Abstract
In an age of cloud computing, mobile users, and wireless networks, the availability of decision support related computing resources can no longer guarantee five-nines (99.999%) availability. Since the dependence on decision support systems is ever increasing, obtaining accurate deterministic advice from these systems will become critical. This study proposes a probabilistic model that maps decision resource availability to correct decision outcomes. Grounded in system reliability theory, the probability functions are given and developed. The model is evaluated with a simulated decision opportunity and the outcome of the experimentation is quantified using a goodness of fit measure and ANOVA testing.
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