Transforming Internal Transport Choices – From Functional Practice to Structured Decision

Abstract

This study develops a structured decision-support model for evaluating and comparing transport alternatives for replenishment orders in a global supply chain. A case study was conducted at Company X which evaluates their currently used practice in comparison to a set of transport alternatives. Through which a calculated and theoretical reasoning behind their currently used transport alternative Parcel is provided. A hybrid multi-criteria decision-making (MCDM) framework was constructed, using the Analytical Hierarchy Process (AHP) for creating weights for the criteria and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) II to compare the alternatives. The alternatives, criteria and weights were decided in conjunction with the stakeholders of Company X. Five transport alternatives were evaluated: Parcel, Pallet Express, Pallet Standard, Pallet Consolidated and Sea Freight. The alternatives were evaluated across four criteria: Freight Cost, Lead Time, Delivery Reliability and Environmental Impact. The weight of the criteria was gathered through queries and validated by both aggregated individual judgements (AIJ) and aggregated individual priorities (AIP), resulting in a consistency ratio of 0,04. Two datasets were used, dataset 1 and dataset 2, to evaluate the model and its results. The different datasets consist of products with different characteristics and costs. The results show that their currently used transport solution ranks first in the PROMETHEE II model with dataset 1 with a Net Flow of 0,3605 and achieves the lowest Total Cost of €60 664. Pallet Consolidated emerges as the preferred transport solution for dataset 2, which validates the supply chain strategy theory of there’s no unified optimal solution that can be applied to all products. Parcel performs the best in the two highest weighted criterion: Delivery Reliability and Lead Time, bringing attention to the subjectivity of MCDM models. The research validates Company X current transport solution for replenishment orders and provides a scalable, data-driven framework to evaluate future datasets.