Integrating Qualitative and Quantitative Factors in Supplier Selection and Performance Evaluation

Abstract

Companies need to cooperate with reliable and high-performing suppliers of goods and services, and build mutual long-term relationships in order to sustain their existence and increase their market share. An engineering manager can determine the most effective strategy in supplier selection by the proposed model, which allows an integration of objective values and the uncertainty of human judgements. A two-stage integrated fuzzy analytic network process (FANP) and super-efficiency data envelopment analysis (DEA) model is proposed and applied to a wind turbine project of a company operating in the renewable energy sector. At the first stage of the methodology, the weights of the qualitative criteria were determined by using FANP. At the second stage, the qualitative supplier selection criteria that were converted into quantitative criteria with FANP were used as outputs; and cost (which was already a quantitative criterion) was used as an input in the DEA, by way of which the performances of the suppliers were assessed. This study, which includes decision-making, performance management, and supply chain management issues, introduces a new approach, both in terms of the sector referred to and the methodology that enables companies to select the best suppliers by assessing both qualitative and quantitative factors.

Optimising the Analysis Stage in the Internationalisation of Manufacturing Operations

“…In this sense, Armengol et al [18] identify a research gap on quantitative tools for decision-making on the internationalisation of operations. Here, this work focuses on a specific analysis stage that requires configuring a decision model to deal with NFI and GSND challenges [13] that impact the production and logistics system design, as well as the associated suppliers network design [19,20]. The main contributions of the paper are twofold: (i) to propose a new mixed integer linear programming (MILP) model with production multilocalisation and distributed production to optimise and simulate the analysis and design of global supply chains; and (ii) to test and validate the proposed model in a real case study of a Spanish SME (small and medium enterprise) manufacturing office chairs.…”