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Abstract
This research aims to examine how, and to what extent, the advanced network technology such as custom-built large-scale network, or internet-based technology contribute to the correlations between supply chain drivers and performance measures. The uniqueness of the research is to use network technology as a leverage factor, instead of merely one of the supply chain drivers, to analyse how it would impact on the correlations between supply chain drivers and performance measures.
Through literature review, we identified the key drivers in supply chain and the key performance indicators as independent and dependent variables respectively for data analysis in the research. We consider the utilisation of network technology as a selection variable in the analysis. We also proposed a set of research questions and hypotheses resulting from the literature review.
The subsequent data analyses attempted to find answers for these questions and test the validity of the hypotheses.
This was achieved by a field survey for 1035 major Australian firms through a structured questionnaire. The response rate of the survey was 20.8%. All these data were analysed with statistical models such as reliability test, multi-collinearity test, MANOVA procedures, factor analysis, and multiple regression modelling to validate whether the survey was robust and how the leverage factor (network technology) would impact on the correlations between supply chain drivers and performance measures.
Each research question and hypothesis was reviewed, validated, and concluded based on the results from data analysis. The key findings from the data analysis support the perception that the network technologies with their external customers and suppliers dramatically affect the correlations between supply chain drivers and performance measures. Statistically it actually determines whether the supply chain will success or fail when comparing firms using the technologies with firms not using them. In general, the impact on the correlations is directional and positive.
A set of validated theoretical models was also proposed to depict the dynamics between supply chain variables under the influence of network technology.
Implications of the findings are also provided in the thesis.