A supply chain collaborative model : integrating the design, operation and measurement stages of supply chain

Pao Yue-kong Library Electronic Theses Database

A supply chain collaborative model : integrating the design, operation and measurement stages of supply chain

 

Author: Lam, Chi-yung
Title: A supply chain collaborative model : integrating the design, operation and measurement stages of supply chain
Degree: Ph.D.
Year: 2011
Subject: Business logistics
Hong Kong Polytechnic University -- Dissertations
Department: Dept. of Industrial and Systems Engineering
Pages: xiv, 198 leaves : ill. ; 30 cm.
InnoPac Record: http://library.polyu.edu.hk/record=b2441571
URI: http://theses.lib.polyu.edu.hk/handle/200/6102
Abstract: Supply chain collaboration offers significant opportunities for supply chain entities in value creation, and developing collaborative and cohesive relationships between entities in the supply chain is essential for maintaining the competitiveness of the supply chain network. The research presented in this thesis aims to fill the gaps in the existing literature by conducting a study of supply chain collaboration from a perspective that extends the traditional study of the operation stage to its two extremes in the design and measurement stages. Accordingly, a Supply Chain Collaborative (SCC) model is proposed which covers the multiple stages of the design, operation and measurement of the supply chain. Under the SCC model, a Cross Functional Partnership Selection (CFPS) sub-model is proposed for the design stage to select and partner supply chain entities; a Cross Entity Operational Planning (CEOP) sub-model is proposed for the operation stage to develop effective and efficient collaboration between common supply chain operational activities; and a Cross Domain Performance Measurement (CDPM) sub-model is proposed for the measurement stage to measure and evaluate the collaborative performance of the entire supply chain. In the development of the SCC model, network graph theory, mathematical programming and statistical methods are applied to the modelling of the design, operation and measurement stages. Following this, the SCC model is illustrated in a case study of the supply chain of a company in the made-to-order manufacturing industry. Heuristics methods using genetic algorithms are then adopted to solve the company's different supply chain scenarios. In addition, statistical methods of analysis of variance (ANOVA), trend line and effect size are used to validate the feasibility and usefulness of the proposed model in enhancing supply chain collaboration. The results of the ANOVA testing show a significant difference between the means of testing hypotheses on the order fulfilment percentage (OFP), which means the SCC model does affect the collaborative performance of the supply chain of the company. The trend line analysis shows that a positive and steady high supply chain collaborative performance trend line can be plotted for the OFP value of the SCC model. Finally, the effect size analysis results show that the SCC model has a positive effect on supply chain collaboration and improves the collaborative performance of the overall supply chain of the company in the case study. Therefore, the analysis results from the case study demonstrate that the SCC model has potential significance and a positive effect on supply chain collaboration.

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