A novel approach to selection of resilient measures portfolio under disruption and uncertainty: a case study of e-payment service providers

Ahmad Jafari Ghezelhesar () and Ali Bozorgi-Amiri ()
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Ahmad Jafari Ghezelhesar: University of Tehran
Ali Bozorgi-Amiri: University of Tehran

Operational Research, 2022, vol. 22, issue 5, No 25, 5477-5527

Abstract: Abstract The increasing development of trade activities and the high frequency of destructive events in the business environment have exposed organizations to various disruptions and operational risks that adversely affect their financial and operational performance. Organizations must, therefore, adopt enterprise risk management approaches to manage risks and prevent/mitigate potential losses. This study proposes a novel quantitative risk management framework based on organizational resilience and business continuity planning for service-based organizations. The proposed framework includes a multi-objective model to cope with disruptions by employing optimal preventive and mitigation action plans. The inherent uncertainty of parameters is tackled using a modified version of the light robust approach. This study aims to adopt an optimal portfolio of resilience strategies and business continuity plans to minimize the average loss in the organization’s operational performance and the total post-disruption recovery time and maximize the total recovery capability of the resilience strategies and continuity plans and the number of time intervals with desirable performance based on business continuity management indicators. An e-payment service provider is also examined as a case study to ensure the reliability and applicability of the proposed model. Based on the results, adopting proper resilience strategies and business continuity plans can improve an organization's capability in managing destructive events and help the organization achieve a viable competitive advantage in the turbulent business environment.

Keywords: Financial systems; Risk management; Business systems; Mathematical modelling; Complexity (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s12351-022-00709-x

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