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Articles 1 - 6 of 6
Full-Text Articles in Business
Contingency Planning Amidst A Pandemic, Natalie C. Belford
Contingency Planning Amidst A Pandemic, Natalie C. Belford
KSU Proceedings on Cybersecurity Education, Research and Practice
Proper prior planning prevents pitifully poor performance: The purpose of this research is to address mitigation approaches - disaster recovery, contingency planning, and continuity planning - and their benefits as they relate to university operations during a worldwide pandemic predicated by the Novel Coronavirus (COVID-19). The most relevant approach pertaining to the University’s needs and its response to the Coronavirus pandemic will be determined and evaluated in detail.
A Credit Analysis Of The Unbanked And Underbanked: An Argument For Alternative Data, Edwin Baidoo
A Credit Analysis Of The Unbanked And Underbanked: An Argument For Alternative Data, Edwin Baidoo
Doctor of Data Science and Analytics Dissertations
The purpose of this study is to ascertain the statistical and economic significance of non-traditional credit data for individuals who do not have sufficient economic data, collectively known as the unbanked and underbanked. The consequences of not having sufficient economic information often determines whether unbanked and underbanked individuals will receive higher price of credit or be denied entirely. In terms of regulation, there is a strong interest in credit models that will inform policies on how to gradually move sections of the unbanked and underbanked population into the general financial network.
In Chapter 2 of the dissertation, I establish the …
A Novel Penalized Log-Likelihood Function For Class Imbalance Problem, Lili Zhang
A Novel Penalized Log-Likelihood Function For Class Imbalance Problem, Lili Zhang
Doctor of Data Science and Analytics Dissertations
The log-likelihood function is the optimization objective in the maximum likelihood method for estimating models (e.g., logistic regression, neural network). However, its formulation is based on assumptions that the target classes are equally distributed and the overall accuracy is maximized, which do not apply to class imbalance problems (e.g., fraud detection, rare disease diagnoses, customer conversion prediction, cybersecurity, predictive maintenance). When trained on imbalanced data, the resulting models tend to be biased towards the majority class (i.e. non-event), which can bring great loss in practice. One strategy for mitigating such bias is to penalize the misclassification costs of observations differently …
Business Analytics Programs In Business School: What Can Marketing Do?, Yanbin Tu
Business Analytics Programs In Business School: What Can Marketing Do?, Yanbin Tu
Atlantic Marketing Association Proceedings
No abstract provided.
Social Media And University Enrollment: Can Social Media Be Used To Raise Awareness Of University Programs?, Hannah Nicole Starnes, Kelly Green Atkins
Social Media And University Enrollment: Can Social Media Be Used To Raise Awareness Of University Programs?, Hannah Nicole Starnes, Kelly Green Atkins
Atlantic Marketing Association Proceedings
No abstract provided.
Financial Technology Usage 2017 Predictive Analytics Study, Alan D. Smith
Financial Technology Usage 2017 Predictive Analytics Study, Alan D. Smith
Atlantic Marketing Association Proceedings
No abstract provided.