DOAJ Open Access 2026

Determining the Optimal Order Quantity for Perishable Products Affected by Stochastic Transportation Delays

Banthita Kanchanasathita Atchara Wangpa Apisit Pitakcheun Chirakiat Saithong

Abstrak

<i>Background:</i> Transportation delays pose significant challenges for perishable products by reducing freshness, shortening selling duration, and causing lost sales during the delay. <i>Methods:</i> Motivated by the growing importance of transportation delays on perishable products, this study develops a single-period analytical expected profit expression to determine the optimal order quantity that maximizes expected profit. The model incorporates deterioration-driven price reductions, lost sales opportunities occurring during the delay, and the shortened selling duration resulting from delayed delivery, without imposing a specific probability distribution on the transportation delay duration. <i>Results:</i> Numerical experiments illustrate how key parameters influence the optimal order quantity and the corresponding expected profit. Deterioration reduces expected profit by primarily reducing the selling price. In addition, a higher disruption probability reduces both the optimal order quantity and the expected profit, while longer selling durations result in larger order quantities and yield higher expected profits. A low initial selling price can result in negative expected profit, indicating cases where placing the order is inappropriate. <i>Conclusions:</i> The findings offer managerial implications for determining optimal order quantities that maximize profit under transportation delays for perishable products.

Penulis (4)

B

Banthita Kanchanasathita

A

Atchara Wangpa

A

Apisit Pitakcheun

C

Chirakiat Saithong

Format Sitasi

Kanchanasathita, B., Wangpa, A., Pitakcheun, A., Saithong, C. (2026). Determining the Optimal Order Quantity for Perishable Products Affected by Stochastic Transportation Delays. https://doi.org/10.3390/logistics10010022

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Informasi Jurnal
Tahun Terbit
2026
Sumber Database
DOAJ
DOI
10.3390/logistics10010022
Akses
Open Access ✓