Document Type
Dissertation
Date of Award
Spring 5-31-2016
Degree Name
Doctor of Philosophy in Information Systems - (Ph.D.)
Department
Information Systems
First Advisor
Murray Turoff
Second Advisor
Starr Roxanne Hiltz
Third Advisor
Jerry Fjermestad
Fourth Advisor
Julian M. Scher
Fifth Advisor
Thomas Wilkin
Abstract
Small businesses, which are defined by the US Small Business Administration as entities with less than 500 employees, suffer interruptions from diverse risks such as financial events, legal situations, or severe storms exemplified by Hurricane Sandy. Proper preparations can help lessen the length of the interruption and put employees and owners back to work. Large corporations generally have large budgets available for planning, business continuity, and disaster recovery. Small businesses must decide which risks are the most important and how best to mitigate those risks using minimal resources.
This research uses a series of surveys followed by mathematical modeling to help discover risk factors, mitigating actions, and the highest return scenarios as a basis for a low-cost business continuity/disaster recovery plan. The surveys use a Delphi study format in order to rank a base list of risks and mitigating actions and to supplement those lists with ones added by the participants. Survey results are analyzed and presented back to the group for a second round of ranking and supplementing the risk/action categories. After two rounds of surveys the data is presented to an expert panel to investigate how the risks interrelate. Quantifying the interrelationships is the basis for the Cross Impact Analysis model that is able to show the relative impact of one event upon another. Once the impacts are known, a series of high valued scenarios are developed using Interpretive Structural Modeling. These high valued scenarios can be used by the small businesses as a basis for a business continuity/disaster recovery plan.
Recommended Citation
Hendela, Arthur Henry, "Collaborative development of a small business emergency planning model" (2016). Dissertations. 69.
https://digitalcommons.njit.edu/dissertations/69
