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A New Method for Academic Staff Selection: A Hybrid Analysis Integrating Neutrosophic Brown-Gibson Model and Neutrosophic AHP
Antonios Paraskevas and Michael Madas
Appropriate selection of academic staff is considered a crucial factor for establishing competitiveness, efficiency, and reputation in an academic institute. This selection plays an important role in achieving strategic goals, particularly by emphasizing a strong commitment to providing an excellent student experience and high-quality innovative teaching and learning practices. This paper proposes a novel hybrid method of multi-criteria decision making that helps decision makers select the optimal candidate for an academic position by considering both quantitative and qualitative aspects. Our proposed methodology utilizes neutrosophic AHP and neutrosophic theory to analyze staff selection based on objective, critical, and subjective criteria. In this approach, we introduce a new model called the neutrosophic Brown-Gibson model (N-BG), which is based on single-valued neutrosophic numbers. This model makes the staff selection problem more realistic and facilitates managerial understanding by considering the uncertainty and vagueness that occur when capturing subjective assessments from decision makers. This manuscript also presents a new neutrosophic objective factor correlated with a score function, which plays a key role in the N-BG method. Finally, we evaluate the applicability and effectiveness of our proposed method in the academic staff selection problem through the analysis of a real case study. The robustness of our solution is demonstrated through a comparative study and sensitivity analysis.
Keywords: MCDM methods, analytical hierarchy process, brown-gibson model, personnel recruitment, neutrosophic set theory