Measuring Risks of Interdependencies in Enterprise Systems: An Application to Ghana’s Salt Enterprise

<p>This dissertation describes the use of Functional Dependency Network Analysis (FDNA) for modeling risks resulting from dependencies among elements of enterprise systems with application to salt processing enterprise in Ghana. FDNA was developed to model dependencies among members of enterprise systems by highlighting two dimensions of dependency: strength and criticality. Nonetheless, the concepts and analytics for these two dimensions of dependencies needed further development and generalization in the context of project management and systems development in developing countries.</p> <p>Managing risks within the interdependency in enterprise systems through integration will help improve global economic growth. Coherent theory for enterprise integration must be developed, especially in developing countries like Ghana. The significance of this dissertation is the further development of theoretical concept that can be used to analyze dimensions of dependencies in enterprise systems. This model development is contingent upon the strength and criticality dimensions of dependencies in enterprise systems as they apply to project management and the development of enterprise systems. The research covers empirical investigation of the complexities and of enterprise risk management in the Sub-Saharan region for the appropriateness of using the FDNA concept to develop the salt processing enterprise in Ghana.</p>

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Engineering Management & Systems Engineering

Year dc:date.available

2019

Author dc:creator

• Mensah, Yaw

Contributors dc:contributor

• C. Ariel Pinto
• Rafael Landaeta
• Michael McShane

• Economics
• Management
• Process safety
• Regression analysis
• Risk analysis
• Risk of interdependency network
• Chemical Engineering
• Systems Engineering

Identifier

9798641777566

OAI identifier oai:identifier

oai:digitalcommons.odu.edu:emse_etds-1173