Job Stress and Individual Creativity: A Screen-Based Partial Least Squares Structural Equation Modeling Protocol for...

Area of Science:

• Organizational Psychology
• Artificial Intelligence Studies
• Management Science

Background:

• Artificial intelligence (AI) integration is transforming workplace dynamics, affecting job demands, leadership perceptions, and employee creativity.
• The Job Demands-Resources (JD-R) model and Social Learning Theory provide frameworks for understanding these complex interactions.
• Existing research often overlooks the mediating role of leadership perceptions and moderating effects of AI in the stress-creativity link.

Purpose of the Study:

• To investigate the mediating role of ethical leadership perceptions in the relationship between job stress and individual creativity.
• To examine the moderating effect of organizational AI embeddedness on the ethical leadership-creativity relationship.
• To provide a reproducible survey-to-PLS-SEM workflow for empirical modeling.

Main Methods:

• Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed.
• A large sample size of 5,000 bootstrap resamples was utilized for robust analysis.
• The study integrated survey data with advanced statistical modeling techniques.

Main Results:

• Job stress was found to negatively impact perceptions of ethical leadership.
• Ethical leadership perceptions positively influenced individual creativity, acting as a significant indirect pathway from job stress.
• Organizational AI embeddedness significantly amplified the positive relationship between ethical leadership perceptions and creativity.

Conclusions:

• Employee creativity in AI-integrated environments is primarily influenced by organizational psychological factors, not just technology.
• Managing job stress and cultivating ethical leadership are crucial for enhancing creativity during digital transformation.
• Organizations should prioritize human-centric strategies alongside AI implementation to foster innovation.