Personality, Relationships, and Decision Making with Relational Dynamics: Personality and Relational Dynamics

Personality, Relationships, and Decision Making with Relational Dynamics: Personality and Relational Dynamics

David S. Bathory (Bathory International, USA)
DOI: 10.4018/978-1-5225-0159-6.ch061
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Abstract

Within the field of Economics there is great interest in predicting the future. In creating Economic Models the rationale has been to create fixed equations that can account for all variables associated with the issues of capital, labor, wages, prices, tariffs and taxes but few models explored the human variable. Probability Statistics bases decision making models upon mathematical predictions. Game Theory is an economic model that begins to explain the rationale of human decision making, but fails to account for flawed thinking and pathology. Relational Dynamics attempts to provide a means of understanding the strategies used in communication and decision making. Within humanity, not all decisions are made rationally and to account for illogical choices, psychology has provided theories of pathology to explain human idiosyncrasies. This paper will explore personality disorders as described by the DSM V and Relational Dynamics in an attempt to understand how pathology influences relationships, decision making and behavioral economics.
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Economics And The Psychology Of Decision Making

Economics has attempted to predict the ebb and flow of resources and human interaction with the market of supply and demand. Psychology has attempted to understand human behavior and predict patterns of behavior that appear to be advantageous to society (non-pathologic) and non-advantageous (pathologic). Just as markets change in the world’s economy, what is considered pathology changes within psychology in response to the normative view in a particular setting (e.g. culture) or time period (e.g. Victorian Era). An effort has been made since the conception of both disciplines to discover “the model” for prediction, yet in reality, models created for dynamic forces require fluidity rather than a fixed equation. The difficulty with prediction and a “moving target” is that the model must also be able to adapt to fluxions (Hubbard & Kane, 2013). Chaos Theory is a related model that attempts to understand the immediate and long term effects created by a single event or variable on others, or a combination of multiple events and how they transform into something greater than conventional addition (Gleick, 1987).

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