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|Title:||Value-based optimization of maritime logistics and supply chain||Authors:||Zhang, Xiunian||Keywords:||Engineering::Maritime studies||Issue Date:||2019||Publisher:||Nanyang Technological University||Source:||Zhang, X. (2019). Value-based optimization of maritime logistics and supply chain. Doctoral thesis, Nanyang Technological University, Singapore.||Abstract:||While competition gradually shifts from individual firms to supply chains, research on Supply Chain Management (SCM) starts to gain mounting attention. Value creation is the objective as well as an important performance evaluation criterion of SCM. New theories are in demand to guide advanced SCM strategies and to quantify the value created by these new measures, especially in this new era of technology. The information explosion brings new challenges and opportunities in SCM. The organizations which can leverage on the state-of-the-art information technology to improve SCM and therefore maximize the value creation would gain a competitive edge in today’s fierce global competition. As 90% of world trade is shipped by sea, maritime logistics plays an indispensable role in global supply chains. This study dedicates to maximize the value created by SCM. It investigates a pressing optimization problem in maritime logistics from the value-based perspective and applies this value-based optimization approach to quantify the value created by information sharing in SCM. The research starts with a review of the previous work on supply chain value creation (SCVC) and proposes a theoretical framework to guide future theory-driven research. The review work makes a solid contribution to the theory building in SCM and serves as a powerful tool for practitioners to formulate or strengthen their SCM strategies. Guided by the framework, value-based management (VBM) is found to be a theory with great potential to guide the operations research (OR) work in the SCVC field. The review also suggests information sharing to be a promising strategy to boost SCVC. Therefore, this study continues to investigate supply chain optimization from the VBM perspective and apply the enhanced VBM theory to exploring information sharing in the digital revolution. This study includes two parts. In the first part, two mathematical models are built based on the value creation logic from the VBM perspective. The decision models facilitate to solve supply chain planning problems in seaborne cold chains, a niche area in SCM which encompasses numerous noteworthy research opportunities. The value-based optimization model is proved to outperform the conventional optimization method, especially on the financial aspect. In the second part, a fuzzy Delphi-AHP-TOPSIS framework is proposed to guide the empirical research on the barriers to the adoption of new information technology. Furthermore, VBM and System Dynamics (SD) are employed to quantify the value generated by different information sharing strategies in a three-echelon supply chain from the VBM perspective. With versatile research methods applying to a specialized research domain, this study not only contributes to the academic community but also provides practical tools and implications for both industry practitioners and policy makers. From the academic perspective, this study facilitates theory building by proposing a conceptual framework which summarizes previous work and guides future theory-driven research in SCVC. This study also promotes the application of value-based OR tools in SCM which diversifies the inventory of research methodologies. Moreover, this work provides a peculiar perspective to quantify the impact of information sharing by combining VBM and SD. Supply chain practitioners could also benefit from the useful decision tools and the insightful practical implications.||URI:||https://hdl.handle.net/10356/103437
|DOI:||10.32657/10220/49492||Rights:||This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).||Fulltext Permission:||embargo_20220527||Fulltext Availability:||With Fulltext|
|Appears in Collections:||CEE Theses|
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