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Cloud-based decision support systems and availability context: the probability of successful decision outcomes

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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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Authors and Affiliations

  1. Department of Information Systems & Technology Management, The George Washington University, Washington, DC, USA

    Stephen Russell

  2. Information Systems Department, University of Maryland, Baltimore County, MD, USA

    Victoria Yoon & Guisseppi Forgionne

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  1. Stephen Russell
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  2. Victoria Yoon
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  3. Guisseppi Forgionne
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Correspondence to Stephen Russell.

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Russell, S., Yoon, V. & Forgionne, G. Cloud-based decision support systems and availability context: the probability of successful decision outcomes. Inf Syst E-Bus Manage 8, 189–205 (2010). https://doi.org/10.1007/s10257-010-0126-4

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  • DOI: https://doi.org/10.1007/s10257-010-0126-4

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