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Title: Logistics horizontal collaboration : an agent-based simulation approach to model collaboration dynamics
Author: Zhu, Jie
ISNI:       0000 0004 6348 2473
Awarding Body: Lancaster University
Current Institution: Lancaster University
Date of Award: 2017
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Underutilized capacity, long shipping lead time, high cost and lack of sufficient scale are examples of logistics inefficiencies that have troubled many supply chain operations. Logistics horizontal collaboration (LHC) is believed to be an innovative approach to tackle the increasing logistics challenges. This kind of collaborative logistics is quickly gaining momentum in practice but relevant contributions in literature are scarce. So far it remains unclear how LHC could be structured and operated given the limited understanding of the various characteristics and forms of LHC between companies. Furthermore, the explicit impact of LHC on the participating partners, as well as on the supply chain system is understudied. Very few studies have explored the process of collaboration and how it links to performance behaviours. Case studies and Agent-Based Simulation are employed in this thesis to study the research gaps identified above. Case studies are initially conducted to examine the key elements which can support the design of LHC, and to make a classification of models for collaboration. These are followed by Agent-Based Simulation to model a typical collaboration process and work out what benefits would emerge if participating in horizontal collaboration and how the collaboration can produce the impacts on the supply chain operations for individuals and the system as a whole. The case studies suggest that “collaboration structures”, “collaboration objectives”, “collaboration intensity”, and “collaboration modes” are the four key elements critical to the design of a LHC project. Each element represents an important aspect of the collaboration and exhibits different characteristics and forms. Based on these key elements, several typologies are derived which together provide a comprehensive view to explain the different types of LHC in practice. The simulation modelling demonstrates that LHC can significantly benefit the logistics efficiency in terms of capacity utilization and customer service in the sense of order fill-rate, and such beneficial effects are consistently observed in different supply chain environments. In particular, LHC can produce better logistics performance in a relationship-based supply chain network where downstream customers can support upstream shippers with more stable and predictable demand. On the other hand, information sharing in the collaboration, for the most part, does not facilitate the higher collaboration gains for partners. Specifically, sharing either the demand or supply information in the horizontal collaboration is not helpful in increasing collaboration gains. Hence there is a difference for the value of information sharing in the context of horizontal collaboration as opposed to vertical collaboration, the latter of which is often justified as providing more beneficial gains. The research findings provide insights for practitioners and scholars about how to develop a type of collaboration project or study, as well as enabling a better understanding of the dynamic collaboration effects.
Supervisor: Onggo, Stephan ; Spring, Martin Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral