Abstract
dc:description.abstract<p>Complex systems are characterized by their high level of inter-connectivity, ambiguity, and emergence. Therefore, a failure in one element of a system (e.g. cyber layer) due to external or internal disturbances can lead to a cascade effect that may influence all elements of the system. Consequently, the complex system will not be able to perform its functional performance. Threats related to complex systems are very dynamic, fast, complex and damage can be severe. Thus, to respond to the dynamic and unpredictable nature of these threats, complex systems need to be highly adaptive to survive and thrive in the face of adversity. Adaptive capacity gives the system the ability to adjust and cope with the new circumstances and conditions resulting from an adverse event.</p> <p>This research addresses the gap in the literature by developing an assessment instrument that captures the key organizational factors necessary for developing and monitoring adaptive capacity in complex systems. These organizational factors serve as criteria to measure the adaptive capacity and improve resilience as well. The presence of these criteria is critical to any complex system, without which resilience is unlikely to be maintained.</p> <p>To develop the assessment instrument, a four-phase research design approach was developed and executed. A grounded theory approach was employed to establish organizational criteria for the adaptive capacity assessment. More than one hundred diverse data sources were analyzed and coded to identify organizational factors that determine adaptive capacity in complex systems. After deriving the organizational criteria, an assessment instrument was developed. The assessment instrument consists of thirty-eight organizational criteria grouped into nine categories. This assessment instrument was then validated by subject matter experts. The experts have provided positive feedback that the proposed instrument is viable and adequate to accomplish its stated purpose.</p>
Degree
thesis:*- 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
- 2020
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Alfaqiri, Abdulrahman
- Contributors dc:contributor
-
- C. Ariel Pinto
- Adrian Gheorghe
- Wie Yusuf
Subjects
dc:subject × 9Identifiers
dc:identifier.*- Identifier
- 9798678109729
- OAI identifier oai:identifier
- oai:digitalcommons.odu.edu:emse_etds-1179