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Estimating Probabilities of Research Success in the Atmospheric Sciences: Results of a Pilot Investigation
Author(s) -
Julian Paul R.,
Kates Robert W.,
Sewell W. R. Derrick
Publication year - 1969
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/wr005i001p00215
Subject(s) - optimism , atmospheric research , degree (music) , resource (disambiguation) , operations research , econometrics , stochastic game , computer science , statistics , environmental science , meteorology , psychology , mathematics , geography , social psychology , computer network , physics , mathematical economics , acoustics
In this paper we have two main objectives. The first of these is to outline a research and payoff (R&P) model that suggests a procedure for evaluating competing or concurrent research projects. The atmospheric sciences provide a good example for an initial application of the model. Weather modification, particularly artificial stimulation of precipitation, has been touted as an answer to many water resource problems. Alternatives to this technology have received little attention. We suggest that the R&P model could profitably be applied in this instance. The second objective of the paper is incorporated in a pilot study of the first step in such an application: namely, the determination of the estimated probabilities of success of various technologies in the atmospheric sciences. For this step, responses to a questionnaire sent to professional atmospheric scientists were examined to determine whether (a) scientists are willing to provide probability estimates of success of various technologies and whether these estimates are consistent with other estimates of success; (b) personal involvement in a field influences such estimates; (c) the probability estimates are consistent with the respondents' assignment of shares of a research budget; and (d) the estimates are generally in agreement with the reports of ‘blue‐ribbon’ panels of experts. We conclude that it is possible to obtain reasonably consistent estimates of research success from those who know most about them. The degree of optimism among those sampled is high, and it is highest for those workers involved in and having a high degree of knowledge of a particular field. Continued efforts in the determination of research success probabilities specifically tailored to the R&P model are recommended.