Information representation and decision process: Effects of measurement scale and shape on decision matrix on preferential choice

Sheau-Farn Liang, Purdue University


Due to the continual innovation in information technology, vast amounts of information in various forms have become available to people for the purpose of decision making and problem solving. Consequently, how to represent the information to facilitate the processes of decision making and problem solving becomes a significant issue. The measurement scale and the shape of the decision matrix were proposed in this research as two information representation factors that influence the decision process. Hypotheses related to the transformation effort between measurement scales and the relationship between the number of alternatives and attributes were tested through two experiments based on the process tracing method. Sixty college students were recruited as subjects. A computerized information display board was developed to present the decision matrices and collect data. Subjects were also asked to verbalize their decision processes for further verbal protocol analysis. In Experiment 1, two independent variables were the value measurement scale with two levels (ordinal and interval), and the attribute measurement scale with three levels (nominal, ordinal and ratio). Three dependent variables representing the extent of particular decision strategies were obtained from subject's computer log and verbal protocol. In Experiment 2, the independent variable was the ALT/ATT ratio, the ratio of the number of alternatives to the number of attributes, with five levels (3/12, 4/9, 6/6, 9/4 and 12/3). Two dependent variables representing the information search patterns were obtained from subject's computer log. The results showed that decision strategies involving search against the attribute rank (e.g., lexicographic and elimination-by-aspects strategies) were used 30% more when the information was provided at the ordinal attribute measurement scale rather than at the nominal attribute scale. Also, with a constant task complexity, more information was searched when the ratio of the number of alternatives to the number of attributes was higher, while less information was searched when the ratio of the number of alternatives to the number of attributes was lower. It is suggested that the findings of this study should be considered in the design of information representation for Decision Support Systems and Management Information Systems.




Lehto, Purdue University.

Subject Area

Industrial engineering|Systems design

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