A fuzzy TOPSIS methodology to support outsourcing of logistics services

Abstract

PurposeTo present a multi‐attribute approach for the selection and ranking of the most suitable 3PL service provider.Design/methodology/approachThe approach is based on the TOPSIS technique (Technique for Order Preference by Similarity to Ideal Solution) and the fuzzy set theory.FindingsA quantitative methodology based on a structured framework, for the selection of the most appropriate 3PL service provider.Research limitations/implicationsFuture research may attempt to compare the results of the methodology proposed with those of other Multi Attribute Group Decision Making methods. In particular, the selection tree could be developed in a multi‐tier hierarchy, trying to punctually address the relationships between the upper tier criteria and the lower level ones. With multi‐tier hierarchies, the performance of AHP could be compared with the one obtained with TOPSIS, not only with respect to “technical suitability” but also in terms of easiness to implement, shortcomings and general managerial viability.Practical implicationsFrom the application of the methodology to a real case, the approach proposed emerges as an appropriate tool, which makes it possible to easily and effectively rank alternatives. Conversely the most critical issue pointed out by the real case application is the preliminary “request of information” phase, which has to be given critical attention. The availability of a well structured body of knowledge about potential candidates emerged as the true discriminant for an effective analysis.Originality/valueThe originality of the paper is threefold: first, an original framework of criteria for the selection of the most suitable 3PL service provider is presented. Second, an original methodology based on a fuzzy TOPSIS approach is presented. Third, the practical implications and drawbacks are discussed by means of a real case application.