Supplier selection model for commodities procurement. Optimised assessment using a fuzzy decision support system

The selection of the most suitable supplier for a procurement process has a markedly strategic aspect for a company. Within this ambit, the literature review shows a lack of uniformity in the terms used to define the phases or components of a procurement process as well as in the election of the critical variables used to select the most suitable supplier. Furthermore, this literature shows a wide variety of individual and integrated methodologies that have been developed so far in an attempt to optimise such a selection.This work proposes a new suppliers’ evaluation-and-selection model. The model homogenises the terminology involved in such processes and fulfils three main goals. First, it allows the joint assessment and comparison among new and historical suppliers, identifying the key evaluation factors in each case. Second, it allows the inherent knowledge about evaluation to be flexibly adapted to the type of product to be purchased – in this paper “basic products” – according to Kraljic's terminology (a major issue in procurement management and not taken into account by any of the models proposed so far). Finally, a FDSS is proposed to make the model operational. The proposed method is robust enough to improve the main shortcomings of more simplistic methods (e.g. those based on weights) and eases the comprehension of the embedded knowledge within the supplier evaluation processes. Simultaneously, this method avoids the complexity of real-life implementation that many of some more sophisticated hybrid methods proposed in recent times – not free of certain additional disadvantages. Finally, the practical usefulness of the proposed method is ascertained through an empirical test in a specific business environment.

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► We design a model to select suppliers in procurement processes which evaluates bids made by new and historical suppliers.
► The model's performance is evaluated by a variable weighting system and by a fuzzy decision support system (FDSS).
► The results obtained by the FDSS adapt better to the actual behaviour of the purchase of commodities than weights methods.
► The system is flexible enough to fit the policies specific to a specific type of product and a particular business sector.
► The acceptance of the proposed model has been validated by a survey test.