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SCIENCE ARTICLE
Striking the Balance: How Workplace Flexibility Enhances Engagement and Performance of Employees working in Public and Private settings
1
Faculty of Economics and administration, Department of Human Resource Management, King Abdulaziz University, Saudi Arabia
2
Department of Human Resource Management, King Abdulaziz University, Jeddah, Saudi Arabia, Saudi Arabia
Submission date: 2024-05-28
Final revision date: 2024-07-13
Acceptance date: 2024-08-30
Online publication date: 2024-10-10
Publication date: 2024-10-14
Corresponding author
Musrrat Parveen
Faculty of Economics and administration, Department of Human Resource Management, King Abdulaziz University, Saudi Arabia
Faculty of Economics and administration, Department of Human Resource Management, King Abdulaziz University, Saudi Arabia
Management 2024;28(2):33-69
KEYWORDS
JEL CLASSIFICATION CODES
M12; M14; M54; J24; C38
TOPICS
ABSTRACT
This study investigates the relationships between workplace flexibility, employee engagement, and performance of employees working in public and private settings. The purpose is to understand how flexible work arrangements influence employee engagement and overall performance across various industries. This research was conducted using a descriptive quantitative method. A structured questionnaire was used to collect data from 400 employees across finance, technology, healthcare, and manufacturing industries. The measurement model’s reliability was evaluated using the partial least square (PLS) structural equation modeling (SEM) approach (see table 3). Cronbach alpha (α) and composite reliability (CR) values were used. A prognosis model evaluation shows that all of the variables have SRMR values of 0.082 and NFI values of 0.914, suggesting that the model accurately matches with the experimental data. The Q2 predict value for employee performance (EP) of 0.352 shows excellent predictive relevance with a significant impact size. In comparison, the Q2 predict predictive value for Employee Engagement (EENG) is 0.185, indicating good predictive relevance with a modest impact size. These Q2Predict values are higher than the required minimum threshold of 0.00, indicating that the model is highly
predictive for each variable. Furthermore, the Q2 effect sizes for EENG and EPC show that they have a significant impact on the endogenous variable (WPFX). SmartPLS 3.3.9 used the PLS algorithm as well as the bootstrapping approach to evaluate the presented hypothesis. Table 6 shows the beta values that demonstrate the intensity and significance of the positive link between the dependent and independent variables, where employee engagement acts as both a moderator and mediator. By
including both mediation and moderation in the same model, you can gain a more comprehensive understanding of how workplace flexibility impacts employee performance, considering the mediating role of employee engagement and the moderating effect of its level. In addition to the above analysis, In addition, demographic factors are tested by Manova.
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