Selection of the strategic alliance partner in logistics value chain

Bueyuekoezkan G., FEYZİOĞLU O., NEBOL E.

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, vol.113, no.1, pp.148-158, 2008 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 113 Issue: 1
  • Publication Date: 2008
  • Doi Number: 10.1016/j.ijpe.2007.01.016
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.148-158
  • Keywords: electronic (e)-logistics, logistics value chain, strategic alliances, partner selection, MCDM, fuzzy AHP, fuzzy TOPSIS, MULTICRITERIA DECISION-MAKING, EXTENT ANALYSIS METHOD, SUPPLY CHAIN, 3RD-PARTY LOGISTICS, SERVICE QUALITY, PERFORMANCE, FRAMEWORK, SYSTEMS, TOPSIS, FIRMS
  • Galatasaray University Affiliated: Yes


As the incredible growth of the Internet is changing the way corporations conduct business, logistics service providers must consider changing their traditional logistics system into an electronic (e)-logistics system. The purpose of this study is to provide a decision support to make a careful assessment of e-logistics partner. As a matter of fact, companies are increasingly aware that they need to work together with their logistics partners in order to best serve their customers and achieve business excellence. However, the selection of a suitable partner for strategic alliance in a logistics value chain is not an easy decision and is associated with uncertainty and complexity. For this reason, the aim of this research is to propose a multi-criteria decision-making (MCDM) approach to effectively evaluate e-logistics-based strategic alliance partners. In addition, because subjective considerations are relevant to the partner evaluation and selection decision, a fuzzy logic approach is adopted. The proposed evaluation procedure consists of several steps. First, we identify the strategic main and sub-criteria of alliance partner selection that companies consider the most important. After constructing the evaluation criteria hierarchy, we calculate the criteria weights by applying the fuzzy Analytic Hierarchy Process (AHP) method. Finally, we conduct the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to achieve the final partner-ranking results. A case study is also given to demonstrate the potential of the methodology. (c) 2007 Published by Elsevier B.V.