Supplier quality evaluation is a critical part of quality management in global supply chains. Poor supplier quality results in not only monetary losses but also negatively impacts the business potential and future growth of buyer organizations. In this thesis, we propose a multi-tier supplier quality evaluation framework based on total cost of ownership and data envelopment analysis for quality management in global supply chains. The proposed approach comprises of three main steps. Firstly, we group the upstream suppliers based on common attributes using hierarchical cluster analysis. Then, we calculate the total cost of ownership for the grouped suppliers and their sub-suppliers using various qualitative and quantitative factors that are vital for quality management in global supply chains. In the third and the last step, we apply data envelopment analysis to compute the efficiencies of various suppliers to identify the best one (s) and recommend for selection. A numerical application is provided.
The proposed approach is very useful to decision makers in benchmarking supplier quality performances and setting improvement targets for supplier quality development in global supply chains.