A Modular-Based Supplier Evaluation Framework: A Comprehensive Data Analysis of ANP Structure

The analytical network process (ANP) has been widely used to evaluate the suppliers, an important subject in supply chain management. We propose an integrated ANP-based evaluation model, which systematically examines six key decision-making modules. They are: questionnaire design, matrix classification, consistency test, inconsistency identification, uncertain or missing values estimation, and sensitivity analysis of rank reversal. Module 1 involves questionnaire design formats, and Module 2 classifies the collected data. Module 3 introduces the maximum eigenvalue threshold as a critical value for consistency test. The induced bias matrix model (IBMM) is employed in Modules 4 and 5 to identify the inconsistent elements and to estimate the uncertain or missing values. In Module 6, we extend the concept of the IBMM to check for rank reversal when a new alternative or criterion is added that perturbs the evaluation system. The case company in the healthcare device industry under study validates that the proposed method is effective. The integrated model not only improves the questionnaire design and simplifies the ANP consistency tests, but also effectively identifies the inconsistent elements and estimates the missing values. The innovative approach to sensitivity analysis is especially insightful and contributes to the understanding of rank reversal issue.