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 International Conference on Complex Systems (ICCS2007)

Title: Time-Behavior Models: A Conceptual Tool for Analyzing Decision-Making Options When Multiple Timescales and Network Effects Come into Play.

Neil Wasserman
Adaptive Service Engineering, Belmont, MA

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     Last modified: October 4, 2007

Numerous studies in behavioral economics show that human decision-making tends to overweight short-term benefit over longer-term opportunity. The inability to pay proper attention to effects that emerge slowly over extended periods of time poses challenges to addressing problems in widely varying domains, including savings behavior, climate change, and health behaviors.

The paper presents an approach to modeling individual human and organizational behaviors which are periodic and which extend over a range of timescales. Within this "time-behavior" framework, the determinants for shifting from short-response to longer-term regularized behaviors are examined from a cognitive and information theoretic perspective. A model is developed which differentiates short-term behaviors (called tŘ) from behavior which are characterized by repeated events with cumulative impact over time. These “t1-behaviors” reflect a type of Fourier decomposition of behaviors with multiple periodicities. T2 and t3-behaviors are introduced which account different network effects as t1-behaviors are replicated across populations. The model can be used as both a descriptive tool which accounts for powerful growth effects and a decision making tool to identify critical behaviors that act as control points for influencing change in a particular environmental domain. The paper suggests ways to understand the infrastructure that supports the transition from short-term tŘ time-behaviors to regularized t1 and higher-order behaviors. The model is structurally stable when applied to varying domains in financial services, healthcare, environment, and organizational change. Examples are provided.

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