Partner selection in agile supply chains: a fuzzy intelligent approach

Abstract

Partner selection is a fundamental issue in supply chain management as it contributes significantly to overall supply chain performance. However, such decision-making is problematic due to the need to consider both tangible and intangible factors, which cause vagueness, ambiguity and complexity. This paper proposes a new fuzzy intelligent approach for partner selection in agile supply chains by using fuzzy set theory in combination with radial basis function artificial neural network. Using these two approaches in combination enables the model to classify potential partners in the qualification phase of partner selection efficiently and effectively using very large amounts of both qualitative and quantitative data. The paper includes a worked empirical application of the model with data from 84 representative companies within the Chinese electrical components and equipment industry, to demonstrate its suitability for helping organisational decision-makers in partner selection.

Keywords:

• partner selection
• agile supply chains
• fuzzy set theory
• artificial neural network

Acknowledgements

This work was financially supported by ‘the National Natural Science Foundation of China’ (No. 71202058), ‘the Natural Science Foundation of Fujian Province of China’ (No. 2012J01305) and ‘the Specialized Research Fund for the Doctoral Programme of Higher Education’ (No. 20110121120028). The authors are grateful to the (anonymous) reviewers for their comments, which have helped to improve the paper.