Optimizing crowdshipping effectiveness in B2C deliveries: a multi-criteria approach for crowd selection

This study addresses the growing need for efficient last-mile delivery solutions through crowdshipping, a key element of the sharing economy. The aim of this re- search is to enhance crowdshipping efficiency by developing a novel Multi-Criteria- Based Crowd Selection (MBCS) framework, which optimises the selection of crowd members for delivery tasks. The framework is built on the ELECTRE I method, allowing the evaluation of potential crowd members using multiple criteria such as reliability, availability, and performance of delivery, which were identified through an extensive literature review. Unlike existing methods that typically consider only one or a few unstructured criteria, the proposed MBCS approach provides a comprehen- sive and holistic evaluation of candidates. Case studies demonstrate the effectiveness of the framework in improving decision-making, leading to more reliable and efficient crowdshipping operations. The study’s novelty lies in its structured multi-criteria approach to crowd selection, offering a robust solution to the challenges of last-mile delivery, particularly in complex and dynamic environments.