The Influence of Information Technology-Based E-HRM Transformation on Employee Performance through the Improvement of Human Resource Quality and Job Satisfaction

Abstract

Objective: The objective of this study is to evaluate the impact of e-compensation, e-learning, and e-performance appraisal on organisational performance, with employee satisfaction as a mediating variable.

Theoretical Framework: A conceptual research model illustrating the relationships between variables. Core of the model: several independent variables based on e-HRM (E-Learning, E-Performance Appraisals, E-Compensation Management) influence employee performance (Y) both directly and indirectly through employee job satisfaction (Z) as a mediating variable. X1: E-Learning Located at the top left. Represents an online/electronic learning system for employee competency development. X2: E-Performance Appraisals Located at the middle left. Includes an electronic performance appraisal system (feedback, rating, digital KPIs). X3: E-Compensation Management Located at the bottom left. Covers the management of salaries, benefits, and incentives through electronic platforms/automation. Z: Employee Job Satisfaction Located in the center; acts as a mediating variable that receives influence from X1, X2, X3 and transmits the influence to Y. Y: Employee Performance Located on the right. is the main dependent variable measured as the outcome of an organization/individual

Method: The methodology A total of 101 respondents were involved in this research. Data processing was carried out using the Structural Equation Modeling (SEM) method with a Partial Least Squares (PLS) variance-based approach.

Results and Discussion: Based on the reliability and convergent validity analysis, the Compensation Management construct demonstrates excellent measurement quality, with high reliability and an AVE value of 0.73 indicating strong indicator consistency and construct validity. The SEM-PLS analysis further shows that the model possesses strong explanatory power, with R-square values of 0.81, 0.83, and 0.84 for Compensation Management, Employee Satisfaction, and Employee Performance, respectively. These results confirm that the theoretical model has high structural accuracy and predictive validity.

Research Implications: The findings of this study can serve as a basis for policymakers, managers, or practitioners in designing more effective strategies based on variables that have been shown to have a significant impact. By identifying dominant factors, organizations can focus resources and policies on aspects that contribute most to improving performance, satisfaction, or other organizational goals. In addition, the PLS method used allows the research results to remain accurate even with a relatively limited number of respondents, making it applicable in real-world contexts that have data constraints.

Originality/Value: This research has a high level of originality because it uses a Structural Equation Modeling (SEM) approach based on Partial Least Squares (PLS) to analyze complex relationships among latent variables, which has not been widely used in the context or field of this study. This approach provides an advantage in analyzing predictive models with a relatively small sample size, thereby producing valid and reliable empirical findings.