Reimagining the Employee Selection Process
Researchers revisit the traditional approach to employee selection. They offer some valuable tips on how organizations can get more out of the hiring process.
Researchers revisit the traditional approach to employee selection. They offer some valuable tips on how organizations can get more out of the hiring process.
New research explores accuracy and bias in automated transcription software used in interviews.
Recent research shows that when job applicants are forced to wait during the job interview stage, they become less attracted to the organization.
New research explores strategies to reduce ADHD-related challenges on conscientiousness tests.
New research shows that when employees are participating in virtual interviews, eye contact can impact their ratings.
This review examines how autonomy-enhancing algorithmic procedures (AEAPs) can improve acceptance of algorithmic decision-making in personnel selection by allowing practitioners to retain a sense of control.
New research finds that machine learning techniques offer a nuanced perspective on personality and job performance.
New research highlights the potential pitfalls of disclosing mental health conditions on LinkedIn.
Research addresses the challenges associated with using artificial intelligence (AI) for personnel selection. It finds that providing clear explanations may improve the trust that people place in these tools.
Harvard Business Review explains how organizations can utilize different interview methods to get what they want out of the job interview process.