Time—Path Types: From Static to Dynamic Typologies

Biometrics and psychometrics have developed a variety of methods to derive empirically clusters or types of variables, objects, or subjects. These empirical classificatory methods have been applied to data at one point in time—they have been used for static analyses. An extension is presented to the case of dynamic analyses, that is, the empirical identification of subjects with different time changes in one or more observed characteristics and their grouping based on sufficient similarity of time changes. Two management applications of the extension are given, the first dealing with behavioral, and the second with behavioristic, data.

• 저널Management Science · 16(10) · B–584
• 토픽Neural Networks and Applications · Artificial Intelligence
• DOI10.1287/mnsc.16.10.b584
• 저자John G. Myers, Francesco M. Nicosia