An Integrated Conceptual Model of 360-Degree Performance Appraisal and Candidate Forecasting Using Adaptive Neuro-Fuzzy Inference System
DOI:
https://doi.org/10.13052/jmm1550-4646.1642Keywords:
Adaptive fuzzy logic, neuro-fuzzy recruitment system, one-way ANOVA, performance appraisal, 360-degree performance evaluationAbstract
360-degree evaluations are popular performance appraisal method that involves evaluation input from multiple levels within the firm as well as external sources. However, subordinate can be bias the ratings. The performance appraisal process is far from accurate and objective, sometimes resulting in rating errors. This article proposes an approach to minimizing subjective judgement in the effective employee evaluation in the existence of the multi-factor competency-based measures in a hierarchical structure using ANFIS and ANOVA algorithm. This study supports the ideas that the best MSE (0.0056) calculation is achieved by Using Adaptive Neuro-Fuzzy Inference System (ANFIS) with ANOVA selection features. The method suggested helps Human Resource (HR) managers to make more objective decisions for put right man on right time. The predicting behavioural competencies of employees to make investment in human development more effective. It is also a change in the decision-making concept of Human Resource Development (HRD) from feelings about the decision based on more information.
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