An Integrated Conceptual Model of 360-Degree Performance Appraisal and Candidate Forecasting Using Adaptive Neuro-Fuzzy Inference System

Abstract

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.

Neuro-Fuzzy Employee Ranking System in the Public Sector

“…As far as performance measurement is concerned Root Mean Square Method(RMSE) will be preferred [20], along with gbellmf membership function [21]. Membership functions will be optimized by the use of hybrid algorithm compared to backpropagation due to low RMSE average value produced.…”

Performance Evaluation(PE) of Physical Education PA(PA) in Rural Schools in Hunan in the Post PA Era

“…However, with the deepening of the state's attention to the "three rural" issues and the acceleration of the construction of a new round of well-off society in an all-round way. As a country with a large population and a developing country, this fact makes more and more "empty nesters" and even left behind children become one of the focuses of educational PA [3][4].…”