PERCEIVED INFORMATION STRUCTURE: IMPLICATIONS FOR DECISION SUPPORT SYSTEM DESIGN
研究了决策者对信息项的感知复杂度（维度），并通过多维尺度分析将具有相同感知的决策者分类，为设计更有效的决策支持系统提供依据，有助于降低信息成本并提升决策质量。
ABSTRACT Top‐level decision making in business organizations is characterized by high degrees of uncertainty, incomplete information, and conflicting objectives. To support top‐level decision making effectively, decision support systems (DSSs) have been proposed. Information supplied by a DSS must be selective in that not all possible information sets may be feasibly or economically represented in the data base. This study suggests that discovery of perceptual complexity (dimensionality) of information items, and the subsequent categorization of decision makers having the same perceptions of those information items, is a first step in the ultimate design of an effective DSS. Through the use of multidimensional scaling in a field setting, this study shows the feasibility of creating relatively homogeneous groups of decision makers according to the content and number of dimensions associated with various information items. Further results of the research suggest that information can be tailored to classes of users, which has cost‐benefit implications as well as the potential to improve the quality of the resultant decisions.