FACTORS INFLUENCING THE PERFORMANCE APPRAISAL SYSTEM AMONG WOMEN AND MEN: A COMPARATIVE ANALYSIS USING MULTINOMIAL LOGISTIC REGRESSION APPROACH

In our research outcome we presented the results of a comparative analysis among men and women on the employee factors influencing the evaluation performance appraisal system using Multinomial Regression Analysis with reference to Agriculture Research Sector employees in Hyderabad Metro, India. The primary data collected from the performance appraisal forms of 400 employees including 300 Men and 100 Women, working in the agriculture research institutes in and around Hyderabad. The seven independent factors Job Knowledge, Skill Level, Job Execution, Initiative, Client Orientation, Team Work, Compliance to Policies and Practices, and one dependent factor, the final outcome of the Performance Appraisal System the Rating measured. The descriptive analysis, and Multinomial Logistic Regression analysis carried out to arrive at the conclusions. To measure the reliability of the instrument used for this study and internal consistencies the reliability statistics Cronbach's alpha (C-Alpha) was estimated. The overall C-Alpha value for men measured at 0.91 and 0.94 for women, and the C-Alpha values for all the factors ranged 0.84 to 0.85 for men and 0.79 to 0.90 for women. The overall Spearman Brown Split-half reliability measured at 0.88 and 0.86 for men and women respectively. The multinomial logistic regression analysis was performed to estimate the likelyhood odds ratios (ORs) to explain the factors associated outcome of the performance appraisal system Rating, a dependent variable. It can be observed from the relative log odds ratios of Women that significant negative influence of all the independent variables, except Client Orientation at 95% CI level for the dependent variable Rating outcome Good and Excellent versus Outstanding. In case of Men all the independent factors negatively contributing for this model for performance appraisal outcome Rating Good, Excellent vs Outstanding. This was explained in detail in the Results section of the paper.