1408
Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Chapter 83
Steven A. Cavaleri
Central Connecticut State University, USA
Chester S. Labedz Jr.
Central Connecticut State University, USA
George H. Stalker
Dataleaf Technologies, Inc., USA
Emergent Dynamics of
Workforce Program Reductions:
A Hybrid Multi-Level Analysis
ABSTRACT
This paper reports on research that explores designing a hybrid system dynamics/agent modeling (HSDAM)
simulation methodology to evaluate potential effects of a new human resources policy in a company. The
study measures the effect of changes in the company’s pension policies on individual employee retention,
promotion and employment longevity. The Delphi method for elicitation of expert views was used, as
four expert panels composed of human resource specialists and general managers participated in model
design and predicted employee behavior. The model integrates multi-level organizational data inputs
from macro-level business data to granular individual-level employee information. Each simulation
run used four years of workforce longitudinal data at the start. Initially, the expert panel predictions
did not validate simulation results. However, once alteration of a key model parameter recalibrated
individual employees as more economically rational, later runs provided strong support for the model
and modeling approach. The simulation results confrmed, among several expert panel predictions, that
setting a policy that decreased the likelihood of employee willingness to retire due to replacement income
concerns could lead to other consequences with potentially adverse strategic implications for the frm.
DOI: 10.4018/978-1-4666-1601-1.ch083