What theories are especially relevant to decision support research?

by Daniel J. Power
Editor, DSSResources.COM

A theory is an organized set of ideas that explain a phenomenon. In decision support research a theory might explain use or lack of use of a decision support capability. A different relevant theory might explain adoption of decision support capabilities. Theory might explain the failures and successes of decision support. Finally theories might inform impacts of decision support capabilities on organizational behaviors and organizational functioning and success. There are many theories linked to Information Systems research (Larsen, Allen, Vance, and Eargle, 2015). Researchers interested in studying various decision support capabilities and technologies and in designing novel systems can potentially benefit from a more focused summary of theoretical frameworks.

Administrative behavior theory

Herbert Simon argued "The capacity of the human mind for formulating and solving complex problems is very small compared with the size of the problems whose solution is required for objectively rational behavior in the real word.” Based upon that generalization, Simon suggests decision makers are satisficing rather than maximizing goals and outcomes. The rationality of decision makers in inherently bounded and limited.

Behavioral decision theory

Slovic, Fischhoff, and Lichtenstein (1977) concluded "because of limited information-processing capacity and ignorance of the rules for optimal information processing and decision making, people’s judgments are subject to systematic biases. (p. 14)" Normative theory like Multi-attribute Utility Theory (MAUT) prescribes courses of action based upon a decision maker’s beliefs and values. Descriptive decision theory examines these beliefs and values and how people incorporate them into their decisions.

Cognitive fit theory

Vessey (1991) proposed that correspondence, congruence or fit between task and information presentation format resulted in superior task performance for individual users.

Cognitive load theory

Cognitive load refers to the effort being used by a person to process data and information. System designers must consider the amount of cognitive load. Driver and Streufert (1969) postulate that "individuals and groups can be viewed as information-processing systems which respond in a curvilinear fashion to three components of input load: complexity of information, noxity (unpleasantness) and eucity (pleasantness)." They postulated there is an optimal input load where each system is expected to achieve maximum complexity in information-processing.

Information processing theory

Multi-attribute utility theory

Prospect theory

Socio-technical theory

Task-technology fit

Technology acceptance model

Work systems theory


Driver, M. J. and S. Streufert, "Integrative Complexity: An Approach to Individuals and Groups as Information-Processing Systems," Administrative Science Quarterly, 14(2):272, June 1969, DOI: 10.2307/2391105

Larsen, K. R., Allen, G., Vance, A., Eargle, D. (Eds.) (2015). Theories Used in IS Research Wiki. Retrieved June 20, 2015 from

Slovic, P., B. Fischhoff, and S. Lichtenstein, "Behavioral Decision Theory," Annual Review of Psychology,Vol. 28:1-39, February 1977 at URL

Vessey, I., "Cognitive Fit: A Theory-Based Analysis of the Graphs Versus Tables Literature," Decision Sciences 22,(2), 1991, pp. 219-240.

Last update: 2018-09-13 08:24
Author: Daniel Power

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