178447834
- 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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