Algorithmic search in management decision systems

✍ Scribed by Laurence A. Madeo; Thomas J. Schriber

• Publisher: Elsevier Science
• Year: 1980
• Weight: 649 KB
• Volume: 13
• Category: Article
• ISSN: 0020-7373
• DOI: 10.1016/s0020-7373(80)80004-6

✦ Synopsis

Research on computer-based management decision systems has analyzed such factors as cognitive style, organizational influences, and format of output. This paper contributes to that set of research by proposing a combination of human (trial-and-error) search with algorithmic search. The combination, called guided search, is described together with an experimental setting for testing the usefulness of guided search.

Phase I of the experiment involved decision making in the context of four decision variables. In this phase, there was no significant difference in achieved objective function value between those with human search and those with guided search. Phase li took place with 11 decision variables. The subjects with guided search obtained significantly better decisions than did the subjects with human search. Although the subjects with guided search required more central processor time than did their counterparts, they used no more elapsed time and did not enter more user input.

The experimental results support the belief that in complex situations guided search can be an effective aid in decision making.