Fuzzy comprehensive evaluation and quantitative weight analysis in structure management of human resources

Abstract

This research delves into the application effects of Fuzzy Comprehensive Evaluation (FCE) and quantitative weight analysis in the structure management of human resources (SMHR) to optimize the structure management. The research begins by analyzing the existing problems in SMHR, such as incomplete performance feedback and error-prone outsourcing decisions. By leveraging human resource management (HRM) characteristics, the researchers construct the SMHR evaluation index system. The Analytical Hierarchy Process (AHP) is employed to establish a hierarchical human resource structure model to determine the relative weight of each HRM indicator. Subsequently, the FCE method is utilized to build an SMHR optimization model, which is then scrutinized and assessed by means of an example. The findings indicate that the consistency ratio (C.R.) values of the first and second-level evaluation factors of the constructed model are less than 0.1, thus passing the consistency test and demonstrating credibility. Ultimately, the research effectively grades SMHR in the enterprise through the analysis of HRM optimization. Accordingly, this research presents a set of optimization suggestions and measures, including the establishment of a professional HRM operation team, acceleration of the construction of a professional talent team, enhancement of the intelligent level of the HRM center, and transition towards digital sharing. These proposed measures can serve as valuable experimental references for the optimization and improvement of HRM structures in future enterprises.

Study on Resilience Evaluation for Construction Management of Major Railway Projects

“…This study used the AHP to determine the weights of indicators. AHP first hierarchizes a problem, decomposes it into different constituent factors according to the nature of the problem and the overall goal to be achieved, and forms different levels of aggregation combinations in accordance with the interrelated influences and affiliations among the factors, so as to constitute a multilevel analytical structural model [50,51]. The scale method of a 1 to 9 scale was used to judge the importance of two elements in the matrix for two-by-two comparison, and to assign a value to the degree of importance.…”