Enhancing human resource management system with triangular fuzzy weighted Bonferroni mean operator

Organizations require an efficient human resource management system to manage employee-related matters such as attendance, leave, salaries, and training. The effectiveness of a business relies on how well it manages its human resources. To achieve this, it is important to have a reliable HR management system in place. Therefore, it is necessary to conduct a study on the factors that influence the selection of an HR management system. To gather multiple decision-makers' opinions and account for their interactions, the Bonferroni mean method is commonly used. In dealing with imprecise and uncertain data, triangular fuzzy numbers are used as a more flexible alternative to crisp numbers. This study used the triangular fuzzy weighted Bonferroni mean operator to rank the primary factors for selecting such a system. The five factors considered were human resource functions (C1), technology (C2), software quality (C3), cost (C4), and vendor support system (C5), with input from four decision makers. Based on their opinions, the study found that human resource functions (C1) were considered the most important factor, followed by vendor support (C5), software quality (C3), cost (C4), and technology (C2).