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oVerVieW
We began studies of this problem with studies
of organizational attention and decision-making
in DOE's nuclear waste management (Lawless et
al., 2008; Lawless et al., 2005). Since then, the
focus of the problem has become more general,
shifting from field research with observations of
citizen organizations advising the Department
of Energy (DOE) on its environmental cleanup
and laboratory simulations of DOE field results
to analyzing stock market data and working on
computational modeling (coupled differential
equations, control theory, AI, Gaussian distribu-
tions, uncertainty models, Fourier transform pairs,
continuous and discrete wavelets). The solutions
and evidence we have collected indicate that
the results apply to organizational models with
agents of any type, including those composed
of humans-robots-machines, the combination of
which necessarily invokes mathematical models
of organizations.
The problem is based on the type of informa-
tion available to social deciders. It has often been
assumed by scientists that this information is
“complete” and representative of what a human
agent believes at any one point in time (but below
see the review by Baumeister et al., 2005 on the
failure of self-esteem to predict academic or work
behaviors; and Kelley, 1991, on the failure of
preferences in game theory to predict the actual
choices made by humans playing games against
real opponents). However, we have concluded
that the information collected from an individual
agent is more or less meaningless, since human
agents spend their time making decisions under
the forces of interdependence.
Interdependence is both simple and complex.
Sensory observation limits the field of action
responses. As an agent acts on its environment,
its sensory observations are impacted, changing
future motor responses, and further changing ob-
servations with each iteration. More importantly,
and disconcerting for social-psychological and
organizational theorists, interdependence is a state
that collapses during measurement (e.g., surveys,
In this paper, we present the background of the
problem as we first discovered it. The problem
was organizational attention and its impact on
decision-making for which both can range in an
organization from fragmented to well-focused.
We discovered the problem while studying the
Department of Energy (DOE) nuclear waste
management program. We review the mathematics
behind our solution to the problem (conservation
of information, or COI) as well as its implica-
tions for the development of theory. We review
the status of its application to telemedicine and
e-health in Georgia as part of a new project for
us which we began late last year (Stachura et al.,
2009). And we provide a review of future steps
and our conclusions as they pertain to the problem,
the mathematics, and the particular application to
telemedicine and e-health.
bAckground
We have been developing theory over the past
decade for a computational model of organiza-
tions and decision-making, primarily centered
around the idea of the physics of the conserva-
tion of information (Lawless et al., 2009). Our
conservation of information (COI) model is based
on a preliminary theory of a social-psychological
harmonic oscillator (SPHO), in which Nash Equi-
libria act as points of conflict that drive a public's
attention back and forth as a conflict is driven
across time by self-interests. The oscillations
from an SPHO generate fluctuations that produce
information characteristic of an organization's
stability response, which forms the central part
of our model of the conservation of information
(COI). Our theory of SPHOs is not yet complete,
but the part that is complete appears to be well-
grounded and with provocative implications for
the advancement of social-psychological and
organizational theory.
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