
doi: 10.2139/ssrn.3038567
We can overcome uncertainty with uncertainty. Using randomness in our choices and in what we control, and hence in the decision making process, could potentially offset the uncertainty inherent in the environment and yield better outcomes. The example we develop in greater detail is with regards to the creation and dissemination of knowledge. That there is uncertainty in this process, is perhaps, not to be debated. Our initial analysis shows that one of the better solutions, we can accomplish in this space, might be described by the prescription, “Don’t Simply Optimize, Also Randomize; best described by the term - Randoptimization”. We specifically show that the best decision we can make, with regards to the selection of articles by journals (and in a subsequent paper, with respect to school admissions), requires us to formulate a cutoff point, or, a region of optimal performance and randomly select from within that region of better results. The policy implication (for all fields) is to randomly select papers, based on publication limitations (journal space, reviewer load etc.) from an overall pool of submissions, that have a single shred of knowledge (or one unique idea) and have the editors and reviewers coach the authors to ensure a better final outcome.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
| 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 |
