Journal
ACM TRANSACTIONS ON MANAGEMENT INFORMATION SYSTEMS
Volume 14, Issue 3, Pages -Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.1145/3607875
Keywords
Bayesian learning; personality traits; work behavior
Categories
Ask authors/readers for more resources
In this article, a data-driven joint Bayesian learning approach called Joint-PJB is introduced to discover explainable joint patterns from personality and job-position-related behavioral data. The model is found to effectively measure the matching degree between employees and their work behaviors, and it showcases its utility in real-world talent management decisions.
Personality has been considered as a driving factor for work engagement, which significantly affects people's role performance at work. Although existing research has provided some intuitive understanding of the connection between personality traits and employees' work behaviors, it still lacks effective quantitative tools for modeling personality traits, job position characteristics, and employee work behaviors simultaneously. To this end, in this article, we introduce a data-driven joint Bayesian learning approach, Joint-PJB, to discover explainable joint patterns from massive personality and job-position-related behavioral data. Specifically, Joint-PJB is designed with the knowledgeable guidance of the four-quadrant behavioral model, namely, DISC (Dominance, Influence, Steadiness, Conscientiousness). Based on the real-world data collected from a high-tech company, Joint-PJB aims to highlight personality-job-behavior joint patterns from personality traits, job responsibilities, and work behaviors. The model can measure the matching degree between employees and their work behaviors given their personality and job position characteristics. We find a significant negative correlation between this matching degree and employee turnover intention. Moreover, we also showcase how the identified patterns can be utilized to support real-world talent management decisions. Both case studies and quantitative experiments verify the effectiveness of Joint-PJB for understanding people's personality traits in different job contexts and their impact on work behaviors.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available