A comparative study between analytic network process and analytic hierarchy process techniques: a case study of candidate selection

This study applies and compares four Multi-Criteria Decision-Making (MCDM) techniques: Analytic Hierarchy Process (AHP), Fuzzy AHP, Analytic Network Process (ANP), and Fuzzy ANP to evaluate job candidates based on predefined criteria: technical skills, sales ability, and experience. The research aims to investigate how different decision-making frameworks, particularly those incorporating fuzziness and interdependencies, influence candidate rankings in human resource selection processes. A hypothetical case study was developed using input data adapted from Goepel (2011), ensuring consistency across crisp and fuzzy models. Results reveal that Candidate 2 consistently ranked highest when evaluated using ANP, Fuzzy ANP, and Fuzzy AHP, highlighting the importance of accounting for uncertainty and interrelationships among criteria. In contrast, AHP, which assumes independent criteria and crisp judgments, favored Candidate 1. The study demonstrates that advanced MCDM methods, especially those integrating fuzzy logic and network-based structures, offer more comprehensive and realistic decision outcomes. These findings contribute to the growing body of research on MCDM applications in human resource management and suggest that the selection of decision-making techniques significantly affects candidate rankings and final decisions.