Analysis of the delivery process with cargo bikes: a study on theory versus practice.

Abstract

Across Europe, cities and logistics actors are investing more on solutions to adapt delivery and pickup processes to current mobility and sustainability demands. The cargo bike has emerged as one of these logistics solutions. However, traditional operational models that are used for trucks and vans cannot be applied here. This is due to the difference in the physical nature (reduced carrying capacity) of the bikes and the fact that existing urban infrastructure was not designed with cargo bikes in mind. To address this, there is a growing body of works on theoretical approaches for cargo bike operational models, particularly in routing and scheduling. The aim of this thesis is to study the potential gaps between cargo bike routing and scheduling problems in the literature and the problems currently faced by cycle logistics providers in Europe. A literature review was conducted to understand the current theory on routing and scheduling problems; their parameters, decision variables, operational constraints and the objectives that they consider. Using themes highlighted from the literature, a questionnaire was developed and used as a guide in semi-structured interviews with cycle logistics companies. Findings revealed strong alignments between theory and practice with capacity limits, time windows, workload balancing, energy constraints, topography, weather impacts, and multi-echelon routing being consistently recognised in both domains. However, several misalignments persist. Welfare metrics, pickup and delivery integration, priority deliveries and contractual boundaries remain under-represented in cargo bike literature. To address these discrepancies, the thesis proposes recommendations for future research, including the integration of rider knowledge and welfare considerations into routing models, and the development of more operationally realistic approaches. Recommendations are also provided to cycle logistics managers to support improved planning and decision-making in cycle-logistics operations.