A Data-driven Approach to Improve Artisans' Productivity in Distributed Supply Chains
Despite their vital role in the global rural economy, and as a major source of employment for women in the developing world, artisanal supply chains continue to be plagued by low productivity and high poverty levels. Identifying effective and implementable solutions to improve artisan productivity is a challenging task due to high fragmentation in upstream parts of the supply chain, where artisans often work from their individual households. This study presents research conducted in close collaboration with one of the leading exporters of handmade rugs in India. Leveraging insights from the field visits and analysis of detailed supply chain data, we provide robust empirical evidence that frequent supervisor visits can play a crucial role in improving artisans' productivity. Our results from Instrumental Variables analysis indicate that a one-day decrease in the average number of days between supervisor visits to remote weavers can decrease weaving times by 13.1%-14.1%, which can lead to a 15%-17% increase in monthly income for weavers. Our analysis also suggests that this impact is heterogeneous, with visits to difficult-to-weave rugs, and visits that are more consistently scheduled, leading to maximum productivity gains for the weavers. To capitalize on these insights, we propose a novel predict-then-optimize framework for optimizing supervisor visits in the supply chain. Finally, we demonstrate that the proposed framework can significantly increase weaver productivity even after accounting for various operational and scheduling constraints. This research offers valuable insights into other distributed supply chains and highlight how supply chain considerations can play a critical role in improving the productivity of the workforce in resource-constrained settings
Year of publication: |
[2023]
|
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Authors: | Singhvi, Divya ; Singhvi, Somya ; Zhang, Xinyu |
Publisher: |
[S.l.] : SSRN |
Saved in:
freely available
Extent: | 1 Online-Ressource (32 p) |
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Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments August 4, 2023 erstellt |
Other identifiers: | 10.2139/ssrn.4531090 [DOI] |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10014343892
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