Industrialorganizational

Industrial-organizational psychology, often abbreviated I-O psychology, is the scientific study of human behavior in workplaces. It applies psychological theories and research methods to issues such as employee selection, performance, motivation, leadership, and well-being with the goal of improving organizational effectiveness and the quality of work life.

The field encompasses two broad domains: personnel psychology, which covers recruitment, testing, training, and assessment; and organizational psychology, which focuses on leadership, teamwork, organizational culture, job design, and change management. I-O psychologists use methods such as job analysis, psychometric assessment, experiments, surveys, and field studies.

Historically rooted in early 20th-century studies of efficiency and the Hawthorne experiments, I-O psychology has evolved into a diverse applied science. Influential developments include scientific management, human relations, systems approaches, and data-driven decision making. Today the field integrates laboratory and real-world research to inform practice.

Applications span talent acquisition and development, performance appraisal, compensation and rewards, safety and ergonomics, work design, and organizational development. I-O psychologists also address diversity, equity, and inclusion, employee engagement, and the impact of technology—such as AI, analytics, and digital HR tools—on selection, assessment, and collaboration.

Education and professional practice typically require advanced degrees in I-O psychology, usually a PhD; master's programs exist as well. Licensure is variable by jurisdiction. Professional organizations include the Society for Industrial and Organizational Psychology (SIOP) in the United States and the European Association of Work and Organizational Psychology (EAWOP).

As workplaces change, I-O psychology emphasizes evidence-based practice, ethics, and methodological rigor, with growing emphasis on remote work, well-being, leadership development, and the ethical use of data and algorithms in human resources.