The decision-making for selecting cold chain logistics providers in the food industry
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Abstract
The issue of selecting a third-party logistics (3PL) provider is becoming more important for businesses that want to reduce costs and improve customer service. This is especially true in cold chain logistics (CCL), which has challenges in shipping perishable products. The objectives of this study are to: (1) compile and validate the criteria used to select CCL providers using the index of item-objective congruence (IOC) and expert interviews; (2) determine the importance of the criteria (the weights) based on the rank-order centroid (ROC) method; and (3) apply the fuzzy technique for order preference by similarity to an ideal solution (fuzzy TOPSIS) method to choose the appropriate provider in real life. The food industry is used as a case study. As a result, after validation, there are 11 main criteria broken down into 26 sub-criteria. The five most important criteria are found to be on-time delivery, transportation system standard, transportation cost, trust, and accessibility of contact persons in urgency, respectively. A sensitivity analysis was also undertaken to assess the robustness of selection result. The integration of the fuzzy TOPSIS and ROC methods is able to facilitate a logical selection of a CCL provider and allows the decision-making process depends less on the subjectivity of the decision maker.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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