Abstract
In the present era of high standards competitive market and business globalization, it becomes difficult to balance financial uncertainties based on market requirements that are influenced by multiple attributes (criteria) involving multiple stakeholders. Further, we encounter many challenges arising from multiple input data sets of vague and imprecise nature that reflect the final options and outcomes (alternatives). Moreover, the prevailing models lack proper applicability of aggregation techniques to resolve the ambiguity of multiple data sets or where more than one experts are involved. Further, do not focus to quantify the uncertainty of complex decision problems representing positive (acceptance) and negative (renunciation) attributes. Those attributes, signifying benefits, and opportunities (BO), and latter costs, and risks (CR) respectively. To address these issues, this book chapter illustrates an analytical methodology representing BOCR models. The modeling has been carried out in the combination of appropriate analytical models and suitable data aggregation techniques. The proposed framework is illustrated by considered two case studies. The first case study illustrates a holistic model in the context of prototype dependability assessment of software at the prototype level. The second case study demonstrates a model validation quantitatively for quality of services (QoS) for real-world SOA based applications.
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Acknowledgements
Part of the research work was carried out (funded and supported) at (i) University of Alberta (U of A), Edmonton, Canada and (ii) Banking Labs Inc, Toronto, a Canadian Architecture and Strategy consulting firm. Results from the labs are curated to measure and revise the framework.
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Kovur, K.M., Gedela, R.K. (2020). An Integrated Approach of BOCR Modeling Framework for Decision Tool Evaluation. In: Karanki, D., Vinod, G., Ajit, S. (eds) Advances in RAMS Engineering. Springer Series in Reliability Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-36518-9_5
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