Year: 2026
Type: article
Abstract: Context: Evaluating third-party logistics (3PL) providers is a complex task since multiple criteria assessed by experts with potentially diverse perspectives are involved, leading to varying scores based on individual prioritizations. This study attempts to evaluate 3PL providers for a mid-sized fishery company in Jakarta, Indonesia, focusing on refrigerated transportation within cold chain logistics. Method: A methodology integrating rough stepwise weight assessment ratio analysis (R-SWARA) and complex proportional assessment (COPRAS) is employed to address expert uncertainty and rank six providers based on seven criteria: security, punctuality, cost, delivery area, customer service, assurance, and logistics experience. R-SWARA assigns weights using rough set intervals, while COPRAS ranks providers. Results: The integrated methods yield Vendor A as the top choice, with a utility degree of 100%, followed by Vendor D and others ranging from 96.7 to 98.4%. These rankings highlight the critical role of punctuality and security in refrigerated transportation, aligning with the fishery industry’s need to ensure product freshness and reliability. A sensitivity analysis that varies the weight of punctuality by ± 20% confirms the ranking’s stability, highlighting the methodology’s robustness. The findings align with prior studies emphasizing performance and quality in logistics, while R-SWARA’s use of intervals offers a novel approach to handling uncertainty. Conclusions: The proposed method recommends Vendor A to ensure timely and secure seafood delivery, with implications for perishable goods logistics. The limitations include a small expert panel and a single-case focus, suggesting the need for future research with larger samples and broader applications. Another limitation of the proposed approach is its reliance on expert judgement for criteria weighting, as well as its sensitivity to the selected criteria and case context. Therefore, the findings should be interpreted as a decision support rather than universal rankings.
Source: Ingeniería
Authors: Adhie Prayogo, Muhammad Mujiya Ulkhaq
Institutions: Muria Kudus University, Diponegoro University
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7208715919