Multiple sourcing strategies and order allocation: an ANPAUGMECON metamodel

Angappa Gunasekaran, Konstantinos Kirytopoulos, Vrassidas Leopoulos, George Mavrotas, Dimitra Voulgaridou

Research output: Contribution to journalArticlepeer-review

23 Scopus citations


Purpose – The strategic importance of sourcing is inherent in the positioning of the purchasing operation in a supply chain and supplier evaluation – a crucial step in sourcing – is a complex multicriteria decision making (MCDM) problem. The purpose of this paper is to provide a metamodel for supplier evaluation and order quantity allocation, based on a MCDM method, namely the Analytic Network Process (ANP) and a multiobjective mathematical programming method (MOMP), the AUGMECON. Design/methodology/approach The proposed approach consists of two parts. The former develops and applies the ANP method in order to evaluate the suppliers in qualitative terms. The latter implements the AUGMECON method in order to find the Pareto optimal solutions for the allocation of order quantities in a multiple sourcing environment. The integrated metamodel is exposed through an illustrative case concerning the parapharmaceutical enterprise cluster in Greece. Findings The proposed metamodel constitutes an efficient method that enables managers to actively participate in the decision making process and exploit the “qualitative value” of their suppliers, while minimizing the costs and the mean delivery times. In addition, it is proved to be suitable for the enterprise clusters, as it adapts a multiple sourcing strategy and enhances the partnership among the members. Research limitations/implications The outcome of the model is highly dependent on the inputs provided by the decision maker. Moreover, the ANP method is computational intensive, but this limitation can be alleviated by appropriate software tools. Originality/value The proposed metamodel is an innovative approach for decision making in the area of multiple sourcing and order allocation.

Original languageEnglish (US)
Pages (from-to)263-276
Number of pages14
JournalSupply Chain Management
Issue number4
StatePublished - Jun 22 2010

All Science Journal Classification (ASJC) codes

  • General Business, Management and Accounting


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