
Abstract This paper examines various interpretations of key characteristics. Starting with Juran’s dictum of focusing on “vital few” and not on “trivial many”, it looks at a representative sample of extant definitions and examples. Causality and sensitivity are then discussed at some length. It is argued that it is the weighted sensitivities that determine what characteristics are key and that literature on design of experiments has supported this view all along. Finally, a statistical interpretation of key characteristics is offered as a unifying framework to capture many of the recent interpretations of key characteristics.
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| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
