Abstract

City logistics involves movements of goods in urban areas respecting the municipal and administrative guidelines. The importance of city logistics is growing over the years especially with its role in minimizing traffic congestion and freeing up of public space for city residents. Collaboration is key to managing city logistics operations efficiently. Collaboration can take place in the form of goods consolidation, sharing of resources, information sharing, etc.

In this thesis, we investigate the problems of collaboration planning of stakeholders to achieve sustainable city logistics operations. Two categories of models are proposed to evaluate the collaboration strategies. At the macro level, we have the simplified collaboration square model and advance collaboration square model and at the micro level we have the operational level model. These collaboration decision making models, with their mathematical elaborations on business-to-business, business-to-customer, customer-to-business, and customer-to-customer provide roadmaps for evaluating the collaboration strategies of stakeholders for achieving sustainable city logistics operations attainable under non-chaotic situation and presumptions of human levity tendency.

City logistics stakeholders can strive to achieve effective collaboration strategies for sustainable city logistics operations by mitigating the uncertainty effect and understanding the theories behind the moving nature of the individual complexities of a city. To investigate system complexity, we propose axioms of uncertainty and use spider networks and system dynamics modeling to investigate system elements and their behavior over time.

The strength of the proposed work is its novelty and ability to investigate collaboration strategies both from macro- and micro-perspective allowing the decision maker to have a complete picture of the different possible collaboration opportunities and associated strategies and select the one most suited to their needs for sustainable operations planning.