Evaluating Employee Performance: An Approach on Łukasiewicz Intuitionistic Fuzzy Sets in BM-Algebras

Abstract

In contemporary human resource management, performance evaluations are often influenced by subjectivity and uncertainty, posing challenges to fairness and accuracy. This study introduces a mathematically grounded approach to employee performance assessment by integrating Łukasiewicz logic with intuitionistic fuzzy set theory, framed within the structure of BM-algebras. We construct and examine Łukasiewicz intuitionistic fuzzy subalgebras (LIFA) and ideals (LIFI), developing a set of theoretical results to define their properties and interactions. Through illustrative examples, we demonstrate the logical consistency and applicability of these constructs. The proposed model employs min-max normalization and fuzzy reasoning to facilitate equitable, transparent, and adaptable evaluations. Beyond workplace settings, this framework holds particular promise for research-oriented educational institutions by fostering inclusive assessment strategies and supporting a more dynamic and responsive learning environment. Moreover, the model’s potential to be scaled and shared across collaborative networks underscores its relevance to collective capacity-building and institutional development.