Collaborations

This collaboration covers the use of artificial intelligence and machine learning–supported analyses to examine how employees’ psychosocial characteristics and work-related behaviors are associated with safety behaviors and to develop predictive models based on these factors.

The purpose of this collaboration is to assess job applicants’ personality characteristics through a story-based mobile application. Within this scope, the project aims to generate AI-supported personality profiles from the collected data and to evaluate the validity, reliability, and other psychometric properties of the assessment tool. It also seeks to develop a scientifically grounded system that matches organizational needs with applicants’ individual characteristics in a systematic way. Overall, the goal is to establish an innovative and data-driven framework for both assessment and person–organization fit.

This cooperation protocol involved counseling and training in employee well-being, workplace safety, workplace stress, and diversity management. The aim was to strengthen organizational awareness, improve employee experience, and support practical areas of development.

Within the scope of this study, a situational judgment test based on workplace-relevant scenarios was developed and administered to assess the growth mindset levels of İzmir Chamber of Commerce staff. In this way, a context-sensitive measurement tool for evaluating growth mindset in an organizational setting was established.

This collaboration involved a comprehensive assessment of employee-related factors, work processes, and organizational practices associated with safety. Using multiple data collection and analysis methods, the study focused on identifying strengths, development areas, and practical recommendations for improvement.