WHAT factors WERE modeled for CONFLICTING RISK STRUCTURES?
CONFLICTING RISK STRUCTURES
CONFLICTING RISK STRUCTURES
CONFLICTING RISK STRUCTURES
Conflicting Risk Structures refer to situations where different risk management frameworks, strategies, or priorities within an organization, or between multiple organizations, are at odds with one another. This conflict can arise from various subfactors, including differences in risk tolerance, objectives, regulatory requirements, or approaches to risk assessment and mitigation.
COGNITIVE DIVERSITY
CONFLICTING RISK STRUCTURES
CONFLICTING RISK STRUCTURES
Cognitive Diversity refers to the inclusion of people who have different ways of thinking, problem-solving, processing information, and approaching tasks. It encompasses a variety of perspectives and mental models that individuals bring to a group based on their unique experiences, education, skills, cultural backgrounds, and personal characteristics.
DECISION QUALITY
CONFLICTING RISK STRUCTURES
DECISION QUALITY
Decision quality refers to the extent to which a decision-making process and its outcomes meet certain standards of effectiveness and reliability. It encompasses the thoroughness, objectivity, and soundness of the decision-making process, ensuring that decisions are well-informed, well-reasoned, and likely to achieve the desired results.
Decision quality refers to the extent to which a decision-making process and its outcomes meet certain standards of effectiveness and reliability. It encompasses the thoroughness, objectivity, and soundness of the decision-making process, ensuring that decisions are well-informed, well-reasoned, and likely to achieve the desired results. Decision quality focuses on both the process and the outcome, aiming to ensure that the best possible decision is made given the available information, resources, and circumstances.
WHAT METHODS WERE USED?
example of Research Design
The example dissertation's research design is quantitative, employing a cross-sectional study approach to investigate the relationships between conflicting risk structures, decision quality, and the moderating effects of cognitive diversity within cybersecurity risk management teams.
EXAMPLE OF DETERMINING STUDY participants
The study participants were 146 cybersecurity professionals with some level of technical certification and were currently employed in roles related to professional risk management. The selection criteria ensured that all participants had relevant cybersecurity and risk management expertise, allowing for a more accurate assessment of the factors influencing decision quality within this context. The participants' demographic details, such as age, gender, job experience, and educational background, were collected, but the high-level demographic data were not fully detailed in the study. This diverse group of professionals was chosen to explore the moderating effects of cognitive diversity—including expertise diversity and conflict-handling style—on the relationship between conflicting risk structures and decision quality. By targeting participants with substantial knowledge and experience in cybersecurity, the study aimed to enhance the validity and applicability of its findings to real-world settings in the cybersecurity domain.
EXAMPLE OF data collection
The data was collected using a survey administered through a panel service provider, Survey Gizmo. The sample included 146 cybersecurity professionals with relevant technical certifications and current employment in some aspect of professional risk management. This sampling strategy ensured that participants had a baseline level of expertise and experience in cybersecurity risk management, enhancing the study's relevance.
EXAMPLE OF data analysis
The study employed advanced statistical techniques, including Confirmatory Factor Analysis (CFA) and Partial Least Squares (PLS) regression, to test the hypothesized relationships and models. CFA was used to validate the measurement model and ensure the constructs were properly defined and measured. PLS regression helped assess the strength and direction of the relationships between the variables, particularly the moderating effects of cognitive diversity on decision quality.
EXAMPLE OF MEASURING validity, reliability, and methodological integrity
The research design included specific, testable hypotheses regarding the relationships between team cohesion, intragroup conflict, goal similarity, conflict resolution norms, cognitive diversity, and decision quality. These hypotheses were tested using a structured approach that allowed for the examination of both direct and moderating effects.