Return to search

Multi-Level Analytic Network Process Model to Mitigate Supply Chain Disruptions in Disaster Recovery Planning

Over the past few decades, environmental changes have led to more frequent occurrences and greater intensities of natural disasters worldwide. In terms of globally connected supply chains, this has resulted in an enormous economical loss for corporations. Therefore, Business Continuity and Disaster Recovery (BC/DR) planning and management has become essential for businesses in order to protect their critical business flow. Yet there is a lack of systematic and transparent methodologies for companies to handle this problem.
Hence, this thesis introduces a novel approach to combine consecutive steps of the Disaster Recovery Planning (DRP) process within one application. The multi-criteria decision-making (MCDM) tool called the Analytic Network Process (ANP) is employed to identify critical products of a business and match them with optimal disruption mitigation strategies based on an evaluation of benefits, opportunities, costs, and risks (BOCR).
To validate the method developed in this thesis, a case study using historical data of a U.S. company (Company XYZ) is introduced. The results of the ANP mathematical modeling demonstrate that the developed methodology provides a valuable approach to analyze and confirm BC/DR planning decisions. Moreover, an expert of Company XYZ confirmed that the suggested solution established through this case study is in agreement with the preferable choice based on his expertise and professional decision-making.
Further research could extend the proposed methodology to other fields of BC/DR planning, such as IT Disaster Recovery Planning or Human Disaster Relief.

Identiferoai:union.ndltd.org:CALPOLY/oai:digitalcommons.calpoly.edu:theses-2708
Date01 April 2016
CreatorsKroener, Martina Ursula
PublisherDigitalCommons@CalPoly
Source SetsCalifornia Polytechnic State University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceMaster's Theses

Page generated in 0.0025 seconds