A Dynamic, Computational Model of Job Insecurity and Job Performance

Despite decades of research, there is little empirical or theoretical consensus around how job insecurity shapes job performance. This article introduces an ecumenical, dynamic, and computational model of the job insecurity-job performance relationship. That is, rather than representing a single theoretical perspective on job insecurity effects, the model includes three key mechanisms through which job insecurity is theorized to impact performance-stress, social exchange, and job preservation motivation-and grounds these in a self-regulatory computational architecture. The model incorporates multiple, dynamic feedback loops that include job performance and job insecurity, as well as individual difference and contextual constructs to project the immediate, short-term, and long-term effects of changes to job security and other important variables. Simulations of the model demonstrate that a self-regulating representation of human information processing can produce effects consistent with the major propositions in the job insecurity literature. Moreover, interrupted time-series simulations of a new job insecurity threat reveal how, when, and why performance can stabilize above, near, or below baseline performance levels, sometimes for counterintuitive reasons. Additionally, the model shows how the frequently reported, cross-sectional, negative relationship between job insecurity and job performance can be explained by job performance's influence on job insecurity. The results imply important considerations and directions for future job insecurity research and demonstrate the value of a formal, dynamic systems approach to theorizing.