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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/CA0D9FC0-8EE1-4156-A582-1E1D2157DD91 | ||
| Year | 2022 | ||
| Type of Item | Book Chapter | ||
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| Bibliographic Citation | A. Podaras, K. Moirogiorgou, and M. Zervakis, “Regression-based recovery time predictions in business continuity management: a public college case study,” in Research Anthology on Business Continuity and Navigating Times of Crisis, IGI Global, 2022, pp. 240-267, doi: 10.4018/978-1-6684-4503-7.ch013. https://doi.org/10.4018/978-1-6684-4503-7.ch013 | ||
| Appears in Collections |
Business continuity is crucial for modern public organizations. It enables the uninterrupted operation of critical business functions and services in the event of an unexpected crisis situation. A key business continuity activity is to set proactively and non-arbitrarily recovery priorities while computing the recovery time effort (RTE) for these functions. The specific activity requires the consideration of technical and environmental factors of individual business functions in order to compute mathematically their recovery time. A recently published formula stems from the business continuity points method. Its limitation has been the absence of real data during its conception. The purpose of the chapter is firstly, to use business continuity data from a public college in order to validate the initial formula and, secondly, to infer a new more accurate and robust RTE equation based on regression analysis techniques. The inferred RTE formula can be used as input for predicting service availability rates.
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