AN AUTOMATED CONSISTENCY ADJUSTMENT ALGORITHM FOR DELPHI–ANALYTICAL HIERARCHY PROCESS MODELS: DESIGN, IMPLEMENTATION, AND VALIDATION

Abstract

Despite the widespread use of the Delphi and Analytic Hierarchy Process (AHP) methods for prioritizing complex problems, a persistent limitation is the persistence of inconsistencies in expert judgment matrices during the AHP data elicitation stage. Existing solutions, particularly genetic algorithm–based approaches, often entail high computational complexity due to population-based search, crossover, and mutation operations, making them less efficient and more difficult to implement in practical settings. There is therefore a need for a simpler, deterministic, and practically implementable consistency ratio (CR) adjustment mechanism within Delphi–AHP frameworks. To address this problem, this study develops a deterministic, automated consistency adjustment algorithm that efficiently corrects inconsistencies in AHP pairwise comparison matrices without relying on genetic algorithm mechanisms. The proposed algorithm was evaluated through controlled experiments on synthetic matrices with varying levels of inconsistency. A design science research methodology guided the development and implementation of the algorithm in a C# web-based decision support system. The framework was validated empirically using data collected from a Delphi–AHP study involving e-learning experts from public and private Nigerian