Developing a novel quantitative framework for business continuity planning

Hojat Rezaei Soufi, S. Ali Torabi and Navid Sahebjamnia

International Journal of Production Research, 2019, vol. 57, issue 3, 779-800

Abstract: Today’s competitive and turbulent environment persuades every organisation to implement a business continuity management system (BCMS) for dealing with disruptive incidents such as earthquake, flood, and terrorist attacks. Within a BCMS, effective and efficient business continuity plans (BCPs) must be provided to ensure the continuity of organisation’s key products. This study develops a novel approach to select the most appropriate BCPs which can meet the business continuity key measures. First, a risk assessment process is conducted to define the disruptive incidents for which the organisation should have suitable BCPs. Then, two different possibilistic programming models including hard and soft BCP selection models are developed to determine appropriate BCPs under epistemic uncertainty of input data. These models aim to maximise the resilience level of the organisation while minimising the establishment cost of selected BCPs.‏ Finally, a real case study is provided whose results demonstrate the applicability and usefulness of the proposed approach.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2018.1483586 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:57:y:2019:i:3:p:779-800

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2018.1483586

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().