Elaborating Theory of Swift Even Flow in E‐Fulfillment Operations

Nicolò Masorgo et al.

Journal of Business Logistics2026https://doi.org/10.1111/jbl.70063article
AJG 3ABDC A
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0.50

Abstract

Retailers struggle with late deliveries, thus motivating research to improve e‐fulfillment performance. Studies have primarily investigated order processing and delivery individually but have ignored the interplay between these two e‐fulfillment activities. The Theory of Swift and Even Flow (TSEF) provides a useful frame for examining the e‐fulfillment process, yet it neglects important behavioral factors. We elaborate the TSEF using logic from the Queue‐Length Visibility and Misperception of Feedback Dynamics perspectives to unveil how behaviors in order processing and delivery contribute to delivery performance. We analyze 11,241 orders from a major Vietnamese retailer using econometric methods informed by practitioner interviews. We find a concave relationship between order processing time (OPT) ratio (defined as the proportion of planned lead time consumed by order processing) and lateness. Late orders have OPT ratios exceeding 25% of the planned lead time, and they exhibit higher OPT variance. We also find a U‐shaped relationship between OPT ratio and order delivery time (ODT); expediting deliveries mitigates delays until OPT ratios reach a threshold of 58%. Finally, we argue that workers and managers prioritize the processing of focused orders. Understanding behaviors in the e‐fulfillment process offers insights that extend the TSEF, new research areas, and managerial implications.

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https://doi.org/https://doi.org/10.1111/jbl.70063

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@article{nicolò2026,
  title        = {{Elaborating Theory of Swift Even Flow in E‐Fulfillment Operations}},
  author       = {Nicolò Masorgo et al.},
  journal      = {Journal of Business Logistics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1111/jbl.70063},
}

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F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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