Faculty Research: Winter 2017
Eleanor Feit, PhD, Assistant Professor of Marketing, published a paper in the Journal of Interactive Marketing showing an association between traditional survey-based brand attitudes – awareness, consideration, familiarity, and purchase intent – and user’s brand searches on Google. This work suggests that Google search can be used to gauge the performance of a brand. Read more about Feit’s research.
David Gefen, PhD, Professor, Decision Sciences and MIS, conducted an analysis of medical reports in conjunction with a large health insurance provider. Using text-mining techniques, Gefen and his team identified risk factors that could help predict cardiac failure and classify unique cases of the condition.
Matthew Schneider, PhD, Assistant Professor, Decision Sciences and MIS, is conducting research on a framework permitting organizations to share their marketing data in order to gain commercial value while limiting the risks of privacy.
Chaojiang Wu, PhD, Assistant Professor, Decision Sciences and MIS, published a paper in Statistics and Computing on a newly developed framework that outperforms existing methods in identifying variables that lead to superior predictive power. The authors tested their framework using credit scoring and healthcare data.
In a paper to be published in Journal of Financial and Quantitative Analysis, Wu and his co-authors proposed a new statistical methodology to understand how the conditional capital asset pricing model can partially explain the value premium phenomena.
Information Systems Strategy
The strategic decisions around the design and management of information systems have an enormous impact on an organization’s capabilities to deploy analytics tools and gather business insights and intelligence. Research at LeBow focuses on key issues such as design of systems, outsourcing, and technology adoption. Application areas include healthcare systems, global supply chain management, and social media strategies.
Data mining is a process for exploring large datasets for patterns and relationships, and it plays a crucial role in predictive analytics for big data. Research at LeBow focuses on mining structured and unstructured data, including data capture/collection, storage, and management, statistical analysis for structured data, and text mining. Application areas include healthcare management, cyber-crime and cybersecurity, operations management, and marketing.
Applied Econometrics and Forecasting
Applied econometrics is the field of developing empirical quantitative models of the economic and business environment in order to develop sound forecasts. Research at LeBow focuses on building and using complex time series models, estimation techniques, and Bayesian statistics, as well as the performance and reliability of econometric software. Application areas include financial modeling and forecasting, educational assessment, antitrust and regulation, and operations management.
Insights and intelligence gained from data analysis can be used to improve business decisions. Optimization is a powerful technique for decision-making and falls into the categories of prescriptive and preemptive analytics. Research at LeBow focuses on the how to formulate and solve complex and large-scale optimization models, building customized software packages and decision support systems to do so, and incorporating risk management concerns, dynamic environments, and competition into the decision framework. Application areas include portfolio optimization, operations and supply chain management, and decision-making in the public sector.