Note: [] Corresponding author. %Departments of Electrical %and
Bioengineering, University of Texas at Arlington, Arlington, TX, USA. E-mail: kondraske@uta.edu
Abstract: General Systems Performance Theory (GSPT) is relatively new and was
motivated by attempts to obtain a quantitative understanding of the interface
of human systems to tasks. However, the general nature of this work is
emphasized in that it is applicable to any system (human or artificial) at any
hierarchical level. Most experimental investigations of GSPT have involved the
human system, which is argued to be representative of a circumstance that
includes great complexity in itself. The need for GSPT, key constructs of it,
and experimental work are summarized. GSPT concepts are used retrospectively
with focus on several other systems to explain common errors made in design and
other circumstances that often lead to unforeseen consequences. Relatively
simple approaches to demonstrate how GSPT methods could minimize or prevent
such errors are delineated. To emphasize the broad applicability of GSPT,
several speculative new, contemporary problem contexts are discussed with
preliminary guidance regarding recommended measurements and assessment
processes. Thus, to realize predictable change in a complex system, it is
asserted that one must first have a reasonable understanding of the
relationship between key components that form a system at any instant in time.
It is ultimately argued in this chapter that: 1) performance is an omnipresent
and ultimate concern, 2) performance variables are special and a quantitative
understanding of the threshold-based (and not correlation-based), resource
economic relationship between performance attributes across hierarchical levels
is essential, and 3) assessment of the notion of ``change'' (i.e., in the
evolution of complex systems and our understanding of this process) depends, in
many situations, first upon valid characterization and understanding of systems
from a performance perspective.